张晗, 陈卫东, 王景川. 多机器人探索系统的人机共享控制[J]. 机器人, 2015, 37(1): 17-24. DOI: 10.13973/j.cnki.robot.2015.017
引用本文: 张晗, 陈卫东, 王景川. 多机器人探索系统的人机共享控制[J]. 机器人, 2015, 37(1): 17-24. DOI: 10.13973/j.cnki.robot.2015.017
ZHANG Han, CHEN Weidong, WANG Jingchuan. Human-Robot Shared Control for Multi-Robot Exploration System[J]. ROBOT, 2015, 37(1): 17-24. DOI: 10.13973/j.cnki.robot.2015.017
Citation: ZHANG Han, CHEN Weidong, WANG Jingchuan. Human-Robot Shared Control for Multi-Robot Exploration System[J]. ROBOT, 2015, 37(1): 17-24. DOI: 10.13973/j.cnki.robot.2015.017

多机器人探索系统的人机共享控制

Human-Robot Shared Control for Multi-Robot Exploration System

  • 摘要: 当多机器人探索系统接受人类操作者的遥控时,其一方面要遵从操作者的意图,另一方面要满足网络连通性约束和提高通信效率等自身性能指标,如何协调两方面的关系,是本文研究的关键问题.在实时任务分配器中,针对实时性和人机决策协调问题,采用边界栅格采样率衰减和面向遥操作者兴趣的任务分配算法,使任务分配决策与人的意图相协调;在拓扑控制器中,对以Steiner点最少且非Steiner点的点权之和最大为优化目标的Steiner树优化问题进行求解,进而控制拓扑,使连通性约束得以保证;在地图融合中心选择器中,通过广度优先搜索选择地图融合中心,从而减小传输带宽和传输能量消耗.在典型室内环境中,与全自主系统Possible Moves Sampling进行了对比仿真,与未使用地图融合中心的探测系统进行了对比实验,结果表明,本系统具有更高、更稳定的探索效率和更小的数据传输量,体现了本文人机共享控制方法的有效性.

     

    Abstract: When multi-robot exploration systems are teleoperated by human, they should follow the operator's intension; on the other hand, they should satisfy the network connectivity constraints and improve their own performance like communication efficiency. This paper focuses on coordinating the relationship between the above two aspects. By attenuating the frontier grids sampling rate and using the teleoperator interest oriented task allocation algorithm, the task allocation decisions and the operator's intention are coordinated by the real-time task allocator to solve the real-time requirements and human-robot decision coordination. In topology controller, an optimization Steiner tree problem is solved to minimize the number of Steiner points and maximize the weight sum of the other points, and thus the connectivity constraints are satisfied. In the selector for map fusion center, breadth first search is adopted to reduce transmission bandwidth cost and energy consumption. In typical indoor environments, comparative simulations against fully autonomous system ''Possible Moves Sampling'' and comparative experiment against an exploration system without a map fusion center are performed. The results show that the proposed system has higher and stabler exploration efficiency and lower data transfer amount, which proves the effectiveness of the human-robot shared control method.

     

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