Position adaptive formation control for multi-robot system using a redundant adaptive robust Kalman filter

Xiancui Wei, Zhiguo Shi
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Abstract

Leader-follower based formation control is a promising technique in multi-robot motion planning system. When the pose of leader-robot mutated or disturbed by external disturbance, the follower-robot usually cannot react quickly, resulting in loss tracing. A redundant adaptive robust Kalman filter (RAREKF) is adopted to predict the relative movement parameters between the leader and follower, so that the followers can reach the desired position and orientation quickly and accurately. According to the actual situation, the redundancy factor in RAREKF is designed to compensate the timeliness lack of the tracking process. This approach has the advantages of eliminating the system state noises and errors generated by the sudden change of formation, which can ensure rapidity and accuracy of the tracking process and maintain the stability of the formation. The validity of the method mentioned above has been verified by simulation experiments.
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基于冗余自适应鲁棒卡尔曼滤波的多机器人位置自适应编队控制
基于Leader-follower的群体控制是多机器人运动规划系统中一种很有前途的技术。当leader-robot姿态发生突变或受到外界干扰时,follower-robot往往不能快速做出反应,导致丢失跟踪。采用冗余自适应鲁棒卡尔曼滤波(RAREKF)预测leader和follower之间的相对运动参数,使follower能够快速准确地到达期望的位置和方向。根据实际情况,设计了RAREKF中的冗余因子来补偿跟踪过程的时效性不足。该方法的优点是消除了编队突然变化所产生的系统状态噪声和误差,保证了跟踪过程的快速性和准确性,保持了编队的稳定性。仿真实验验证了该方法的有效性。
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