Fuzzy Formation Control and Collision Avoidance for Multiagent Systems

Abstract

This paper aims to investigate the formation control of leader-follower multiagent systems, where the problem of collision avoidance is considered. Based on the graph-theoretic concepts and locally distributed information, a neural fuzzy formation controller is designed with the capability of online learning. The learning rules of controller parameters can be derived from the gradient descent method. To avoid collisions between neighboring agents, a fuzzy separation controller is proposed such that the local minimum problem can be solved. In order to highlight the advantages of this fuzzy logic based collision-free formation control, both of the static and dynamic leaders are discussed for performance comparisons. Simulation results indicate that the proposed fuzzy formation and separation control can provide better formation responses compared to conventional consensus formation and potential-based collision-avoidance algorithms.

Finite-Time Formation Control without Collisions for Multiagent Systems with Communication Graphs Composed of Cyclic Paths

“…Proof. The closed-loop system in terms of the Laplacian matrix and using initially (15) instead of (16) takes the forṁ…”

“…In order to achieve the trajectory, a control strategy based on a pure pursuit algorithm was implemented in the robots. The collision avoidance in the leader-follower multiagent systems was studied in [15]. The graph theory is used to model the communication topology between agents.…”

Multiple robots motion control to transport an object

“…There are some method for robot motion control, such as EKF [7], optimal feedback control [8], robust control [9], intelligent control [10], decentralized control [11], and Sliding mode control. EKF requires a long time to update the desired states.…”

Motion coordination for swarm robots

“…However, only few of existing results have been presented to solve the problem of this behavior in multi-agent systems based on interval type-2 fuzzy logic controller (IT2FLC) [10][11][12]. This paper aims to investigate the motion coordination control base on IT2FLC, where the problem of collision avoidance and flock centering are considered.…”