1
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Van Havermaet S, Khaluf Y, Simoens P. Reactive shepherding along a dynamic path. Sci Rep 2024; 14:14915. [PMID: 38942794 PMCID: PMC11213918 DOI: 10.1038/s41598-024-65894-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2024] [Accepted: 06/25/2024] [Indexed: 06/30/2024] Open
Abstract
Shepherding, the task of guiding a herd of autonomous individuals in a desired direction, is an essential skill employed in the herding of animals, crowd control, and evacuation operations. Integrating shepherding capabilities into robots holds promise to perform such tasks with increased efficiency and reduced labor costs. To date, robotic shepherds have only been designed to steer a herd towards a predetermined goal location without constraints on the trajectory. However, the tasks of a sheepdog encompass not only steering the herd but also (i) maintaining the herd within a designated area and (ii) averting dangers, obstacles, or undesirable terrain such as newly sown land. We present a decentralized control algorithm for multi-robot shepherding designed to guide a group of animals along a specified path delineated by two boundaries. The algorithm incorporates the additional objective of preserving the group within these boundaries. Simulation results reveal that, especially in sections of the path with sharp turns and a small distance between the boundaries, the group exhibits a tendency to deviate beyond the prescribed margin. Additionally, our findings emphasize the algorithm's sensitivity to the ratio of robot-group sizes and the magnitude of the group's velocity.
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Affiliation(s)
- Stef Van Havermaet
- IDLab, Department of Information Technology, Ghent University - imec, B-9052, Gent, Belgium.
| | - Yara Khaluf
- IDLab, Department of Information Technology, Ghent University - imec, B-9052, Gent, Belgium
- Department of Social Sciences, Wageningen University and Research, 6706KN, Wageningen, The Netherlands
| | - Pieter Simoens
- IDLab, Department of Information Technology, Ghent University - imec, B-9052, Gent, Belgium
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2
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Chakrabortty T, Bhamla S. Controlling noisy herds. ARXIV 2024:arXiv:2406.06912v1. [PMID: 38947931 PMCID: PMC11213128] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 07/02/2024]
Abstract
The wisdom of the crowd breaks down in small groups. While large flocks exhibit swarm intelligence to evade predators, small groups display erratic behavior, oscillating between unity and discord. We investigate these dynamics using small groups of sheep controlled by shepherd dogs in century-old sheepdog trials, proposing a two-parameter stochastic dynamic framework. Our model employs pressure (stimulus intensity) and lightness (response isotropy) to simulate herding and shedding behaviors. Light sheep rapidly achieve a stable herding state, while heavy sheep exhibit intermittent herding and orthogonal alignment to the dog. High response isotropy enhances group cohesion but complicates group splitting. We construct a unified phase diagram for sheep behavior, identifying three regimes-fleeing, flocking, and grazing-based on group size and stimulus specificity. Increasing stimulus specificity shifts small group behavior from grazing to fleeing, while larger groups exhibit flocking. This transition underscores the challenge of controlling small indecisive collectives. Introducing the Indecisive Collective Algorithm (ICA), we show that deliberate indecisiveness and stochasticity improve control efficiency. ICA outperforms traditional averaging-based algorithms in high-noise settings and excels in tasks requiring group splitting. Our study offers a foundational framework for controlling small, indecisive groups, applicable to biochemical reactions, cell populations, and opinion dynamics.
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3
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Suh K, Thornton R, Farahani PE, Cohen D, Toettcher J. Large-scale control over collective cell migration using light-controlled epidermal growth factor receptors. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.05.30.596676. [PMID: 38853934 PMCID: PMC11160748 DOI: 10.1101/2024.05.30.596676] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2024]
Abstract
Receptor tyrosine kinases (RTKs) are thought to play key roles in coordinating cell movement at single-cell and tissue scales. The recent development of optogenetic tools for controlling RTKs and their downstream signaling pathways suggested these responses may be amenable to engineering-based control for sculpting tissue shape and function. Here, we report that a light-controlled EGF receptor (OptoEGFR) can be deployed in epithelial cell lines for precise, programmable control of long-range tissue movements. We show that in OptoEGFR-expressing tissues, light can drive millimeter-scale cell rearrangements to densify interior regions or produce rapid outgrowth at tissue edges. Light-controlled tissue movements are driven primarily by PI 3-kinase signaling, rather than diffusible signals, tissue contractility, or ERK kinase signaling as seen in other RTK-driven migration contexts. Our study suggests that synthetic, light-controlled RTKs could serve as a powerful platform for controlling cell positions and densities for diverse applications including wound healing and tissue morphogenesis.
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Affiliation(s)
- Kevin Suh
- Department of Chemical and Biological Engineering, Princeton University, Princeton 08544
- Omenn-Darling Bioengineering Institutes, Princeton University, Princeton 08544
| | - Richard Thornton
- Omenn-Darling Bioengineering Institutes, Princeton University, Princeton 08544
- Department of Molecular Biology, Princeton University, Princeton 08544
| | - Payam E Farahani
- Department of Chemical and Biological Engineering, Princeton University, Princeton 08544
| | - Daniel Cohen
- Omenn-Darling Bioengineering Institutes, Princeton University, Princeton 08544
- Department of Mechanical and Aerospace Engineering, Princeton University, Princeton 08544
| | - Jared Toettcher
- Omenn-Darling Bioengineering Institutes, Princeton University, Princeton 08544
- Department of Molecular Biology, Princeton University, Princeton 08544
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4
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Shamay-Tsoory SG, Kanterman A. Away from the herd: loneliness as a dysfunction of social alignment. Soc Cogn Affect Neurosci 2024; 19:nsae005. [PMID: 38287695 PMCID: PMC10873844 DOI: 10.1093/scan/nsae005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2023] [Revised: 12/06/2023] [Accepted: 01/24/2024] [Indexed: 01/31/2024] Open
Abstract
The tendency of all humans to experience loneliness at some point in their lives implies that it serves an adaptive function. Building on biological theories of herding in animals, according to which collective movement emerges from local interactions that are based on principles of attraction, repulsion and alignment, we propose an approach that synthesizes these principles with theories of loneliness in humans. We present here the 'herding model of loneliness' that extends these principles into the psychological domain. We hold that these principles serve as basic building blocks of human interactions and propose that distorted attraction and repulsion tendencies may lead to inability to align properly with others, which may be a core component in loneliness emergence and perpetuation. We describe a neural model of herding in humans and suggest that loneliness may be associated with altered interactions between the gap/error detection, reward signaling, threat and observation-execution systems. The proposed model offers a framework to predict the behavior of lonely individuals and thus may inform intervention designs for reducing loneliness intensity.
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Affiliation(s)
| | - Alisa Kanterman
- Department of Psychology, University of Haifa, Haifa 3498838, Israel
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5
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Hansen MJ, Domenici P, Bartashevich P, Burns A, Krause J. Mechanisms of group-hunting in vertebrates. Biol Rev Camb Philos Soc 2023; 98:1687-1711. [PMID: 37199232 DOI: 10.1111/brv.12973] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2022] [Revised: 04/24/2023] [Accepted: 04/26/2023] [Indexed: 05/19/2023]
Abstract
Group-hunting is ubiquitous across animal taxa and has received considerable attention in the context of its functions. By contrast much less is known about the mechanisms by which grouping predators hunt their prey. This is primarily due to a lack of experimental manipulation alongside logistical difficulties quantifying the behaviour of multiple predators at high spatiotemporal resolution as they search, select, and capture wild prey. However, the use of new remote-sensing technologies and a broadening of the focal taxa beyond apex predators provides researchers with a great opportunity to discern accurately how multiple predators hunt together and not just whether doing so provides hunters with a per capita benefit. We incorporate many ideas from collective behaviour and locomotion throughout this review to make testable predictions for future researchers and pay particular attention to the role that computer simulation can play in a feedback loop with empirical data collection. Our review of the literature showed that the breadth of predator:prey size ratios among the taxa that can be considered to hunt as a group is very large (<100 to >102 ). We therefore synthesised the literature with respect to these predator:prey ratios and found that they promoted different hunting mechanisms. Additionally, these different hunting mechanisms are also related to particular stages of the hunt (search, selection, capture) and thus we structure our review in accordance with these two factors (stage of the hunt and predator:prey size ratio). We identify several novel group-hunting mechanisms which are largely untested, particularly under field conditions, and we also highlight a range of potential study organisms that are amenable to experimental testing of these mechanisms in connection with tracking technology. We believe that a combination of new hypotheses, study systems and methodological approaches should help push the field of group-hunting in new directions.
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Affiliation(s)
- Matthew J Hansen
- Fish Biology, Fisheries and Aquaculture, Leibniz Institute of Freshwater Ecology and Inland Fisheries, Müggelseedamm 310, Berlin, 12587, Germany
| | - Paolo Domenici
- IBF-CNR, Consiglio Nazionale delle Ricerche, Area di Ricerca San Cataldo, Via G. Moruzzi No. 1, Pisa, 56124, Italy
- IAS-CNR, Località Sa Mardini, Torregrande, Oristano, 09170, Italy
| | - Palina Bartashevich
- Faculty of Life Science, Humboldt-Universität zu Berlin, Invalidenstrasse 42, Berlin, 10115, Germany
- Cluster of Excellence "Science of Intelligence," Technical University of Berlin, Marchstr. 23, Berlin, 10587, Germany
| | - Alicia Burns
- Faculty of Life Science, Humboldt-Universität zu Berlin, Invalidenstrasse 42, Berlin, 10115, Germany
- Cluster of Excellence "Science of Intelligence," Technical University of Berlin, Marchstr. 23, Berlin, 10587, Germany
| | - Jens Krause
- Fish Biology, Fisheries and Aquaculture, Leibniz Institute of Freshwater Ecology and Inland Fisheries, Müggelseedamm 310, Berlin, 12587, Germany
- Faculty of Life Science, Humboldt-Universität zu Berlin, Invalidenstrasse 42, Berlin, 10115, Germany
- Cluster of Excellence "Science of Intelligence," Technical University of Berlin, Marchstr. 23, Berlin, 10587, Germany
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6
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Gyllingberg L, Birhane A, Sumpter DJT. The lost art of mathematical modelling. Math Biosci 2023:109033. [PMID: 37257641 DOI: 10.1016/j.mbs.2023.109033] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2022] [Revised: 05/24/2023] [Accepted: 05/24/2023] [Indexed: 06/02/2023]
Abstract
We provide a critique of mathematical biology in light of rapid developments in modern machine learning. We argue that out of the three modelling activities - (1) formulating models; (2) analysing models; and (3) fitting or comparing models to data - inherent to mathematical biology, researchers currently focus too much on activity (2) at the cost of (1). This trend, we propose, can be reversed by realising that any given biological phenomenon can be modelled in an infinite number of different ways, through the adoption of an pluralistic approach, where we view a system from multiple, different points of view. We explain this pluralistic approach using fish locomotion as a case study and illustrate some of the pitfalls - universalism, creating models of models, etc. - that hinder mathematical biology. We then ask how we might rediscover a lost art: that of creative mathematical modelling.
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Affiliation(s)
| | - Abeba Birhane
- Mozilla Foundation, 2 Harrison Street, Suite 175, San Francisco, CA 94105, USA
| | - David J T Sumpter
- Department of Information Technology, Uppsala University, Box 337, Uppsala, SE-751 05, Sweden.
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7
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Van Havermaet S, Simoens P, Landgraf T, Khaluf Y. Steering herds away from dangers in dynamic environments. ROYAL SOCIETY OPEN SCIENCE 2023; 10:230015. [PMID: 37234508 PMCID: PMC10206474 DOI: 10.1098/rsos.230015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/05/2023] [Accepted: 04/26/2023] [Indexed: 05/28/2023]
Abstract
Shepherding, the task of guiding a herd of autonomous individuals in a desired direction, is an essential skill to herd animals, enable crowd control and rescue from danger. Equipping robots with the capability of shepherding would allow performing such tasks with increased efficiency and reduced labour costs. So far, only single-robot or centralized multi-robot solutions have been proposed. The former is unable to observe dangers at any place surrounding the herd, and the latter does not generalize to unconstrained environments. Therefore, we propose a decentralized control algorithm for multi-robot shepherding, where the robots maintain a caging pattern around the herd to detect potential nearby dangers. When danger is detected, part of the robot swarm positions itself in order to repel the herd towards a safer region. We study the performance of our algorithm for different collective motion models of the herd. We task the robots to shepherd a herd to safety in two dynamic scenarios: (i) to avoid dangerous patches appearing over time and (ii) to remain inside a safe circular enclosure. Simulations show that the robots are always successful in shepherding when the herd remains cohesive, and enough robots are deployed.
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Affiliation(s)
- Stef Van Havermaet
- Department of Information Technology, University of Ghent—imec, Technologiepark 126, 9052 Ghent, Belgium
| | - Pieter Simoens
- Department of Information Technology, University of Ghent—imec, Technologiepark 126, 9052 Ghent, Belgium
| | - Tim Landgraf
- Department of Mathematics and Computer Science, Freie Universität Berlin, Arnimallee 7, 14195 Berlin, Germany
| | - Yara Khaluf
- Department of Information Technology, University of Ghent—imec, Technologiepark 126, 9052 Ghent, Belgium
- Department of Social Sciences, Wageningen University and Research, Hollandseweg 1, 6706KN Wageningen, The Netherlands
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8
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Arques P, Aznar F, Pujol M, Rizo R. Obtaining emergent behaviors for swarm robotics singling with deep reinforcement learning. Adv Robot 2023. [DOI: 10.1080/01691864.2023.2194952] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/01/2023]
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9
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King AJ, Portugal SJ, Strömbom D, Mann RP, Carrillo JA, Kalise D, de Croon G, Barnett H, Scerri P, Groß R, Chadwick DR, Papadopoulou M. Biologically inspired herding of animal groups by robots. Methods Ecol Evol 2023. [DOI: 10.1111/2041-210x.14049] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/04/2023]
Affiliation(s)
- Andrew J. King
- Department of Biosciences, Faculty of Science and Engineering Swansea University Swansea UK
| | - Steven J. Portugal
- Department of Biological Sciences, School of Life and Environmental Sciences Royal Holloway University of London Egham UK
| | - Daniel Strömbom
- Department of Biology Lafayette College Easton Pennsylvania USA
| | - Richard P. Mann
- Department of Statistics, School of Mathematics University of Leeds Leeds UK
| | | | - Dante Kalise
- Department of Mathematics Imperial College London London UK
| | - Guido de Croon
- Faculty of Aerospace Engineering Delft University of Technology Delft The Netherlands
| | - Heather Barnett
- Central Saint Martins University of the Arts London London UK
| | - Paul Scerri
- Perceptronics Solutions Los Angeles California USA
| | - Roderich Groß
- Department of Automatic Control and Systems Engineering The University of Sheffield Sheffield UK
| | - David R. Chadwick
- Environment Centre Wales, School of Natural Sciences Bangor University Bangor UK
| | - Marina Papadopoulou
- Department of Biosciences, Faculty of Science and Engineering Swansea University Swansea UK
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10
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Fujioka A, Ogura M, Wakamiya N. Shepherding algorithm for heterogeneous flock with model-based discrimination. Adv Robot 2022. [DOI: 10.1080/01691864.2022.2133552] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/01/2022]
Affiliation(s)
- Anna Fujioka
- Department of Information and Computer Science, School of Engineering Science, Osaka University, Osaka, Japan
- Department of Bioinformatic Engineering, Graduate School of Information Science and Technology, Osaka University, Osaka, Japan
| | - Masaki Ogura
- Department of Bioinformatic Engineering, Graduate School of Information Science and Technology, Osaka University, Osaka, Japan
| | - Naoki Wakamiya
- Department of Bioinformatic Engineering, Graduate School of Information Science and Technology, Osaka University, Osaka, Japan
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11
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Zhang S, Pan J. Collecting a Flock With Multiple Sub-Groups by Using Multi-Robot System. IEEE Robot Autom Lett 2022. [DOI: 10.1109/lra.2022.3178152] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Affiliation(s)
- Shuai Zhang
- Department of Computer Science, The University of Hong Kong, Hong Kong
| | - Jia Pan
- Department of Computer Science, The University of Hong Kong, Hong Kong
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12
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Defense against Adversarial Swarms with Parameter Uncertainty. SENSORS 2022; 22:s22134773. [PMID: 35808268 PMCID: PMC9268987 DOI: 10.3390/s22134773] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/11/2022] [Revised: 06/01/2022] [Accepted: 06/03/2022] [Indexed: 12/10/2022]
Abstract
This paper addresses the problem of optimal defense of a high-value unit (HVU) against a large-scale swarm attack. We discuss multiple models for intra-swarm cooperation strategies and provide a framework for combining these cooperative models with HVU tracking and adversarial interaction forces. We show that the problem of defending against a swarm attack can be cast in the framework of uncertain parameter optimal control. We discuss numerical solution methods, then derive a consistency result for the dual problem of this framework, providing a tool for verifying computational results. We also show that the dual conditions can be computed numerically, providing further computational utility. Finally, we apply these numerical results to derive optimal defender strategies against a 100-agent swarm attack.
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13
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Wolf AE, Heinrich MA, Breinyn IB, Zajdel TJ, Cohen DJ. Short-term bioelectric stimulation of collective cell migration in tissues reprograms long-term supracellular dynamics. PNAS NEXUS 2022; 1:pgac002. [PMID: 35360553 PMCID: PMC8962779 DOI: 10.1093/pnasnexus/pgac002] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/03/2021] [Revised: 09/03/2021] [Accepted: 01/07/2022] [Indexed: 01/28/2023]
Abstract
The ability to program collective cell migration can allow us to control critical multicellular processes in development, regenerative medicine, and invasive disease. However, while various technologies exist to make individual cells migrate, translating these tools to control myriad, collectively interacting cells within a single tissue poses many challenges. For instance, do cells within the same tissue interpret a global migration 'command' differently based on where they are in the tissue? Similarly, since no stimulus is permanent, what are the long-term effects of transient commands on collective cell dynamics? We investigate these questions by bioelectrically programming large epithelial tissues to globally migrate 'rightward' via electrotaxis. Tissues clearly developed distinct rear, middle, side, and front responses to a single global migration stimulus. Furthermore, at no point poststimulation did tissues return to their prestimulation behavior, instead equilibrating to a 3rd, new migratory state. These unique dynamics suggested that programmed migration resets tissue mechanical state, which was confirmed by transient chemical disruption of cell-cell junctions, analysis of strain wave propagation patterns, and quantification of cellular crowd dynamics. Overall, this work demonstrates how externally driving the collective migration of a tissue can reprogram baseline cell-cell interactions and collective dynamics, even well beyond the end of the global migratory cue, and emphasizes the importance of considering the supracellular context of tissues and other collectives when attempting to program crowd behaviors.
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Affiliation(s)
- Abraham E Wolf
- Department of Chemical and Biological Engineering, Princeton University, Princeton, NJ 08544, USA
| | | | | | - Tom J Zajdel
- Department of Mechanical and Aerospace Engineering, Princeton University, Princeton, NJ 08544, USA
| | - Daniel J Cohen
- To whom correspondence should be addressed. Address: Attn. , 111 Hoyt Laboratory, Princeton, NJ 08544, USA. E-mail:
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14
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Wang W, Escobedo R, Sanchez S, Sire C, Han Z, Theraulaz G. The impact of individual perceptual and cognitive factors on collective states in a data-driven fish school model. PLoS Comput Biol 2022; 18:e1009437. [PMID: 35235565 PMCID: PMC8932591 DOI: 10.1371/journal.pcbi.1009437] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2021] [Revised: 03/18/2022] [Accepted: 02/08/2022] [Indexed: 11/18/2022] Open
Abstract
In moving animal groups, social interactions play a key role in the ability of individuals to achieve coordinated motion. However, a large number of environmental and cognitive factors are able to modulate the expression of these interactions and the characteristics of the collective movements that result from these interactions. Here, we use a data-driven fish school model to quantitatively investigate the impact of perceptual and cognitive factors on coordination and collective swimming patterns. The model describes the interactions involved in the coordination of burst-and-coast swimming in groups of Hemigrammus rhodostomus. We perform a comprehensive investigation of the respective impacts of two interactions strategies between fish based on the selection of the most or the two most influential neighbors, of the range and intensity of social interactions, of the intensity of individual random behavioral fluctuations, and of the group size, on the ability of groups of fish to coordinate their movements. We find that fish are able to coordinate their movements when they interact with their most or two most influential neighbors, provided that a minimal level of attraction between fish exist to maintain group cohesion. A minimal level of alignment is also required to allow the formation of schooling and milling. However, increasing the strength of social interactions does not necessarily enhance group cohesion and coordination. When attraction and alignment strengths are too high, or when the heading random fluctuations are too large, schooling and milling can no longer be maintained and the school switches to a swarming phase. Increasing the interaction range between fish has a similar impact on collective dynamics as increasing the strengths of attraction and alignment. Finally, we find that coordination and schooling occurs for a wider range of attraction and alignment strength in small group sizes.
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Affiliation(s)
- Weijia Wang
- School of Systems Science, Beijing Normal University, Beijing, China
- Centre de Recherches sur la Cognition Animale, Centre de Biologie Intégrative (CBI), Centre National de la Recherche Scientifique (CNRS) & Université de Toulouse Paul Sabatier, Toulouse, France
- Institut de Recherche en Informatique de Toulouse (IRIT), Université de Toulouse Capitole, Toulouse, France
| | - Ramón Escobedo
- Centre de Recherches sur la Cognition Animale, Centre de Biologie Intégrative (CBI), Centre National de la Recherche Scientifique (CNRS) & Université de Toulouse Paul Sabatier, Toulouse, France
| | - Stéphane Sanchez
- Institut de Recherche en Informatique de Toulouse (IRIT), Université de Toulouse Capitole, Toulouse, France
| | - Clément Sire
- Laboratoire de Physique Théorique, CNRS & Université de Toulouse Paul Sabatier, Toulouse, France
| | - Zhangang Han
- School of Systems Science, Beijing Normal University, Beijing, China
| | - Guy Theraulaz
- Centre de Recherches sur la Cognition Animale, Centre de Biologie Intégrative (CBI), Centre National de la Recherche Scientifique (CNRS) & Université de Toulouse Paul Sabatier, Toulouse, France
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15
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Auletta F, Fiore D, Richardson MJ, di Bernardo M. Herding stochastic autonomous agents via local control rules and online target selection strategies. Auton Robots 2022. [DOI: 10.1007/s10514-021-10033-6] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/02/2022]
Abstract
AbstractWe propose a simple yet effective set of local control rules to make a small group of “herder agents” collect and contain in a desired region a large ensemble of non-cooperative, non-flocking stochastic “target agents” in the plane. We investigate the robustness of the proposed strategies to variations of the number of target agents and the strength of the repulsive force they feel when in proximity of the herders. The effectiveness of the proposed approach is confirmed in both simulations in ROS and experiments on real robots.
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16
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Himo R, Ogura M, Wakamiya N. Iterative shepherding control for agents with heterogeneous responsivity. MATHEMATICAL BIOSCIENCES AND ENGINEERING : MBE 2022; 19:3509-3525. [PMID: 35341262 DOI: 10.3934/mbe.2022162] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
In the context of the theory of multi-agent systems, the shepherding problem refers to designing the dynamics of a herding agent, called a sheepdog, so that a given flock of agents, called sheep, is guided into a goal region. Although several effective methodologies and algorithms have been proposed in the last decade for the shepherding problem under various formulations, little research has been directed to the practically important case in which the flock contains sheep agents unresponsive to the sheepdog agent. To fill in this gap, we propose a sheepdog algorithm for guiding unresponsive sheep in this paper. In the algorithm, the sheepdog iteratively applies an existing shepherding algorithm, the farthest-agent targeting algorithm, while dynamically switching its destination. This procedure achieves the incremental growth of a controllable flock, which finally enables the sheepdog to guide the entire flock into the goal region. Furthermore, we illustrate by numerical simulations that the proposed algorithm can outperform the farthest-agent targeting algorithm.
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Affiliation(s)
- Ryoto Himo
- Graduate School of Information Science and Technology, Osaka University, 1-5 Yamadaoka, Suita, Osaka 565-0871, Japan
| | - Masaki Ogura
- Graduate School of Information Science and Technology, Osaka University, 1-5 Yamadaoka, Suita, Osaka 565-0871, Japan
| | - Naoki Wakamiya
- Graduate School of Information Science and Technology, Osaka University, 1-5 Yamadaoka, Suita, Osaka 565-0871, Japan
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17
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Abstract
This paper proposes a novel robotic animal herding system based on a network of autonomous barking drones. The objective of such a system is to replace traditional herding methods (e.g., dogs) so that a large number (e.g., thousands) of farm animals such as sheep can be quickly collected from a sparse status and then driven to a designated location (e.g., a sheepfold). In this paper, we particularly focus on the motion control of the barking drones. To this end, a computationally efficient sliding mode based control algorithm is developed, which navigates the drones to track the moving boundary of the animals’ footprint and enables the drones to avoid collisions with others. Extensive computer simulations, where the dynamics of the animals follow Reynolds’ rules, show the effectiveness of the proposed approach.
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18
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Herd guidance by multiple sheepdog agents with repulsive force. ARTIFICIAL LIFE AND ROBOTICS 2022. [DOI: 10.1007/s10015-021-00726-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
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19
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Nalepka P, Silva PL, Kallen RW, Shockley K, Chemero A, Saltzman E, Richardson MJ. Task dynamics define the contextual emergence of human corralling behaviors. PLoS One 2021; 16:e0260046. [PMID: 34780559 PMCID: PMC8592491 DOI: 10.1371/journal.pone.0260046] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2021] [Accepted: 10/29/2021] [Indexed: 11/24/2022] Open
Abstract
Social animals have the remarkable ability to organize into collectives to achieve goals unobtainable to individual members. Equally striking is the observation that despite differences in perceptual-motor capabilities, different animals often exhibit qualitatively similar collective states of organization and coordination. Such qualitative similarities can be seen in corralling behaviors involving the encirclement of prey that are observed, for example, during collaborative hunting amongst several apex predator species living in disparate environments. Similar encirclement behaviors are also displayed by human participants in a collaborative problem-solving task involving the herding and containment of evasive artificial agents. Inspired by the functional similarities in this behavior across humans and non-human systems, this paper investigated whether the containment strategies displayed by humans emerge as a function of the task's underlying dynamics, which shape patterns of goal-directed corralling more generally. This hypothesis was tested by comparing the strategies naïve human dyads adopt during the containment of a set of evasive artificial agents across two disparate task contexts. Despite the different movement types (manual manipulation or locomotion) required in the different task contexts, the behaviors that humans display can be predicted as emergent properties of the same underlying task-dynamic model.
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Affiliation(s)
- Patrick Nalepka
- School of Psychological Sciences, Macquarie University, Sydney, NSW, Australia
- Centre for Elite Performance, Expertise and Training, Macquarie University, Sydney, NSW, Australia
| | - Paula L. Silva
- Department of Psychology, Center for Cognition, Action & Perception, University of Cincinnati, Cincinnati, OH, United States of America
| | - Rachel W. Kallen
- School of Psychological Sciences, Macquarie University, Sydney, NSW, Australia
- Centre for Elite Performance, Expertise and Training, Macquarie University, Sydney, NSW, Australia
| | - Kevin Shockley
- Department of Psychology, Center for Cognition, Action & Perception, University of Cincinnati, Cincinnati, OH, United States of America
| | - Anthony Chemero
- Department of Psychology, Center for Cognition, Action & Perception, University of Cincinnati, Cincinnati, OH, United States of America
| | - Elliot Saltzman
- Department of Physical Therapy & Athletic Training, College of Health & Rehabilitation Sciences, Sargent College, Boston University, Boston, MA, United States of America
- Haskins Laboratories, New Haven, CT, United States of America
| | - Michael J. Richardson
- School of Psychological Sciences, Macquarie University, Sydney, NSW, Australia
- Centre for Elite Performance, Expertise and Training, Macquarie University, Sydney, NSW, Australia
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Yaxley KJ, Joiner KF, Abbass H. Drone approach parameters leading to lower stress sheep flocking and movement: sky shepherding. Sci Rep 2021; 11:7803. [PMID: 33833361 PMCID: PMC8032684 DOI: 10.1038/s41598-021-87453-y] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2020] [Accepted: 03/23/2021] [Indexed: 11/09/2022] Open
Abstract
Consumer groups are pressuring modern farmers to be more efficient with a focus on better animal welfare. Herding risks farmer lives, involves stress from farm dogs, and if not performed often and intelligently, risks neglect. We examined the behavioural and physiological response of twelve Dorper sheep (Ovies aries) to a drone to adapt mathematical models of shepherding to the new dimension. The model aims to make it feasible for artificial intelligence to improve the autonomy of farmers and pilots in shepherding from the sky. Sheep acclimatised quickly and positively to the drone initiating drive of a flock, regardless of drone speed. Our results demonstrate that stimulating sheep auditory awareness during herding from the sky leads to varying sheep responses. When controlled, these auditory cues can maintain safer distances between the drone and the sheep, offering great potential for the agriculture industry. We outline our ongoing research plans to achieve more autonomous sky shepherding that is compassionate to animal welfare and trusted by farmers and the consuming public.
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Affiliation(s)
- Kate J Yaxley
- School of Engineering and IT, University of New South Wales (UNSW), Canberra, Australia
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Zhi J, Lien JM. Learning to Herd Agents Amongst Obstacles: Training Robust Shepherding Behaviors Using Deep Reinforcement Learning. IEEE Robot Autom Lett 2021. [DOI: 10.1109/lra.2021.3068955] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
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22
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Song H, Varava A, Kravchenko O, Kragic D, Wang MY, Pokorny FT, Hang K. Herding by caging: a formation-based motion planning framework for guiding mobile agents. Auton Robots 2021. [DOI: 10.1007/s10514-021-09975-8] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
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23
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Hu J, Turgut AE, Krajnik T, Lennox B, Arvin F. Occlusion-Based Coordination Protocol Design for Autonomous Robotic Shepherding Tasks. IEEE Trans Cogn Dev Syst 2021. [DOI: 10.1109/tcds.2020.3018549] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
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Patil G, Nalepka P, Kallen RW, Richardson MJ. Hopf Bifurcations in Complex Multiagent Activity: The Signature of Discrete to Rhythmic Behavioral Transitions. Brain Sci 2020; 10:brainsci10080536. [PMID: 32784867 PMCID: PMC7465533 DOI: 10.3390/brainsci10080536] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2020] [Revised: 07/31/2020] [Accepted: 08/06/2020] [Indexed: 11/16/2022] Open
Abstract
Most human actions are composed of two fundamental movement types, discrete and rhythmic movements. These movement types, or primitives, are analogous to the two elemental behaviors of nonlinear dynamical systems, namely, fixed-point and limit cycle behavior, respectively. Furthermore, there is now a growing body of research demonstrating how various human actions and behaviors can be effectively modeled and understood using a small set of low-dimensional, fixed-point and limit cycle dynamical systems (differential equations). Here, we provide an overview of these dynamical motorprimitives and detail recent research demonstrating how these dynamical primitives can be used to model the task dynamics of complex multiagent behavior. More specifically, we review how a task-dynamic model of multiagent shepherding behavior, composed of rudimentary fixed-point and limit cycle dynamical primitives, can not only effectively model the behavior of cooperating human co-actors, but also reveals how the discovery and intentional use of optimal behavioral coordination during task learning is marked by a spontaneous, self-organized transition between fixed-point and limit cycle dynamics (i.e., via a Hopf bifurcation).
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Long NK, Sammut K, Sgarioto D, Garratt M, Abbass HA. A Comprehensive Review of Shepherding as a Bio-Inspired Swarm-Robotics Guidance Approach. IEEE TRANSACTIONS ON EMERGING TOPICS IN COMPUTATIONAL INTELLIGENCE 2020. [DOI: 10.1109/tetci.2020.2992778] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
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26
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Garcia E, Casbeer DW, Pachter M. Optimal Strategies for a Class of Multi-Player Reach-Avoid Differential Games in 3D Space. IEEE Robot Autom Lett 2020. [DOI: 10.1109/lra.2020.2994023] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
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Jiang C, Ni Z, Guo Y, He H. Pedestrian Flow Optimization to Reduce the Risk of Crowd Disasters Through Human–Robot Interaction. IEEE TRANSACTIONS ON EMERGING TOPICS IN COMPUTATIONAL INTELLIGENCE 2020. [DOI: 10.1109/tetci.2019.2930249] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
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Early J, Aalders J, Arnott E, Wade C, McGreevy P. Sequential Analysis of Livestock Herding Dog and Sheep Interactions. Animals (Basel) 2020; 10:ani10020352. [PMID: 32098372 PMCID: PMC7070376 DOI: 10.3390/ani10020352] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2020] [Revised: 02/19/2020] [Accepted: 02/20/2020] [Indexed: 11/24/2022] Open
Abstract
Simple Summary Although livestock herding dogs have contributed significantly to Australian agriculture, there are virtually no studies examining the interactions between dog and livestock during herding. One statistical approach that may assist our understanding of such interactions during herding is lag sequential analysis that reveals links between one event and the next. Using high-definition video recordings of herding in a yard-based competition trial and software to code the main dog and sheep behaviours, we identified several significant behavioural interactions. These included the dog ceasing all movement followed by the sheep also ceasing movement; the dog chasing the sheep and a group of sheep escaping the main flock; a single sheep escaping the flock and the dog chasing; sheep initiating movement followed by the dog following; foot-stamping followed by the dog ceasing all movement; and, foot-stamping by the sheep and the dog lip-licking in response. Further statistical analysis found no significant sex differences in the herding styles of the dogs included in the study. Of benefit to livestock herding dog handlers and breeders was the identification of trial score as a predictor of efficient performance. Abstract Livestock herding dogs are crucial contributors to Australian agriculture. However, there is a dearth of empirical studies of the behavioural interactions between dog and livestock during herding. A statistical approach that may reveal cause and effect in such interactions is lag sequential analysis. Using 48 video recordings of livestock herding dogs and sheep in a yard trial competition, event-based (time between behaviours is irrelevant) and time-based (time between behaviours is defined) lag sequential analyses identified several significant behavioural interactions (adjusted residuals greater than 2.58; the maximum likelihood-ratio chi-squared statistic for all eight contingency tables identified all sequences as highly significant (p < 0.001)). These sequences were: The dog ceasing all movement followed by the sheep also ceasing movement; the dog chasing the sheep and a group of sheep escaping the main flock; a single sheep escaping the flock and the dog chasing; sheep initiating movement followed by the dog following; foot-stamping followed by the dog ceasing all movement; and, foot-stamping by the sheep and the dog lip-licking in response. Log linear regression identified significant relationships among undesirable behaviours in sheep and both observed trial duration (p = 0.001) and trial score (p = 0.009). No differences in the herding styles of dogs were identified between sex of dog and frequency of sheep escape behaviours (p = 0.355) nor the sex of dog and competition level (p = 0.116). The identification of trial score as a predictor of efficient performance confirms the benefits of incorporating extant objective measures to assess livestock herding dogs.
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Affiliation(s)
- Jonathan Early
- Sydney School of Veterinary Science, Faculty of Science, University of Sydney, Sydney, NSW 2006, Australia; (J.A.); (E.A.); (P.M.)
- Correspondence:
| | - Jessica Aalders
- Sydney School of Veterinary Science, Faculty of Science, University of Sydney, Sydney, NSW 2006, Australia; (J.A.); (E.A.); (P.M.)
| | - Elizabeth Arnott
- Sydney School of Veterinary Science, Faculty of Science, University of Sydney, Sydney, NSW 2006, Australia; (J.A.); (E.A.); (P.M.)
| | - Claire Wade
- School of Life and Environmental Sciences, Faculty of Science, University of Sydney, Sydney, NSW 2006, Australia;
| | - Paul McGreevy
- Sydney School of Veterinary Science, Faculty of Science, University of Sydney, Sydney, NSW 2006, Australia; (J.A.); (E.A.); (P.M.)
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Sueoka Y, Sato Y, Ishitani M, Osuka K. Analysis of push-forward model for swarm-like collective motions. ARTIFICIAL LIFE AND ROBOTICS 2019. [DOI: 10.1007/s10015-019-00548-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/26/2022]
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Ringhofer M, Go CK, Inoue S, S. Mendonça R, Hirata S, Kubo T, Ikeda K, Yamamoto S. Herding mechanisms to maintain the cohesion of a harem group: two interaction phases during herding. J ETHOL 2019. [DOI: 10.1007/s10164-019-00622-5] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
Abstract
AbstractIn animal groups, individual interactions achieve coordinated movements to maintain cohesion. In horse harem groups, herding is a behavior in which males chase females from behind; it is considered to assist with group cohesiveness. However, the mechanisms by which the individuals move to maintain group cohesion are unknown. We applied novel non-invasive methods of drone filming and video tracking to observe horse movements in the field with high temporal and spatial resolution. We tracked all group members and drew trajectories. We analyzed the movements of females and found two phases of interactions based on their timing of movement initiation. The females that moved first were those nearest to the herding male, while the movement initiation of the later females was determined by the distance from the nearest moving female, not by the distance from the herding male. These interactions are unique among animal group movements and might represent a herding mechanism responsible for maintaining group cohesion. This might be due to long-term stable relationships within a harem group and strong social bonds between females. This study showed that the combination of drone filming and video tracking is a useful method for analyzing the movements of animals simultaneously in high resolution.
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Surendran A, Plank MJ, Simpson MJ. Spatial structure arising from chase-escape interactions with crowding. Sci Rep 2019; 9:14988. [PMID: 31628421 PMCID: PMC6800429 DOI: 10.1038/s41598-019-51565-3] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2019] [Accepted: 10/03/2019] [Indexed: 12/17/2022] Open
Abstract
Movement of individuals, mediated by localised interactions, plays a key role in numerous processes including cell biology and ecology. In this work, we investigate an individual-based model accounting for various intraspecies and interspecies interactions in a community consisting of two distinct species. In this framework we consider one species to be chasers and the other species to be escapees, and we focus on chase-escape dynamics where the chasers are biased to move towards the escapees, and the escapees are biased to move away from the chasers. This framework allows us to explore how individual-level directional interactions scale up to influence spatial structure at the macroscale. To focus exclusively on the role of motility and directional bias in determining spatial structure, we consider conservative communities where the number of individuals in each species remains constant. To provide additional information about the individual-based model, we also present a mathematically tractable deterministic approximation based on describing the evolution of the spatial moments. We explore how different features of interactions including interaction strength, spatial extent of interaction, and relative density of species influence the formation of the macroscale spatial patterns.
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Affiliation(s)
- Anudeep Surendran
- School of Mathematical Sciences, Queensland University of Technology, Brisbane, Australia
| | - Michael J Plank
- School of Mathematics and Statistics, University of Canterbury, Christchurch, New Zealand.,Te Pūnaha Matatini, A New Zealand Centre of Research Excellence, Auckland, New Zealand
| | - Matthew J Simpson
- School of Mathematical Sciences, Queensland University of Technology, Brisbane, Australia.
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Papaspyros V, Bonnet F, Collignon B, Mondada F. Bidirectional interactions facilitate the integration of a robot into a shoal of zebrafish Danio rerio. PLoS One 2019; 14:e0220559. [PMID: 31430290 PMCID: PMC6701756 DOI: 10.1371/journal.pone.0220559] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2019] [Accepted: 07/18/2019] [Indexed: 11/21/2022] Open
Abstract
Many studies on collective animal behavior seek to identify the individual rules that underlie collective patterns. However, it was not until the recent advancements of micro-electronic and embedded systems that scientists were able to create mixed groups of sensor-rich robots and animals and study collective interactions from the within a bio-hybrid group. In recent work, scientists showed that a robot-controlled lure is capable of influencing the collective decisions of zebrafish Danio rerio shoals moving in a ring and a two-room setup. Here, we study a closely related topic, that is, the collective behavior patterns that emerge when different behavioral models are reproduced through the use of a robotic lure. We design a behavioral model that alternates between obeying and disobeying the collective motion decisions in order to become socially accepted by the shoal members. Subsequently, we compare it against two extreme cases: a reactive and an imposing decision model. For this, we use spatial, directional and information theoretic metrics to measure the degree of integration of the robotic agent. We show that our model leads to similar information flow as in freely roaming shoals of zebrafish and exhibits leadership skills more often than the open-loop models. Thus, in order for the robot to achieve higher degrees of integration in the zebrafish shoal, it must, like any other shoal member, be bidirectionally involved in the decision making process. These findings provide insight on the ability to form mixed societies of animals and robots and yield promising results on the degree to which a robot can influence the collective decision making.
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Affiliation(s)
- Vaios Papaspyros
- Biorobotics Laboratory, Institute of Bioengineering, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Frank Bonnet
- Biorobotics Laboratory, Institute of Bioengineering, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Bertrand Collignon
- Biorobotics Laboratory, Institute of Bioengineering, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
- Unit of Social Ecology (USE), Université libre de Bruxelles (ULB), Bruxelles, Belgium
| | - Francesco Mondada
- Biorobotics Laboratory, Institute of Bioengineering, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
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34
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Licitra RA, Bell ZI, Dixon WE. Single-Agent Indirect Herding of Multiple Targets With Uncertain Dynamics. IEEE T ROBOT 2019. [DOI: 10.1109/tro.2019.2911799] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
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35
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Fürtbauer I, Solman C, Fry A. Sheep wool cortisol as a retrospective measure of long-term HPA axis activity and its links to body mass. Domest Anim Endocrinol 2019; 68:39-46. [PMID: 30797176 DOI: 10.1016/j.domaniend.2018.12.009] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/26/2018] [Revised: 11/29/2018] [Accepted: 12/24/2018] [Indexed: 01/21/2023]
Abstract
Hair cortisol analysis has been suggested as a powerful retrospective measure of long-term hypothalamic-pituitary-adrenal (HPA) axis activity in numerous mammal species. In contrast, research evaluating the use of wool as a marker of long-term HPA axis activity is still scarce, and wool differs from hair in a number of ways. Here, we assess repeatability and differences in wool cortisol concentrations (WCCs) across (i) the wool shaft, (ii) two body locations, and (iii) time, in 33 barren Welsh mountain ewes (Ovis aries). We also (iv) investigated effects of grazing-related changes in body mass on WCCs and (v) assessed effects of the washing procedure during sample preparation on WCCs. Cortisol concentrations were repeatable but differed significantly across the wool shaft indicating that, provided wool growth rate is known, a single sample per individual could be used as a retrospective cortisol "timeline." WCCs were significantly higher in shoulder than in back samples, and no correlation between these two body locations was found, highlighting the importance of sampling from the same body location for repeated measures. An increase in body mass during grazing corresponded with a decrease in WCCs, which was significantly negatively correlated with body mass (and positively with age), suggesting that WCCs can be used as a marker of body condition and nutritional status in sheep. Interestingly, we found higher WCCs in washed compared with unwashed samples and discuss implications of this finding for future work. Overall, our study revealed significant within- and between-individual differences in WCCs and highlights a number of advantages but also methodological considerations of using WCCs as a retrospective measure of long-term HPA axis activity in sheep.
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Affiliation(s)
- I Fürtbauer
- Department of Biosciences, Swansea University, Singleton Park, SA2 8PP Swansea, UK.
| | - C Solman
- Department of Biosciences, Swansea University, Singleton Park, SA2 8PP Swansea, UK
| | - A Fry
- Department of Biosciences, Swansea University, Singleton Park, SA2 8PP Swansea, UK
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36
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Strömbom D, Hassan T, Hunter Greis W, Antia A. Asynchrony induces polarization in attraction-based models of collective motion. ROYAL SOCIETY OPEN SCIENCE 2019; 6:190381. [PMID: 31183154 PMCID: PMC6502356 DOI: 10.1098/rsos.190381] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/04/2019] [Accepted: 03/15/2019] [Indexed: 05/14/2023]
Abstract
Animal groups frequently move in a highly organized manner, as represented by flocks of birds and schools of fish. Despite being an everyday occurrence, we do not fully understand how this works. In particular, what social interactions between animals give rise to the flock structures we observe? This question is often investigated using self-propelled particle models where particles represent the individual animals. These models differ in the social interactions used, individual particle properties, and various technical assumptions. One particular technical assumption relates to whether all particles update their headings and positions at exactly the same time (synchronous update) or not (asynchronous update). Here, we investigate the causal effects of this assumption in an attraction-only model and find that it has a dramatic impact. Polarized groups do not form when synchronous update is used, but are produced with asynchronous update, and this phenomenon is robust with respect to variation in particle displacements and inclusion of noise. Given that many important models have been implemented with synchronous update only, we speculate that our understanding of the social interactions on which they are based may be incomplete. Perhaps previously unobserved phenomena will emerge if other potentially more realistic update schemes are used.
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Affiliation(s)
- Daniel Strömbom
- Department of Mathematics, Uppsala University, Uppsala 75601, Sweden
- Department of Biology, Lafayette College, Easton 18042, PA, USA
- Department of Biosciences, College of Science, Swansea University, Swansea SA2 6PP, UK
- Author for correspondence: Daniel Strömbom e-mail:
| | - Tasnia Hassan
- Department of Biology, Lafayette College, Easton 18042, PA, USA
| | - W. Hunter Greis
- Department of Biology, Lafayette College, Easton 18042, PA, USA
| | - Alice Antia
- Department of Mathematics and Statistics, Carleton College, Northfield 55057, MN, USA
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Nalepka P, Lamb M, Kallen RW, Shockley K, Chemero A, Saltzman E, Richardson MJ. Human social motor solutions for human-machine interaction in dynamical task contexts. Proc Natl Acad Sci U S A 2019; 116:1437-1446. [PMID: 30617064 PMCID: PMC6347696 DOI: 10.1073/pnas.1813164116] [Citation(s) in RCA: 27] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
Multiagent activity is commonplace in everyday life and can improve the behavioral efficiency of task performance and learning. Thus, augmenting social contexts with the use of interactive virtual and robotic agents is of great interest across health, sport, and industry domains. However, the effectiveness of human-machine interaction (HMI) to effectively train humans for future social encounters depends on the ability of artificial agents to respond to human coactors in a natural, human-like manner. One way to achieve effective HMI is by developing dynamical models utilizing dynamical motor primitives (DMPs) of human multiagent coordination that not only capture the behavioral dynamics of successful human performance but also, provide a tractable control architecture for computerized agents. Previous research has demonstrated how DMPs can successfully capture human-like dynamics of simple nonsocial, single-actor movements. However, it is unclear whether DMPs can be used to model more complex multiagent task scenarios. This study tested this human-centered approach to HMI using a complex dyadic shepherding task, in which pairs of coacting agents had to work together to corral and contain small herds of virtual sheep. Human-human and human-artificial agent dyads were tested across two different task contexts. The results revealed (i) that the performance of human-human dyads was equivalent to those composed of a human and the artificial agent and (ii) that, using a "Turing-like" methodology, most participants in the HMI condition were unaware that they were working alongside an artificial agent, further validating the isomorphism of human and artificial agent behavior.
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Affiliation(s)
- Patrick Nalepka
- Centre for Elite Performance, Expertise and Training, Macquarie University, Sydney, NSW 2109, Australia;
- Department of Psychology, Macquarie University, Sydney, NSW 2109, Australia
| | - Maurice Lamb
- Center for Cognition, Action & Perception, Department of Psychology, University of Cincinnati, Cincinnati, OH 45220
| | - Rachel W Kallen
- Centre for Elite Performance, Expertise and Training, Macquarie University, Sydney, NSW 2109, Australia
- Department of Psychology, Macquarie University, Sydney, NSW 2109, Australia
| | - Kevin Shockley
- Center for Cognition, Action & Perception, Department of Psychology, University of Cincinnati, Cincinnati, OH 45220
| | - Anthony Chemero
- Center for Cognition, Action & Perception, Department of Psychology, University of Cincinnati, Cincinnati, OH 45220
| | - Elliot Saltzman
- Department of Physical Therapy & Athletic Training, Sargent College of Health & Rehabilitation Sciences, Boston University, Boston, MA 02215
- Haskins Laboratories, New Haven, CT 06511
| | - Michael J Richardson
- Centre for Elite Performance, Expertise and Training, Macquarie University, Sydney, NSW 2109, Australia;
- Department of Psychology, Macquarie University, Sydney, NSW 2109, Australia
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38
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Filippov AE, Guillermo-Ferreira R, Gorb SN. "Cylindrical worlds" in biology: Does the aggregation strategy give a selective advantage? Biosystems 2018; 175:39-46. [PMID: 30389555 DOI: 10.1016/j.biosystems.2018.10.016] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2018] [Revised: 10/25/2018] [Accepted: 10/26/2018] [Indexed: 10/28/2022]
Abstract
Tree trunks and other cylindrical objects, where aggregated insects live, represent a very specific world for predator-prey interactions, which must differ from the situation on a 2D plane. In the present paper, in order to gain a better understanding of the specificity of predator-prey interaction in a cylindrical space, we applied a theoretical approach. Here we introduce a numerical model that allows us to test the effect of different interaction properties between predator and aggregated prey on the plane (2D) and on a cylinder (3D), taking into consideration different abilities of predators to visually detect the prey in these two types of space. The main aim was to test these interactions in an environment, which more realistically reproduces the conditions where aggregated insects usually live. We showed that the aggregation in conjunction with a specific environment may bring additional advantages for the prey. When one prey subgroup aggregates on the other side of the tree trunk and becomes invisible behind the horizon of events for the predator, the subgroup will survive with an extremely high probability. After all, the predator moving along one side of the tree will finally loose the major group completely.
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Affiliation(s)
- A E Filippov
- Functional Morphology and Biomechanics, Zoological Institute, Kiel University, Am Botanischen Garten, 1-9, 24118, Kiel, Germany; Donetsk Institute for Physics and Engineering, National Academy of Sciences of Ukraine, Donetsk, Ukraine.
| | - R Guillermo-Ferreira
- Department of Hydrobiology, Federal University of São Carlos - UFSCar, São Carlos, São Paulo, Brazil
| | - S N Gorb
- Functional Morphology and Biomechanics, Zoological Institute, Kiel University, Am Botanischen Garten, 1-9, 24118, Kiel, Germany
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Affiliation(s)
- Y. Tsunoda
- Department of Mechanical Engineering, Graduate School of Engineering, Osaka University, Osaka, Japan
| | - Y. Sueoka
- Department of Mechanical Engineering, Graduate School of Engineering, Osaka University, Osaka, Japan
| | - Y. Sato
- Department of Mechanical Engineering, Graduate School of Engineering, Osaka University, Osaka, Japan
| | - K. Osuka
- Department of Mechanical Engineering, Graduate School of Engineering, Osaka University, Osaka, Japan
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Strömbom D, Dussutour A. Self-organized traffic via priority rules in leaf-cutting ants. PLoS Comput Biol 2018; 14:e1006523. [PMID: 30307942 PMCID: PMC6198993 DOI: 10.1371/journal.pcbi.1006523] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2018] [Revised: 10/23/2018] [Accepted: 09/21/2018] [Indexed: 11/18/2022] Open
Abstract
Ants, termites and humans often form well-organized and highly efficient trails between different locations. Yet the microscopic traffic rules responsible for this organization and efficiency are not fully understood. In previous experimental studies with leaf-cutting ants (Atta colombica), a set of local priority rules were isolated and it was proposed that these rules govern the temporal and spatial organization of the traffic on the trails. Here we introduce a model based on these priority rules to investigate whether they are sufficient to produce traffic similar to that observed in the experiments on both a narrow and a wider trail. We establish that the model is able to reproduce key characteristics of the traffic on the trails. In particular, we show that the proposed priority rules induce de-synchronization into clusters of inbound and outbound ants on a narrow trail, and that priority-type dependent segregated traffic emerges on a wider trail. Due to the generic nature of the proposed priority rules we speculate that they may be used to model traffic organization in a variety of other ant species.
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Affiliation(s)
- Daniel Strömbom
- Department of Mathematics, Uppsala University, Uppsala, Sweden
- Department of Biosciences, Swansea University, Swansea, United Kingdom
- Department of Biology, Lafayette College, Easton, Pennsylvania, United States of America
| | - Audrey Dussutour
- Centre de Recherches sur la Cognition Animale (CRCA), Centre de Biologie Intégrative (CBI), Université de Toulouse, CNRS, UPS, Toulouse, France
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Paranjape AA, Chung SJ, Kim K, Shim DH. Robotic Herding of a Flock of Birds Using an Unmanned Aerial Vehicle. IEEE T ROBOT 2018. [DOI: 10.1109/tro.2018.2853610] [Citation(s) in RCA: 67] [Impact Index Per Article: 11.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
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Strömbom D, King AJ. Robot Collection and Transport of Objects: A Biomimetic Process. Front Robot AI 2018; 5:48. [PMID: 33500933 PMCID: PMC7805832 DOI: 10.3389/frobt.2018.00048] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2017] [Accepted: 04/11/2018] [Indexed: 11/22/2022] Open
Abstract
Animals as diverse as ants and humans are faced with the tasks of collecting, transporting or herding objects. Sheepdogs do this daily when they collect, herd, and maneuver flocks of sheep. Here, we adapt a shepherding algorithm inspired by sheepdogs to collect and transport objects using a robot. Our approach produces an effective robot collection process that autonomously adapts to changing environmental conditions and is robust to noise from various sources. We suggest that this biomimetic process could be implemented into suitable robots to perform collection and transport tasks that might include – for example – cleaning up objects in the environment, keeping animals away from sensitive areas or collecting and herding animals to a specific location. Furthermore, the feedback controlled interactions between the robot and objects which we study can be used to interrogate and understand the local and global interactions of real animal groups, thus offering a novel methodology of value to researchers studying collective animal behavior.
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Affiliation(s)
- Daniel Strömbom
- Department of Mathematics, Uppsala University, Uppsala, Sweden.,Department of Biosciences, Swansea University, Swansea, United Kingdom
| | - Andrew J King
- Department of Biosciences, Swansea University, Swansea, United Kingdom
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Cazenille L, Collignon B, Chemtob Y, Bonnet F, Gribovskiy A, Mondada F, Bredeche N, Halloy J. How mimetic should a robotic fish be to socially integrate into zebrafish groups? BIOINSPIRATION & BIOMIMETICS 2018; 13:025001. [PMID: 28952466 DOI: 10.1088/1748-3190/aa8f6a] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/07/2023]
Abstract
Biomimetic robots are promising tools in animal behavioural studies. If they are socially integrated in a group of animals, they can produce calibrated social stimuli to test the animal responses. However, the design of such social robots is challenging as it involves both a luring capability including appropriate robot behaviours, and the acceptation of the robots by the animals as social companions. Here, we investigate the integration of a biomimetic robot driven by biomimetic behavioural models into a group of zebrafish (Danio rerio). The robot behaviours are based on a stochastic model linking zebrafish visual perception to individual behaviour and calibrated experimentally to correspond to the behaviour of zebrafish. We show that our robot can be integrated into a group of zebrafish, mimic their behaviour and exhibit similar collective dynamics compared to fish-only groups. This study shows that an autonomous biomimetic robot was enhanced by a biomimetic behavioural model so that it can socially integrate into groups of fish.
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Affiliation(s)
- Leo Cazenille
- Univ Paris Diderot, Sorbonne Paris Cité, LIED, UMR 8236, 75013, Paris, France. Sorbonne Universités, UPMC Univ Paris 06, CNRS, ISIR, F-75005 Paris, France
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Rossi F, Bandyopadhyay S, Wolf M, Pavone M. Review of Multi-Agent Algorithms for Collective Behavior: a Structural Taxonomy. ACTA ACUST UNITED AC 2018. [DOI: 10.1016/j.ifacol.2018.07.097] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/28/2022]
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Abstract
The limitations of using small-brained rodents to model diseases that affect large-brain humans are becoming increasingly obvious as novel therapies emerge. Huntington's disease (HD) is one such disease. In recent years, the desirability of a large-brained, long-lived animal model of HD for preclinical testing has changed into a necessity. Treatment involving gene therapy in particular presents delivery challenges that are currently unsolved. Models using long-lived, large-brained animals would be useful, not only for refining methods of delivery (particularly for gene and other therapies that do not involve small molecules) but also for measuring long-term "off-target" effects, and assessing the efficacy of therapies. With their large brains and convoluted cortices, sheep are emerging as feasible experimental subjects that can be used to bridge the gap between rodents and humans in preclinical drug development. Sheep are readily available, economical to use, and easy to care for in naturalistic settings. With brains of a similar size to a large rhesus macaque, they have much to offer. The only thing that was missing until recently was the means of testing their neurological function and behavior using approaches and methods that are relevant to HD. In this chapter, I will outline the present and future possibilities of using sheep and testing as large animal models of HD.
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Affiliation(s)
- A J Morton
- Department of Physiology, Development and Neuroscience, University of Cambridge, Cambridge, UK.
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Lee W, Kim D. Autonomous Shepherding Behaviors of Multiple Target Steering Robots. SENSORS 2017; 17:s17122729. [PMID: 29186836 PMCID: PMC5751650 DOI: 10.3390/s17122729] [Citation(s) in RCA: 37] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/14/2017] [Revised: 11/20/2017] [Accepted: 11/21/2017] [Indexed: 11/16/2022]
Abstract
This paper presents a distributed coordination methodology for multi-robot systems, based on nearest-neighbor interactions. Among many interesting tasks that may be performed using swarm robots, we propose a biologically-inspired control law for a shepherding task, whereby a group of external agents drives another group of agents to a desired location. First, we generated sheep-like robots that act like a flock. We assume that each agent is capable of measuring the relative location and velocity to each of its neighbors within a limited sensing area. Then, we designed a control strategy for shepherd-like robots that have information regarding where to go and a steering ability to control the flock, according to the robots’ position relative to the flock. We define several independent behavior rules; each agent calculates to what extent it will move by summarizing each rule. The flocking sheep agents detect the steering agents and try to avoid them; this tendency leads to movement of the flock. Each steering agent only needs to focus on guiding the nearest flocking agent to the desired location. Without centralized coordination, multiple steering agents produce an arc formation to control the flock effectively. In addition, we propose a new rule for collecting behavior, whereby a scattered flock or multiple flocks are consolidated. From simulation results with multiple robots, we show that each robot performs actions for the shepherding behavior, and only a few steering agents are needed to control the whole flock. The results are displayed in maps that trace the paths of the flock and steering robots. Performance is evaluated via time cost and path accuracy to demonstrate the effectiveness of this approach.
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Affiliation(s)
- Wonki Lee
- Biological Cybernetics Lab, School of Electrical and Electronic Engineering, Yonsei University, 50 Yonsei-ro, Seodaemun-gu, Seoul 120-749, Korea.
| | - DaeEun Kim
- Biological Cybernetics Lab, School of Electrical and Electronic Engineering, Yonsei University, 50 Yonsei-ro, Seodaemun-gu, Seoul 120-749, Korea.
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Kershenbaum A, Blumstein DT. Introduction to the special column: communication, cooperation, and cognition in predators. Curr Zool 2017; 63:295-299. [PMID: 29491988 PMCID: PMC5804181 DOI: 10.1093/cz/zox027] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Affiliation(s)
- Arik Kershenbaum
- Department of Zoology, University of Cambridge, Cambridge CB2 3EJ, UK
| | - Daniel T. Blumstein
- Department of Ecology and Evolutionary Biology, University of California, Los Angeles, CA 90095-1606, USA
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