F. Mondada, A. Martinoli, N. Correll, A. Gribovskiy, J. Halloy, R. Siegwart, J.-L. Deneubourg (2013): A General Methodology for the Control of Mixed Natural-Artificial Societies. In: Kernbach, Serge (Ed.): Handbook of Collective Robotics, pp. 547-586, Pan Stanford, Singapore, 2013.
We present a methodology for designing the artificial lures that are able to provoke particular, potentially beyond natural, responses in collective animal societies. The main difficulty in this process is to predict the emergent response at collective level, which is a function of multiple interactions among the animals and lures. To achieve this, we suggest to adhere to an iterative process consisting of deriving a quantitative behavioral model for the individual animals, identification of potential interactions among individuals based on experimental observations, and validation of the model and its assumptions by means of higher level abstract models (realistic, microscopic, and macroscopic models). The resulting formal description of animal behavior and interactions, can then serve as a guideline for developing specifications of potential robotic platforms or lures, whose behavior
and interactions are in turn validated by using the same methods and tools used for studying the natural society.
N. Correll, M. Schwager, D. Rus (2008): Social Control of Herd Animals by Integration of Artificially Controlled Congeners. In: From Animals to Animats 10. Lecture Notes in Computer Science, pp. 437–446, Osaka, Japan, 2008, (Best Paper Award).
We study social control of a cow herd in which some of the animals are controlled by a sensing and actuation device mounted on the cow. The control is social in that it aims at exploiting the existing gregarious behavior of the animals, rather than controlling each individual directly. As a case study we consider the open-loop control of the herd’s position using location-dependent stimuli. We propose a hybrid dynamical model for capturing the dynamics of the animals during periods of grazing and periods of stress. We assume that stress can either be induced by the sensing and actuation device or by social amplification due to observing/overhearing nearby stressed congeners. The dynamics of the grazing part of the proposed model have been calibrated using experimental data from 10 free-ranging cows, and various assumptions on the animal behavior under stress are investigated by a parameter sweep on the hybrid model. Results show that the gregarious behavior of the animals must be increased during stress for control by undirected stimuli to be successful. We also show that the presence of social amplification of stress allows for robust, low-stress control by controlling only a fraction of the herd.
J. Halloy, J.-M. Ame, G. Sempo C. Detrain, G. Caprari, M. Asadpour, N. Correll, A. Martinoli, F. Mondada, R. Siegwart, J.-L. Deneubourg (2007): Social integration of robots in groups of cockroaches to control self-organized choice. In: Science, 318 (5853), pp. 1155–1158, 2007.
Collective behavior based on self-organization has been shown in group-living animals from insects to vertebrates. These findings have stimulated engineers to investigate approaches for the coordination of autonomous multirobot systems based on self-organization. In this experimental study, we show collective decision-making by mixed groups of cockroaches and socially integrated autonomous robots, leading to shared shelter selection. Individuals, natural or artificial, are perceived as equivalent, and the collective decision emerges from nonlinear feedbacks based on local interactions. Even when in the minority, robots can modulate the collective decision-making process and produce a global pattern not observed in their absence. These results demonstrate the possibility of using intelligent autonomous devices to study and control self-organized behavioral patterns in group-living animals.



One Response to Animal Control

  1. Animal robotics | Greenovationhawaii says:

    [...] Collective Decisions in Mixed Animal-Robot Societies | Correll LabWe wish to design a general methodology for designing mixed animal-robot societies, in which the robots can control the animal swarm/herd/flock in a desired … [...]

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