Collective responses of a large mackerel school depend on the size and speed of a robotic fish but not on tail motion

Quantifying the biomimicry gap in biohybrid robot-fish pairs

Biohybrid systems in which robotic lures interact with animals have become compelling tools for probing and identifying the mechanisms underlying collective animal behavior. One key challenge lies in the transfer of social interaction models from simulations to reality, using robotics to validate the modeling hypotheses. This challenge arises in bridging what we term the 'biomimicry gap', which is caused by imperfect robotic replicas, communication cues and physics constraints not incorporated in the simulations, that may elicit unrealistic behavioral responses in animals. In this work, we used a biomimetic lure of a rummy-nose tetra fish (Hemigrammus rhodostomus) and a neural network (NN) model for generating biomimetic social interactions. Through experiments with a biohybrid pair comprising a fish and the robotic lure, a pair of real fish, and simulations of pairs of fish, we demonstrate that our biohybrid system generates social interactions mirroring those of genuine fish pairs. Our analyses highlight that: 1) the lure and NN maintain minimal deviation in real-world interactions compared to simulations and fish-only experiments, 2) our NN controls the robot efficiently in real-time, and 3) a comprehensive validation is crucial to bridge the biomimicry gap, ensuring realistic biohybrid systems.

The role of hydrodynamics in collective motions of fish schools and bioinspired underwater robots

Collective behaviour defines the lives of many animal species on the Earth. Underwater swarms span several orders of magnitude in size, from coral larvae and krill to tunas and dolphins. Agent-based algorithms have modelled collective movements of animal groups by use of social forces, which approximate the behaviour of individual animals. But details of how swarming individuals interact with the fluid environment are often under-examined. How do fluid forces shape aquatic swarms? How do fish use their flow-sensing capabilities to coordinate with their schooling mates? We propose viewing underwater collective behaviour from the framework of fluid stigmergy, which considers both physical interactions and information transfer in fluid environments. Understanding the role of hydrodynamics in aquatic collectives requires multi-disciplinary efforts across fluid mechanics, biology and biomimetic robotics. To facilitate future collaborations, we synthesize key studies in these fields.

Proactivity of fish and leadership of self-propelled robotic fish during interaction

Fish interacting with biomimetic robotic fish is beneficial for animal behavior research, particularly in the study of collective behavior. Compared with passive-dragging robotic fish, self-propelled robotic fish floats in water, and its movement matches the flow field formed by the caudal fin oscillation, leading to more realistic interaction with animals. In this paper, we propose a self-propelled koi-mimicking robotic fish entity, develop a system for robotic fish and koi fish interaction, and conduct extensive experiments on quantity variation and parameter variation. The results showed that fish exhibited significantly lower proactivity when alone, and the most proactive case is one robotic fish interacting with two real fish. The experiments on parameter variation indicated that fish may respond more proactivity to robotic fish that swim with high frequency and low amplitude, but may also move together with high-frequency and high-amplitude swimming robotic fish. These findings could provide insights into fish collective behavior, guide the design of further fish-robot interaction experiments, and suggest directions for future improvements in goal-oriented robotic fish platforms.

Entropy and Fractal Techniques for Monitoring Fish Behaviour and Welfare in Aquacultural Precision Fish Farming-A Review

In a non-linear system, such as a biological system, the change of the output (e.g., behaviour) is not proportional to the change of the input (e.g., exposure to stressors). In addition, biological systems also change over time, i.e., they are dynamic. Non-linear dynamical analyses of biological systems have revealed hidden structures and patterns of behaviour that are not discernible by classical methods. Entropy analyses can quantify their degree of predictability and the directionality of individual interactions, while fractal dimension (FD) analyses can expose patterns of behaviour within apparently random ones. The incorporation of these techniques into the architecture of precision fish farming (PFF) and intelligent aquaculture (IA) is becoming increasingly necessary to understand and predict the evolution of the status of farmed fish. This review summarizes recent works on the application of entropy and FD techniques to selected individual and collective fish behaviours influenced by the number of fish, tagging, pain, preying/feed search, fear/anxiety (and its modulation) and positive emotional contagion (the social contagion of positive emotions). Furthermore, it presents an investigation of collective and individual interactions in shoals, an exposure of the dynamics of inter-individual relationships and hierarchies, and the identification of individuals in groups. While most of the works have been carried out using model species, we believe that they have clear applications in PFF. The review ends by describing some of the major challenges in the field, two of which are, unsurprisingly, the acquisition of high-quality, reliable raw data and the construction of large, reliable databases of non-linear behavioural data for different species and farming conditions.

Open-source five degree of freedom motion platform for investigating fish-robot interaction

This paper presents the design, construction, operation, and validation of a robotic gantry platform specifically designed for studying fish-robot interaction. The platform has five degrees of freedom to manipulate the three-dimensional position, yaw angle, and the pitch of a lure. Additionally, it has a four-conductor slip ring that allows power and data to be transmitted to the lure for the operation of fins and other actuators that increase realism or act as stimuli to focal fish during an ethorobotic experiment. The design is open-source, low-cost, and includes purpose-built electronics, software, and hardware to make it extensible and customizable for a number of applications with varying requirements.

Salmon behavioural response to robots in an aquaculture sea cage

Animal-robot studies can inform us about animal behaviour and inspire advances in agriculture, environmental monitoring and animal health and welfare. Currently, experimental results on how fish are affected by the presence of underwater robots are largely limited to laboratory environments with few individuals and a focus on model species. Laboratory studies provide valuable insight, but their results are not necessarily generalizable to larger scales such as marine aquaculture. This paper examines the effects of underwater robots and a human diver in a large fish aggregation within a Norwegian aquaculture facility, with the explicit purpose to improve the use of underwater robots for fish observations. We observed aquaculture salmon's reaction to the flipper-propelled robot U-CAT in a sea cage with 188 000 individuals. A significant difference in fish behaviour was found using U-CAT when compared to a thruster-driven underwater robot, Argus Mini and a human diver. Specifically, salmon were more likely to swim closer to U-CAT at a lower tailbeat frequency. Fish reactions were not significantly different when considering motor noise or when U-CAT's colour was changed from yellow to silver. No difference was observed in the distance or tailbeat frequency as a response to thruster or flipper motion, when actuated and passively floating robots were compared. These results offer insight into how large aggregations of aquaculture salmon respond to underwater robots. Furthermore, the proposed underwater video processing workflow to assess fish's response to underwater robots is simple and reproducible. This work provides a practical method to study fish-robot interactions, which can lead to improved underwater robot designs to provide more affordable, scalable and effective solutions.

Bidirectional interactions facilitate the integration of a robot into a shoal of zebrafish Danio rerio

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.

Bottom-level motion control for robotic fish to swim in groups: modeling and experiments

Moving in groups is an amazing spectacle of collective behaviour in fish and has attracted considerable interest from many fields, including biology, physics and engineering. Although robotic fish have been well studied, including algorithms to simulate group swimming, experiments that demonstrate multiple robotic fish as a stable group are yet to be achieved. One of the challenges is the lack of a robust bottom-level motion control system for robotic fish platforms. Here we seek to overcome this challenge by focusing on the design and implementation of a motion controller for robotic fish that allows multiple individuals to swim in groups. As direction control is essential in motion control, we first propose a high-accuracy controller which can control a sub-carangiform robotic fish from one arbitrary position/pose (position and direction) to another. We then develop a hydrodynamic-model-based simulation platform to expedite the process of the parameter tuning of the controller. The accuracy of the simulation platform was assessed by comparing the results from experiments on a robotic fish using speeding and turning tests. Subsequently, extensive simulations and experiments with robotic fish were used to verify the accuracy and robustness of the bottom-level motion control. Finally, we demonstrate the efficacy of our controller by implementing group swimming using three robotic fish swimming freely in prescribed trajectories. Although the fluid environment can be complex during group swimming, our bottom-level motion control remained nominally accurate and robust. This motion control strategy lays a solid foundation for further studies of group swimming with multiple robotic fish.

Prey Responses to Exotic Predators: Effects of Old Risks and New Cues

Exotic predators can have major negative impacts on prey. Importantly, prey vary considerably in their behavioral responses to exotic predators. Factors proposed to explain variation in prey response to exotic predators include the similarity of new predators to familiar, native predators, the prevalence and diversity of predators in a prey's past, and variation in a prey's innate ability to discriminate between predators and safety. While these factors have been put forth verbally in the literature, no theory exists that combines these hypotheses in a common conceptual framework using a unified behavioral model. Here, we formalize existing verbal arguments by modeling variation in prey responses to new predators in a state-dependent detection theory framework. We find that while some conventional wisdom is upheld, novel predictions emerge. As expected, prey respond poorly to exotic predators that do not closely resemble familiar predators. Furthermore, a history with more abundant or diverse native predators can lessen effects of some exotic predators on prey; however, under some conditions, the opposite prediction emerges. Also, prey that evolved in situations where they easily discriminate between safe and dangerous situations can be more susceptible to novel predators.

Scale invariance in natural and artificial collective systems: a review

Self-organized collective coordinated behaviour is an impressive phenomenon, observed in a variety of natural and artificial systems, in which coherent global structures or dynamics emerge from local interactions between individual parts. If the degree of collective integration of a system does not depend on size, its level of robustness and adaptivity is typically increased and we refer to it as scale-invariant. In this review, we first identify three main types of self-organized scale-invariant systems: scale-invariant spatial structures, scale-invariant topologies and scale-invariant dynamics. We then provide examples of scale invariance from different domains in science, describe their origins and main features and discuss potential challenges and approaches for designing and engineering artificial systems with scale-invariant properties.

Evidence for mutual allocation of social attention through interactive signaling in a mormyrid weakly electric fish

Mormyrid weakly electric fish produce electric organ discharges (EODs) for active electrolocation and electrocommunication. These pulses are emitted with variable interdischarge intervals (IDIs) resulting in temporal discharge patterns and interactive signaling episodes with nearby conspecifics. However, unequivocal assignment of interactive signaling to a specific behavioral context has proven to be challenging. Using an ethorobotical approach, we confronted single individuals of weakly electric Mormyrus rume proboscirostris with a mobile fish robot capable of interacting both physically, on arbitrary trajectories, as well as electrically, by generating echo responses through playback of species-specific EODs, thus synchronizing signals with the fish. Interactive signaling by the fish was more pronounced in response to a dynamic echo playback generated by the robot than in response to playback of static random IDI sequences. Such synchronizations were particularly strong at a distance corresponding to the outer limit of active electrolocation, and when fish oriented toward the fish replica. We therefore argue that interactive signaling through echoing of a conspecific's EODs provides a simple mechanism by which weakly electric fish can specifically address nearby individuals during electrocommunication. Echoing may thus enable mormyrids to mutually allocate social attention and constitute a foundation for complex social behavior and relatively advanced cognitive abilities in a basal vertebrate lineage.

Closed-loop control of zebrafish behaviour in three dimensions using a robotic stimulus

Robotics is continuously being integrated in animal behaviour studies to create customizable, controllable, and repeatable stimuli. However, few systems have capitalized on recent breakthroughs in computer vision and real-time control to enable a two-way interaction between the animal and the robot. Here, we present a "closed-loop control" system to investigate the behaviour of zebrafish, a popular animal model in preclinical studies. The system allows for actuating a biologically-inspired 3D-printed replica in a 3D workspace, in response to the behaviour of a zebrafish. We demonstrate the role of closed-loop control in modulating the response of zebrafish, across a range of behavioural and information-theoretic measures. Our results suggest that closed-loop control could enhance the degree of biomimicry of the replica, by increasing the attraction of live subjects and their interaction with the stimulus. Interactive experiments hold promise to advance our understanding of zebrafish, offering new means for high throughput behavioural phenotyping.

How mimetic should a robotic fish be to socially integrate into zebrafish groups?

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.