Target tracking and obstacle avoidance for multi-agent networks with input constraints

Abstract

In this paper, the problems of target tracking and obstacle avoidance for multi-agent networks with input constraints are investigated. When there is a moving obstacle, the control objectives are to make the agents track a moving target and to avoid collisions among agents. First, without considering the input constraints, a novel distributed controller can be obtained based on the potential function. Second, at each sampling time, the control algorithm is optimized. Furthermore, to solve the problem that agents cannot effectively avoid the obstacles in dynamic environment where the obstacles are moving, a new velocity repulsive potential is designed. One advantage of the designed control algorithm is that each agent only requires local knowledge of its neighboring agents. Finally, simulation results are provided to verify the effectiveness of the proposed approach.

Finite-time Consensus for Multi-agent Systems via Nonlinear Control Protocols

“…In recent years, the study of consensus problems for multi-agent systems has received a great deal of attentions and considerable research efforts in various fields, partially due to the broad applications in motion control of multiple mobile robots [1] , formation control [2] , and target tracking and obstacle avoidance [3] , etc. Consensus means that a group of agents reaches an agreement on a common value by communicating with their neighbors.…”