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A Probabilistic Eulerian Approach for Motion Planning of a Large-Scale Swarm of Robots

Bandyopadhyay, Saptarshi and Chung, Soon-Jo and Hadaegh, Fred Y. (2016) A Probabilistic Eulerian Approach for Motion Planning of a Large-Scale Swarm of Robots. In: 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). IEEE , Piscataway, NJ, pp. 3822-3829. ISBN 978-1-5090-3761-2. http://resolver.caltech.edu/CaltechAUTHORS:20161221-142802182

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Abstract

We present a novel method for guiding a large-scale swarm of autonomous agents into a desired formation shape in a distributed and scalable manner. Our Probabilistic Swarm Guidance using Inhomogeneous Markov Chains (PSG-IMC) algorithm adopts an Eulerian framework, where the physical space is partitioned into bins and the swarm's density distribution over each bin is controlled. Each agent determines its bin transition probabilities using a time-inhomogeneous Markov chain. These time-varying Markov matrices are constructed by each agent in real-time using the feedback from the current swarm distribution, which is estimated in a distributed manner. The PSG-IMC algorithm minimizes the expected cost of the transitions per time instant, required to achieve and maintain the desired formation shape, even when agents are added to or removed from the swarm. The algorithm scales well with a large number of agents and complex formation shapes. We demonstrate the effectiveness of this proposed swarm guidance algorithm by using results of numerical simulations and hardware experiments with multiple quadrotors.


Item Type:Book Section
Related URLs:
URLURL TypeDescription
http://dx.doi.org/10.1109/IROS.2016.7759562DOIArticle
http://ieeexplore.ieee.org/document/7759562/PublisherArticle
ORCID:
AuthorORCID
Chung, Soon-Jo0000-0002-6657-3907
Additional Information:© 2016 IEEE. Date Added to IEEE Xplore: 01 December 2016. This research was supported in part by AFOSR grant FA95501210193 and NSF IIS 1253758. This research was carried out in part at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration.
Group:GALCIT
Funders:
Funding AgencyGrant Number
Air Force Office of Scientific Research (AFOSR)FA95501210193
NSFIIS-1253758
NASA/JPL/CaltechUNSPECIFIED
Record Number:CaltechAUTHORS:20161221-142802182
Persistent URL:http://resolver.caltech.edu/CaltechAUTHORS:20161221-142802182
Official Citation:S. Bandyopadhyay, Soon-Jo Chung and F. Y. Hadaegh, "A probabilistic eulerian approach for motion planning of a large-scale swarm of robots," 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Daejeon, 2016, pp. 3822-3829. doi: 10.1109/IROS.2016.7759562
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:73102
Collection:CaltechAUTHORS
Deposited By: Ruth Sustaita
Deposited On:21 Dec 2016 22:47
Last Modified:04 Jan 2017 19:38

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