The considered information sharing is based on the following pattern: The leader has access only to its own state, i.e., does not sense or receive any information on the states of the remaining agents, and communicates information to them regarding to their goal destinations. Each follower has access to its own state, measures the position of agents lying in its sensing area, exchanges information on pose and velocity with agents lying in its safety area, and receives information from the leader regarding to its goal destination, as long as the leader lies within an upper bounded distance with respect to the follower.
Published in Chapter:
Distributed Control of Robot Swarms: A Lyapunov-Like Barrier Functions Approach
Dimitra Panagou (University of Michigan, USA), Dušan M. Stipanović (University of Illinois, USA), and Petros G. Voulgaris (University of Illinois, USA)
Copyright: © 2016
|Pages: 30
DOI: 10.4018/978-1-4666-9572-6.ch005
Abstract
This chapter considers the problem of multi-agent coordination and control under multiple objectives, and presents a set-theoretic formulation which is amenable to Lyapunov-based analysis and control design. A novel class of Lyapunov-like barrier functions is introduced and used to encode multiple control objectives, such as collision avoidance, proximity maintenance and convergence to desired destinations. The construction is based on recentered barrier functions and on maximum approximation functions. Thus, a single Lyapunov-like function is used to encode the constrained set of each agent, yielding simple, gradient-based control solutions. The derived control strategies are distributed, i.e., based on information locally available to each agent, which is dictated by sensing and communication limitations. The proposed coordination protocol dictates semi-cooperative conflict resolution among agents, as well as conflict resolution with respect to an agent (the leader) which is not actively participating in collision avoidance, except when necessary. The considered scenario is pertinent to surveillance tasks and involves nonholonomic vehicles. The efficacy of the approach is demonstrated through simulation results.