A switching formation strategy for obstacle avoidance of a multi-robot system based on robot priority model

Area of Science:

• Robotics
• Control Systems
• Artificial Intelligence

Background:

• Multi-robot systems require robust strategies for navigation in complex environments.
• Coordinated movement and formation control are essential for efficient multi-robot operations.
• Obstacle avoidance is a critical challenge for autonomous robots.

Purpose of the Study:

• To develop a novel switching formation strategy for multi-robot systems with velocity constraints.
• To enable robots to effectively avoid and traverse obstacles while maintaining formation.
• To ensure collision-free navigation and precise trajectory tracking.

Main Methods:

• A leader-follower approach where the leader plans a path using geometric obstacle avoidance control method (GOACM).
• Follower robots adjust their positions based on calculated desired distances and bearing angles relative to the leader.
• A novel robot priority model for collision avoidance during formation switching.
• An adaptive tracking control algorithm for trajectory and velocity error convergence.

Main Results:

• Multi-robots successfully formed and switched formations while avoiding obstacles.
• The proposed strategy demonstrated effective collision avoidance.
• Simulation and experimental results validated the proposed methods.

Conclusions:

• The developed switching formation strategy is effective for multi-robot obstacle avoidance.
• The method ensures safe navigation and coordinated movement in dynamic environments.
• The adaptive tracking control guarantees accurate trajectory and velocity following.