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A new approach of formation navigation derived from multi-robots cooperative online FastSLAM
Authors:Yunfei CAI  Zhenmin TANG and Chunxia ZHAO
Affiliation:Institute of Pattern Recognition and Artificial Intelligence, Nanjing University of Science and Technology,Institute of Pattern Recognition and Artificial Intelligence, Nanjing University of Science and Technology,Institute of Pattern Recognition and Artificial Intelligence, Nanjing University of Science and Technology
Abstract:A new formation navigation approach derived from multi-robots cooperative online FastSLAM is proposed. In this approach, the leader and follower robots are defined. The posteriori estimation of the leader robot state is treated as a relative reference for all follower robots to correct their state priori estimations. The control volume of individual follower will be achieved from the results of the corrected estimation. All robots are observed as landmarks with known associations by the others and are considered in their landmarks updating. By the method, the errors of the robot posterior estimations are reduced and the formation is well kept. The simulation and physical experiment results show that the multi-robots relative localization accuracy is improved and the formation navigation control is more stable and efficient than normal leader-following strategy. The algorithm is easy in implementation.
Keywords:Multi-robots  Formation navigation  FastSLAM
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