Robot Collection and Transport of Objects: A Biomimetic Process

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

Active Particles Bound by Information Flows

Self-organization is the generation of order out of local interactions in non-equilibrium [1]. It is deeply connected to all fields of science from physics, chemistry to biology where functional living structures self-assemble[2] and constantly evolve[3] all based on physical interactions. The emergence of collective animal behavior[4], of society or language are the results of self-organization processes as well though they involve abstract interactions arising from sensory inputs, information processing, storage and feedback[5-7]. Resulting collective behaviors are found for example in crowds of people, flocks of birds, schools of fish or swarms of bacteria[8,9]. Here we introduce such information based interactions to the behavior of active microparticles. A real time feedback of active particle positions controls the propulsion direction these active particles. The emerging structures are bound by dissipation and reveal frustrated geometries due to confinement to two dimensions. They diffuse like passive clusters of colloids, but possess internal dynamical degrees of freedom that are determined by the feed- back and the noise in the system. As the information processing in the feedback loops can be designed almost arbitrarily, new perspectives for self-organization studies involving coupled feedback systems with separate timescales, machine learning and swarm intelligence arise.Comment: 13 pages, 4 figure

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

So far, actuated fish models have been used to study animal interactions in small-scale controlled experiments. This study, conducted in a semi-controlled setting, investigates robot5interactions with a large wild-caught marine fish school (∼3000 individuals) in their natural social environment. Two towed fish robots were used to decouple size, tail motion and speed in a series of sea-cage experiments. Using high-resolution imaging sonar and sonar-video blind scoring, we monitored and classified the school's collective reaction towards the fish robots as attraction or avoidance. We found that two key releasers—the size and the speed of the robotic fish—were responsible for triggering either evasive reactions or following responses. At the same time, we found fish reactions to the tail motion to be insignificant. The fish evaded a fast-moving robot even if it was small. However, mackerels following propensity was greater towards a slow small robot. When moving slowly, the larger robot triggered significantly more avoidance responses than a small robot. Our results suggest that the collective responses of a large school exposed to a robotic fish could be manipulated by tuning two principal releasers—size and speed. These results can help to design experimental methods for in situ observations of wild fish schools or to develop underwater robots for guiding and interacting with free-ranging aggregated aquatic organisms.This work was financed by the Norwegian Research Council (grant 204229/F20) and Estonian Government Target Financing (grant SF0140018s12). JCC was partially supported by a grant from Iceland, Liechtenstein and Norway through the EEA Financial Mechanism, operated by Universidad Complutense de Madrid. We are grateful to A. Totland for his technical help. The animal collection was approved by The Royal Norwegian Ministry of Fisheries, and the experiment was approved by the Norwegian Animal Research Authority. The Institute of Marine Research is permitted to conduct experiments at the Austevoll aquaculture facility by the Norwegian Biological Resource Committee and the Norwegian Animal Research Committee (Forsøksdyrutvalget)

Follow the dummy: measuring the influence of a biomimetic robotic fish-lure on the collective decisions of a zebrafish shoal inside a circular corridor

Robotic agents that are accepted by animals as conspecifics are very powerful tools in behavioral biology because of the ways they help in studying social interactions in gregarious animals. In recent years, we have developed a biomimetic robotic fish lure for the purpose of studying the behavior of the zebrafish Danio rerio. In this paper, we present a series of experiments that were designed to assess the impact of some features of the lure regarding its acceptance among the fish. We developed an experimental setup composed of a circular corridor and a motorized rotating system able to steer the lure inside the corridor with a tunable linear speed. We used the fish swimming direction and distance between the fish and the lure as a metric to characterize the level of acceptance of the lure, depending on various parameters. The methodology presented and the experimental results are promising for the field of animal–robot interaction studies

Investigation of Communication Constraints in Distributed Multi-Agent Systems

Based on a simple flocking model with collision avoidance, a set of investigations of multi-agent system communication constraints have been conducted, including distributed estimation of global features, the influence of jamming, and communication performance optimization. In flocking control, it is necessary to achieve a common velocity among agents and maintain a safe distance between neighboring agents. The local information among agents is exchanged in a distributed fashion to help achieve velocity consensus. A distributed estimation algorithm was recently proposed to estimate the group’s global features based on achieving consensus among agents’ local estimations of such global features. To reduce the communication load, the exchange of local estimations among agents occurs at discrete time instants defined by an event-triggering mechanism. To confirm the effectiveness of the new distributed estimation algorithm, we simulated the algorithm while adopting a simple flocking control technique with collision avoidance. In addition, the effect of jamming on flocking control and the distributed algorithm is studied through computer simulations. Finally, to better exploit the communication channel among agents, we study a recently proposed formation control multi-agent algorithm, which optimizes the inter-agent distance in order to achieve optimum inter-agent communication performance. The study is also conducted through computer simulations, which confirms the effectiveness of the algorithm

A robotic honeycomb for interaction with a honeybee colony

Abstract: Robotic technologies have shown the capability to interact with living organisms and even to form integrated mixed societies comprised of living and artificial agents. Bio-compatible robots, incorporating sensing and actuation capable of generating and responding to relevant stimuli, can be a tool to study collective behaviors previously unattainable with traditional techniques. To investigate collective behaviors of the western honeybee (Apis mellifera), we designed a robotic system capable of observing and modulating the bee cluster using an array of thermal sensors and actuators. We initially integrated the system into a beehive populated with approximately 4,000 bees for several months. The robotic system was able to observe the colony by continuously collecting spatio- temporal thermal profiles of the winter cluster. Furthermore, we found that our robotic device reliably modulated the superorganism’s response to dynamic thermal stimulation, influencing its spatiotemporal re-organization. In addition, after identifying the thermal collapse of a colony, we used the robotic system in a “life-support” mode via its thermal actuators. Ultimately, we demonstrated a robotic device capable of autonomous closed-loop interaction with a cluster comprising thousands of individual bees. Such biohybrid societies open the door to investigation of collective behaviors that necessitate observing and interacting with the animals within a complete social context, as well as for potential applications in augmenting the survivability of these pollinators crucial to our ecosystems and our food supply. This is the author’s version of the work. It is posted here by permission of the AAAS for personal use, not for redistribution. The definitive version was published in Science Robotics, Vol. 8, 76, Mar 2023, DOI: 10.1126/scirobotics.add7385 https://doi.org/10.1126/scirobotics.add738

Mechanisms of Vocal Coordination in Zebra Finches

Social animals frequently emit communication calls. Although these calls are often innate in their acoustic structure, they can be used adaptably to coordinate behavior with other individuals. It is not known, however, what each animal needs to learn in order to achieve and maintain synchronized call patterns with others. To study this process, we have developed a vocal robot that can be programed to generate call patterns or to sense a bird\u27s contact (short) calls and respond with precisely timed call answers. By varying the robot\u27s vocal behavior, including call timing and rhythm, we tested how interacting zebra finches adapt to different call patterns produced by a partner robot bird. This approach allows us to assess engagement and the capacity to synchronize calls between females (vocal non-learners) and males (vocal learners) as well as birds with different levels of developmental social experience. We also tested if forebrain structures that are known to be involved in song learning are required for the coordination of calls. We discovered that zebra finches can learn to adjust the timing of their responses to a robot bird partner within minutes. Further, when challenged with complex rhythms containing jamming elements, birds dynamically adjusted the timing of their calls in anticipation of jamming. Blocking the song system cortical output dramatically reduced the precision of birds\u27 response timing and abolished their ability to avoid jamming. Surprisingly, we observed this effect in both males and females, indicating that the female song system is functional rather than vestigial. We then tested if social interactions during development are necessary for birds to acquire the capacity to synchronize and adapt their call timing to those of a partner bird robot. We found that socially isolated birds were extremely imprecise in the timing of their responses. Further, they were unable to avoid disruptive jamming. Interestingly, these results were very similar to those observed after blocking the forebrain song system in socialized birds. We conclude that social interactions during development are necessary for zebra finch males to develop the capacity to precisely adapt the timing of their calls. Further, the capacity to synchronize calls must be acquired independently from that of song learning. Finally, we investigated if, and to what extent, birds can take into account the behavior of a third party while interacting with a partner. Using miniaturized wireless audio transmitters, we found that when two birds are interacting simultaneously with the vocal robot and with each other, they can avoid jamming with each other and with robot by cooperatively changing the latencies of their answer calls. These qualitative results suggest that birds are capable of adjusting the timing of their calls with respect to more than a single partner bird. Together, our results uncover behavioral and physiological mechanisms that give rise to vocal coordination, bridging a functional gap between innate and learned vocalization abilities

Zebrafish Adjust Their Behavior in Response to an Interactive Robotic Predator

Zebrafish (Danio rerio) constitutes a valuable experimental species for the study of the biological determinants of emotional responses, such as fear and anxiety. Fear-related test paradigms traditionally entail the interaction between focal subjects and live predators, which may show inconsistent behavior throughout the experiment. To address this technical challenge, robotic stimuli are now frequently integrated in behavioral studies, yielding repeatable, customizable, and controllable experimental conditions. While most of the research has focused on open-loop control where robotic stimuli are preprogrammed to execute a priori known actions, recent work has explored the possibility of two-way interactions between robotic stimuli and live subjects. Here, we demonstrate a “closed-loop control” system to investigate fear response of zebrafish in which the response of the robotic stimulus is determined in real-time through a finite-state Markov chain constructed from independent observations on the interactions between zebrafish and their predator. Specifically, we designed a 3D-printed robotic replica of the zebrafish allopatric predator red tiger Oscar fish (Astronotus ocellatus), instrumented to interact in real-time with live subjects. We investigated the role of closed-loop control in modulating fear response in zebrafish through the analysis of the focal fish ethogram and the information-theoretic quantification of the interaction between the subject and the replica. Our results indicate that closed-loop control elicits consistent fear response in zebrafish and that zebrafish quickly adjust their behavior to avoid the predator's attacks. The augmented degree of interactivity afforded by the Markov-chain-dependent actuation of the replica constitutes a fundamental advancement in the study of animal-robot interactions and offers a new means for the development of experimental paradigms to study fear

Inferring causal relationships in zebrafish-robot interactions through transfer entropy: a small lure to catch a big fish

In the field of animal behavior, effective methods to apprehend causal relationships that underlie the interactions between animals are in dire need. How to identify a leader in a group of social animals or quantify the mutual response of predator and prey are exemplary questions that would benefit from an improved understanding of causality. Information theory offers a potent framework to objectively infer cause-and-effect relationships from raw experimental data, in the form of behavioral observations or individual trajectory tracks. In this targeted review, we summarize recent advances in the application of the information-theoretic concept of transfer entropy to animal interactions. First, we offer an introduction to the theory of transfer entropy, keeping a balance between fundamentals and practical implementation. Then, we focus on animal-robot experiments as a means for the validation of the use of transfer entropy to measure causal relationships. We explore a test battery of robotics-based protocols designed for studying zebrafish social behavior and fear response. Grounded in experimental evidence, we demonstrate the potential of transfer entropy to assist in the detection and quantification of causal relationships in animal interactions. The proposed robotics-based platforms offer versatile, controllable, and customizable stimuli to generate a priori known cause-and-effect relationships, which would not be feasible with live stimuli. We conclude the paper with an outlook on possible applications of transfer entropy to study group behavior and clarify the determinants of leadership in social animals