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A new approach of formation navigation derived from multi-robots cooperative online FastSLAM
  • ISSN号:1672-6340
  • 期刊名称:控制理论与应用(英文版)
  • 时间:0
  • 页码:451-457
  • 分类:TP242[自动化与计算机技术—控制科学与工程;自动化与计算机技术—检测技术与自动化装置] TP273[自动化与计算机技术—控制科学与工程;自动化与计算机技术—检测技术与自动化装置]
  • 作者机构:[1]Institute of Pattern Recognition and Artificial Intelligence, Nanjing University of Science and Technology, Nanjing Jiangsu 210094, China
  • 相关基金:This work was supported by the National Natural Science Foundation of China (No. 90820306).
  • 相关项目:乡村道路环境下无人驾驶车辆关键技术与集成验证平台研究
中文摘要:

<正>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.

英文摘要:

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.

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