Quantized flocking control for second-order multiple agents with obstacle avoidance

Chunguang Li,Guodong Liu,Guangqian Xie,Chongben Tao

doi:10.1177/1687814015624646

Abstract

A quantized flocking control for a group of second-order multiple agents with obstacle avoidance is proposed to address the problem of the exchange of information needed for quantification. With a reasonable assumption, a logarithmic or uniform quantizer is used for the exchange of relative position and velocity information between adjacent agents and the virtual leader, moving at a steady speed along a straight line, and a distributed flocking algorithm with obstacle avoidance capability is designed based on the quantitative information. The Lyapunov stability criterion of nonsmooth systems and the invariance principle are used to prove the stability of these systems. The simulations and experiments are presented to demonstrate the feasibility and effectiveness of the proposed approach.

Highlights

The flocking of a group of autonomous agents is currently a significant research subject in the field of multiple-robot cooperative control
Su et al.[5] revisited the multi-agent flocking in the absence of the above two assumptions and showed that even when only a fraction of agents are informed, the flocking algorithm in Olfati-Saber[4] enables all the informed agents to move with the desired constant velocity and an uninformed agent to move with the same desired velocity if it can be influenced by the informed agents from
The second objective is to verify the flocking algorithm with obstacle avoidance when only a minority of the agents are informed regarding obstacle information. Through both mathematical analysis and numerical simulation, we show that a group of agents form a flock under exchange information quantized by a uniform or logarithmic quantizer condition

Summary

Introduction

The flocking of a group of autonomous agents is currently a significant research subject in the field of multiple-robot cooperative control. Keywords Multiple agents, flocking control, logarithmic quantizer, uniform quantizer The above research works did not investigate the flocking control of second-order multi-agent systems based on quantitative information.

Results

Conclusion