A Caltech Library Service

Probabilistic and Distributed Control of a Large-Scale Swarm of Autonomous Agents

Bandyopadhyay, Saptarshi and Chung, Soon-Jo and Hadaegh, Fred Y. (2017) Probabilistic and Distributed Control of a Large-Scale Swarm of Autonomous Agents. IEEE Transactions on Robotics, 33 (5). pp. 1103-1123. ISSN 1552-3098.

[img] PDF - Published Version
See Usage Policy.

[img] PDF - Accepted Version
See Usage Policy.


Use this Persistent URL to link to this item:


We present a distributed control algorithm simultaneously solving both the stochastic target assignment and optimal motion control for large-scale swarms to achieve complex formation shapes. Our probabilistic swarm guidance using inhomogeneous Markov chains (PSG–IMC) algorithm adopts a Eulerian density-control framework, under which the physical space is partitioned into multiple bins and the swarm's density distribution over each bin is controlled in a probabilistic fashion to efficiently handle loss or the addition of agents. We assume that the number of agents is much larger than the number of bins and that each agent knows in which bin it is located, the desired formation shape, and the objective function and motion constraints. PSG–IMC determines the bin-to-bin transition probabilities of each agent using a time IMC. These time-varying Markov matrices are computed 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 transitions per time instant that are required to achieve and maintain the desired formation shape, even if agents are added to or removed from the swarm. PSG–IMC scales well with a large number of agents and complex formation shapes and can also be adapted for area exploration applications. We demonstrate the effectiveness of this proposed swarm guidance algorithm by using numerical simulations and hardware experiments with multiple quadrotors.

Item Type:Article
Related URLs:
URLURL TypeDescription Paper
Chung, Soon-Jo0000-0002-6657-3907
Additional Information:© 2017 California Institute of Technology. Manuscript received August 8, 2016; revised January 11, 2017; accepted March 20, 2017. Date of publication June 14, 2017; date of current version October 2, 2017. This paper was recommended for publication by Associate Editor C. Secchi and Editor C. Torras upon evaluation of the reviewers’ comments. This work was supported in part by the Air Force Office of Scientific Research under Grant FA95501210193 and in part by the National Science Foundation under Grant IIS 1253758. The authors would like to thank D. Morgan, G. Subramanian, J. Yu, I. Jang, and S. Rahili for their valuable input. 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. © 2017 California Institute of Technology.
Funding AgencyGrant Number
Air Force Office of Scientific Research (AFOSR)FA95501210193
Subject Keywords:Guidance, Markov chains, multiagent systems, path planning, swarm robotics
Issue or Number:5
Record Number:CaltechAUTHORS:20161122-110230585
Persistent URL:
Official Citation:S. Bandyopadhyay, S. J. Chung and F. Y. Hadaegh, "Probabilistic and Distributed Control of a Large-Scale Swarm of Autonomous Agents," in IEEE Transactions on Robotics, vol. 33, no. 5, pp. 1103-1123, Oct. 2017. doi: 10.1109/TRO.2017.2705044 URL:
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:72244
Deposited By: Ruth Sustaita
Deposited On:22 Nov 2016 20:04
Last Modified:03 Oct 2019 16:15

Repository Staff Only: item control page