Design of robot swarms inspired by self-organization in social insect groups is currently an active research area with a diverse portfolio of potential applications. In this work, the authors propose a control law for efficient area coverage by a robot swarm in a 2D spatial domain, inspired by the unique dynamical characteristics of ant foraging. The novel idea pursued in the effort is that dynamic, adaptive switching between Brownian motion and Lévy flight in the stochastic component of the search increases the efficiency of the search. Influence of different pheromone (the virtual chemotactic agent that drives the foraging) threshold values for switching between Lévy flights and Brownian motion is studied using two performance metrics — area coverage and visit entropy. The results highlight the advantages of the switching strategy for the control framework, particularly in cases when the object of the search is scarce in quantity or getting depleted in real-time.
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ASME 2017 Dynamic Systems and Control Conference
October 11–13, 2017
Tysons, Virginia, USA
Conference Sponsors:
- Dynamic Systems and Control Division
ISBN:
978-0-7918-5828-8
PROCEEDINGS PAPER
Robot Swarm for Efficient Area Coverage Inspired by Ant Foraging: The Case of Adaptive Switching Between Brownian Motion and Lévy Flight Available to Purchase
Aditya Deshpande,
Aditya Deshpande
University of Cincinnati, Cincinnati, OH
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Manish Kumar,
Manish Kumar
University of Cincinnati, Cincinnati, OH
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Subramanian Ramakrishnan
Subramanian Ramakrishnan
University of Minnesota, Duluth, Duluth, MN
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Aditya Deshpande
University of Cincinnati, Cincinnati, OH
Manish Kumar
University of Cincinnati, Cincinnati, OH
Subramanian Ramakrishnan
University of Minnesota, Duluth, Duluth, MN
Paper No:
DSCC2017-5229, V002T14A009; 8 pages
Published Online:
November 14, 2017
Citation
Deshpande, A, Kumar, M, & Ramakrishnan, S. "Robot Swarm for Efficient Area Coverage Inspired by Ant Foraging: The Case of Adaptive Switching Between Brownian Motion and Lévy Flight." Proceedings of the ASME 2017 Dynamic Systems and Control Conference. Volume 2: Mechatronics; Estimation and Identification; Uncertain Systems and Robustness; Path Planning and Motion Control; Tracking Control Systems; Multi-Agent and Networked Systems; Manufacturing; Intelligent Transportation and Vehicles; Sensors and Actuators; Diagnostics and Detection; Unmanned, Ground and Surface Robotics; Motion and Vibration Control Applications. Tysons, Virginia, USA. October 11–13, 2017. V002T14A009. ASME. https://doi.org/10.1115/DSCC2017-5229
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