Aggregation Through Adaptive Random Walks in a Minimalist Robot Swarm

In swarm robotics, random walks have proven to be efficient behaviours to explore unknown environments. By adapting the parameters of the random walk to environmental and social contingencies, it is possible to obtain interesting collective behaviours. In this paper, we introduce two novel aggregation behaviours based on different parameterisations of random walks tuned through numerical optimisation. Cue-based aggregation allows the swarm to reach the centre of an arena relying only on local discrete sampling, but does not guarantee the formation of a dense cluster. Neighbour-based aggregation instead allows the swarm to cluster in a single location based on the local detection of neighbours, but ignores the environmental cue. We then investigate a heterogeneous swarm made up of the two robot types. Results show that a trade-off can be found in terms of robot proportions to achieve cue-based aggregation while keeping the majority of the swarm in a single dense cluster.

[1]  K. Ohkura,et al.  Swarm Crawler Robots Using Lévy Flight for Targets Exploration in Large Environments , 2022, Robotics.

[2]  M. Birattari,et al.  Controlling Robot Swarm Aggregation through a Minority of Informed Robots , 2022, ANTS Conference.

[3]  Tugay Alperen Karagüzel,et al.  Environment induced emergence of collective behavior in evolving swarms with limited sensing , 2022, GECCO.

[4]  P. A. Vargas,et al.  Efficient quantitative assessment of robot swarms: coverage and targeting Lévy strategies , 2022, Bioinspiration & biomimetics.

[5]  Eliseo Ferrante,et al.  Cultural evolution of probabilistic aggregation in synthetic swarms , 2021, Appl. Soft Comput..

[6]  Bao Pang,et al.  Effect of random walk methods on searching efficiency in swarm robots for area exploration , 2021, Appl. Intell..

[7]  G. Volpe,et al.  Microscale Marangoni Surfers. , 2020, Physical review letters.

[8]  G. Volpe,et al.  Feedback-controlled active brownian colloids with space-dependent rotational dynamics , 2019, Nature Communications.

[9]  H. Karani,et al.  Tuning the Random Walk of Active Colloids: From Individual Run-and-Tumble to Dynamic Clustering. , 2019, Physical review letters.

[10]  Eliseo Ferrante,et al.  On self-organised aggregation dynamics in swarms of robots with informed robots , 2019, Neural Computing and Applications.

[11]  James A. R. Marshall,et al.  Simulating Kilobots Within ARGoS: Models and Experimental Validation , 2018, ANTS Conference.

[12]  James A. R. Marshall,et al.  ARK: Augmented Reality for Kilobots , 2017, IEEE Robotics and Automation Letters.

[13]  Giuseppe Oriolo,et al.  Random Walks in Swarm Robotics: An Experiment with Kilobots , 2016, ANTS Conference.

[14]  Yoshiaki Katada,et al.  Swarm robotic network using Lévy flight in target detection problem , 2016, Artificial Life and Robotics.

[15]  Tony J. Dodd,et al.  Self-organized aggregation without computation , 2014, Int. J. Robotics Res..

[16]  Ali Emre Turgut,et al.  Cue-based aggregation with a mobile robot swarm: a novel fuzzy-based method , 2014, Adapt. Behav..

[17]  Thomas Schmickl,et al.  Dynamics of Collective Decision Making of Honeybees in Complex Temperature Fields , 2013, PloS one.

[18]  M. Dorigo,et al.  ARGoS: a modular, parallel, multi-engine simulator for multi-robot systems , 2012, Swarm Intelligence.

[19]  Radhika Nagpal,et al.  Kilobot: A low cost scalable robot system for collective behaviors , 2012, 2012 IEEE International Conference on Robotics and Automation.

[20]  V. Isaeva.  Self-organization in biological systems , 2012, Biology Bulletin.

[21]  Thomas Schmickl,et al.  Noname manuscript No. (will be inserted by the editor) Analysis of Emergent Symmetry Breaking in Collective Decision Making , 2010 .

[22]  Guy Theraulaz,et al.  The Embodiment of Cockroach Aggregation Behavior in a Group of Micro-robots , 2008, Artificial Life.

[23]  Erol Sahin,et al.  Probabilistic aggregation strategies in swarm robotic systems , 2005, Proceedings 2005 IEEE Swarm Intelligence Symposium, 2005. SIS 2005..

[24]  J. Deneubourg,et al.  Self-organized aggregation in cockroaches , 2005, Animal Behaviour.

[25]  M. Dorigo,et al.  Evolving Self-Organizing Behaviors for a Swarm-Bot , 2004, Auton. Robots.

[26]  E. Kaplan,et al.  Nonparametric Estimation from Incomplete Observations , 1958 .

[27]  V. Trianni,et al.  Adaptive Strategies for Team Formation in Minimalist Robot Swarms , 2022, IEEE Robotics and Automation Letters.

[28]  D.,et al.  Random walk exploration for swarm mapping , 2019 .

[29]  Leslie Pérez Cáceres,et al.  The irace package: Iterated racing for automatic algorithm configuration , 2016 .

[30]  Vito Trianni,et al.  Fundamental Collective Behaviors in Swarm Robotics , 2015, Handbook of Computational Intelligence.