1
|
Gordleeva SY, Kastalskiy IA, Tsybina YA, Ermolaeva AV, Hramov AE, Kazantsev VB. Control of movement of underwater swimmers: Animals, simulated animates and swimming robots. Phys Life Rev 2023; 47:211-244. [PMID: 38072505 DOI: 10.1016/j.plrev.2023.10.037] [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: 10/27/2023] [Accepted: 10/29/2023] [Indexed: 12/18/2023]
Abstract
The control of movement in living organisms represents a fundamental task that the brain has evolved to solve. One crucial aspect is how the nervous system organizes the transformation of sensory information into motor commands. These commands lead to muscle activation and subsequent animal movement, which can exhibit complex patterns. One example of such movement is locomotion, which involves the translation of the entire body through space. Central Pattern Generators (CPGs) are neuronal circuits that provide control signals for these movements. Compared to the intricate circuits found in the brain, CPGs can be simplified into networks of neurons that generate rhythmic activation, coordinating muscle movements. Since the 1990s, researchers have developed numerous models of locomotive circuits to simulate different types of animal movement, including walking, flying, and swimming. Initially, the primary goal of these studies was to construct biomimetic robots. However, it became apparent that simplified CPGs alone were not sufficient to replicate the diverse range of adaptive locomotive movements observed in living organisms. Factors such as sensory modulation, higher-level control, and cognitive components related to learning and memory needed to be considered. This necessitated the use of more complex, high-dimensional circuits, as well as novel materials and hardware, in both modeling and robotics. With advancements in high-power computing, artificial intelligence, big data processing, smart materials, and electronics, the possibility of designing a new generation of true bio-mimetic robots has emerged. These robots have the capability to imitate not only simple locomotion but also exhibit adaptive motor behavior and decision-making. This motivation serves as the foundation for the current review, which aims to analyze existing concepts and models of movement control systems. As an illustrative example, we focus on underwater movement and explore the fundamental biological concepts, as well as the mathematical and physical models that underlie locomotion and its various modulations.
Collapse
Affiliation(s)
- S Yu Gordleeva
- National Research Lobachevsky State University of Nizhny Novgorod, 23 Gagarin Ave., Nizhny Novgorod, 603022, Russia; Immanuel Kant Baltic Federal University, 14 A. Nevskogo St., Kaliningrad, 236016, Russia; Moscow Institute of Physics and Technology, 9 Institutskiy Ln., Dolgoprudny, 141701, Moscow Region, Russia
| | - I A Kastalskiy
- National Research Lobachevsky State University of Nizhny Novgorod, 23 Gagarin Ave., Nizhny Novgorod, 603022, Russia; Moscow Institute of Physics and Technology, 9 Institutskiy Ln., Dolgoprudny, 141701, Moscow Region, Russia.
| | - Yu A Tsybina
- National Research Lobachevsky State University of Nizhny Novgorod, 23 Gagarin Ave., Nizhny Novgorod, 603022, Russia; I.M. Sechenov First Moscow State Medical University (Sechenov University), 2 Bol'shaya Pirogovskaya St., Moscow, 119435, Russia
| | - A V Ermolaeva
- National Research Lobachevsky State University of Nizhny Novgorod, 23 Gagarin Ave., Nizhny Novgorod, 603022, Russia; I.M. Sechenov First Moscow State Medical University (Sechenov University), 2 Bol'shaya Pirogovskaya St., Moscow, 119435, Russia
| | - A E Hramov
- Immanuel Kant Baltic Federal University, 14 A. Nevskogo St., Kaliningrad, 236016, Russia; Saint Petersburg State University, 7-9 Universitetskaya Emb., Saint Petersburg, 199034, Russia
| | - V B Kazantsev
- National Research Lobachevsky State University of Nizhny Novgorod, 23 Gagarin Ave., Nizhny Novgorod, 603022, Russia; Immanuel Kant Baltic Federal University, 14 A. Nevskogo St., Kaliningrad, 236016, Russia; Moscow Institute of Physics and Technology, 9 Institutskiy Ln., Dolgoprudny, 141701, Moscow Region, Russia
| |
Collapse
|
2
|
Thandiackal R, Melo K, Paez L, Herault J, Kano T, Akiyama K, Boyer F, Ryczko D, Ishiguro A, Ijspeert AJ. Emergence of robust self-organized undulatory swimming based on local hydrodynamic force sensing. Sci Robot 2021; 6:6/57/eabf6354. [PMID: 34380756 DOI: 10.1126/scirobotics.abf6354] [Citation(s) in RCA: 36] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2020] [Accepted: 07/21/2021] [Indexed: 01/23/2023]
Abstract
Undulatory swimming represents an ideal behavior to investigate locomotion control and the role of the underlying central and peripheral components in the spinal cord. Many vertebrate swimmers have central pattern generators and local pressure-sensitive receptors that provide information about the surrounding fluid. However, it remains difficult to study experimentally how these sensors influence motor commands in these animals. Here, using a specifically designed robot that captures the essential components of the animal neuromechanical system and using simulations, we tested the hypothesis that sensed hydrodynamic pressure forces can entrain body actuation through local feedback loops. We found evidence that this peripheral mechanism leads to self-organized undulatory swimming by providing intersegmental coordination and body oscillations. Swimming can be redundantly induced by central mechanisms, and we show that, therefore, a combination of both central and peripheral mechanisms offers a higher robustness against neural disruptions than any of them alone, which potentially explains how some vertebrates retain locomotor capabilities after spinal cord lesions. These results broaden our understanding of animal locomotion and expand our knowledge for the design of robust and modular robots that physically interact with the environment.
Collapse
Affiliation(s)
- Robin Thandiackal
- École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland. .,Harvard University, Cambridge MA, USA
| | - Kamilo Melo
- École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland. .,KM-RoBoTa Sàrl, Renens, Switzerland
| | - Laura Paez
- École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | | | | | | | | | | | | | - Auke J Ijspeert
- École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.
| |
Collapse
|
3
|
Aguzzi J, Costa C, Calisti M, Funari V, Stefanni S, Danovaro R, Gomes HI, Vecchi F, Dartnell LR, Weiss P, Nowak K, Chatzievangelou D, Marini S. Research Trends and Future Perspectives in Marine Biomimicking Robotics. SENSORS (BASEL, SWITZERLAND) 2021; 21:3778. [PMID: 34072452 PMCID: PMC8198061 DOI: 10.3390/s21113778] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/14/2021] [Revised: 05/17/2021] [Accepted: 05/27/2021] [Indexed: 12/16/2022]
Abstract
Mechatronic and soft robotics are taking inspiration from the animal kingdom to create new high-performance robots. Here, we focused on marine biomimetic research and used innovative bibliographic statistics tools, to highlight established and emerging knowledge domains. A total of 6980 scientific publications retrieved from the Scopus database (1950-2020), evidencing a sharp research increase in 2003-2004. Clustering analysis of countries collaborations showed two major Asian-North America and European clusters. Three significant areas appeared: (i) energy provision, whose advancement mainly relies on microbial fuel cells, (ii) biomaterials for not yet fully operational soft-robotic solutions; and finally (iii), design and control, chiefly oriented to locomotor designs. In this scenario, marine biomimicking robotics still lacks solutions for the long-lasting energy provision, which presently hinders operation autonomy. In the research environment, identifying natural processes by which living organisms obtain energy is thus urgent to sustain energy-demanding tasks while, at the same time, the natural designs must increasingly inform to optimize energy consumption.
Collapse
Affiliation(s)
- Jacopo Aguzzi
- Department of Renewable Marine Resources, Instituto de Ciencias del Mar (ICM-CSIC), 08003 Barcelona, Spain
- Stazione Zoologica Anton Dohrn (SZN), 80122 Naples, Italy; (V.F.); (S.S.); (R.D.); (F.V.)
| | - Corrado Costa
- Centro di Ricerca Ingegneria e Trasformazioni Agroalimentari, Consiglio per la Ricerca in Agricoltura e l’Analisi dell’Economia Agraria (CREA), 00015 Rome, Italy
| | - Marcello Calisti
- The BioRobotics Institute, Scuola Superiore Sant’Anna (SSAA), 56127 Pisa, Italy;
- Lincoln Institute for Agri-food Technology (LIAT), University of Lincoln, Lincoln LN6 7TS, UK
| | - Valerio Funari
- Stazione Zoologica Anton Dohrn (SZN), 80122 Naples, Italy; (V.F.); (S.S.); (R.D.); (F.V.)
- Consiglio Nazionale delle Ricerche (CNR), Istituto di Scienze Marine (ISMAR), 40129 Bologna, Italy
| | - Sergio Stefanni
- Stazione Zoologica Anton Dohrn (SZN), 80122 Naples, Italy; (V.F.); (S.S.); (R.D.); (F.V.)
| | - Roberto Danovaro
- Stazione Zoologica Anton Dohrn (SZN), 80122 Naples, Italy; (V.F.); (S.S.); (R.D.); (F.V.)
- Department of Life and Environmental Science, Università Politecnica delle Marche, 60121 Ancona, Italy
| | - Helena I. Gomes
- Faculty of Engineering, University of Nottingham, Nottingham NG7 2RD, UK;
| | - Fabrizio Vecchi
- Stazione Zoologica Anton Dohrn (SZN), 80122 Naples, Italy; (V.F.); (S.S.); (R.D.); (F.V.)
| | - Lewis R. Dartnell
- School of Life Sciences, University of Westminster, London W1W 6UW, UK;
| | | | - Kathrin Nowak
- Compagnie Maritime d’Expertises (COMEX), 13275 Marseille, France;
| | | | - Simone Marini
- Consiglio Nazionale delle Ricerche (CNR), Istituto di Scienze Marine (ISMAR), 19032 La Spezia, Italy;
| |
Collapse
|
4
|
Chen K, Hwu T, Kashyap HJ, Krichmar JL, Stewart K, Xing J, Zou X. Neurorobots as a Means Toward Neuroethology and Explainable AI. Front Neurorobot 2020; 14:570308. [PMID: 33192435 PMCID: PMC7604467 DOI: 10.3389/fnbot.2020.570308] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2020] [Accepted: 08/25/2020] [Indexed: 12/18/2022] Open
Abstract
Understanding why deep neural networks and machine learning algorithms act as they do is a difficult endeavor. Neuroscientists are faced with similar problems. One way biologists address this issue is by closely observing behavior while recording neurons or manipulating brain circuits. This has been called neuroethology. In a similar way, neurorobotics can be used to explain how neural network activity leads to behavior. In real world settings, neurorobots have been shown to perform behaviors analogous to animals. Moreover, a neuroroboticist has total control over the network, and by analyzing different neural groups or studying the effect of network perturbations (e.g., simulated lesions), they may be able to explain how the robot's behavior arises from artificial brain activity. In this paper, we review neurorobot experiments by focusing on how the robot's behavior leads to a qualitative and quantitative explanation of neural activity, and vice versa, that is, how neural activity leads to behavior. We suggest that using neurorobots as a form of computational neuroethology can be a powerful methodology for understanding neuroscience, as well as for artificial intelligence and machine learning.
Collapse
Affiliation(s)
- Kexin Chen
- Department of Cognitive Sciences, University of California, Irvine, Irvine, CA, United States
| | - Tiffany Hwu
- HRL Laboratories (formerly Hughes Research Laboratory), LLC, Malibu, CA, United States
| | - Hirak J Kashyap
- Department of Computer Science, University of California, Irvine, Irvine, CA, United States
| | - Jeffrey L Krichmar
- Department of Cognitive Sciences, University of California, Irvine, Irvine, CA, United States.,Department of Computer Science, University of California, Irvine, Irvine, CA, United States
| | - Kenneth Stewart
- Department of Computer Science, University of California, Irvine, Irvine, CA, United States
| | - Jinwei Xing
- Department of Cognitive Sciences, University of California, Irvine, Irvine, CA, United States
| | - Xinyun Zou
- Department of Computer Science, University of California, Irvine, Irvine, CA, United States
| |
Collapse
|