Formation Control of Mobile Robots with Active Obstacle Avoidance

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In this paper,the formation control and obstacle avoidance problems are dealt with a unified control algorithm,which allows the follower to avoid obstacle while maintaining desired relative bearing or relative distance from the leader.In the known leader-follower robot formation control literature,absolute motion states of the leader robot are required to control the followers, which may not be available in some environments.In this research,the leader-follower robot formation is modelled and controlled in terms of the relative motion states between the leader and follower robots.The absolute motion states of the leader robot are not required in the proposed formation controller.Furthermore,the research has been extended to a novel obstacle avoidance scheme based on sensing the relative motion between robot and obstacle.Experimental investigation has been conducted using the platform consisted of three nonholonomic mobile robots and computer vision system,and the results have demonstrated the effectiveness of the proposed methods. In this paper, the formation control and obstacle avoidance problems are dealt with a unified control algorithm, which allows the follower to avoid obstacle while maintaining desired relative bearing or relative distance from the leader. In the known leader-follower robot formation control literature, absolute motion states of the leader robot are required to control the followers, which may not be available in some environments. in this research, the leader-follower formation is modelled and controlled in terms of the relative motion states between the leader and follower robots. The absolute motion states of the leader robot are not required in the proposed formation controller. Stillrther, the research has been extended to a novel obstacle avoidance scheme based on sensing the relative motion between robot and obstacle. Experimental cycle has been conducted using the platform consisted of three nonholonomic mobile robots and computer vision system, and the results have demonstra ted the effectiveness of the proposed methods.
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