基于状态切换的分布式多机器人编队控制
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摘要
人工势场方法、虚拟结构方法、领导跟随方法、基于行为的方法等传统多移动机器人编队控制算法,都只在编队控制的某个环节有较好的效果,并没有有效解决编队组建、行进、变换、避障等一系列完整动作。针对上述算法的优缺点及适应情形,应用切换系统的思想,提出了基于状态切换的分布式多机器人编队控制算法。设计了基于复合信息的状态切换触发机制,通过机器人自身状态和周围环境适时触发切换机制,合理选择编队控制的一种或多种算法;提出了基于超宽带(UWB)测距的队形反馈机制,利用UWB数据结构简单、便于在微型移动机器人上进行处理的特点,实时完成对整个编队队形的保持和反馈,同时提出分布式状态估计算法,为触发机制提供机器人的运行状态。通过搭建多移动机器人平台,将所提策略应用到实际机器人编队控制中,验证了算法的有效性和稳定性。
Traditional multi-mobile robot formation control algorithms,such as artificial potential field method,virtual structure method,leader-follower method and behavior-based method,have good effects in a specific part of formation control,and have not effectively solve a series of complete movement of formation,marching,transformation and obstacle avoidance. For the advantages and disadvantages of the algorithms mentioned above,the switching system is applied,and a distributed multi-robot formation control algorithm based on state switching is proposed. A state-switching trigger mechanism based on complex information is designed. The switching mechanism is triggered by the robot's own state and the surrounding environment,and one or more algorithms of formation control are reasonably selected. A formation feedback mechanism based on ultra-wideband( UWB) rangefinding is proposed,which makes use of the simple data structure of UWB to facilitate the processing of the micro-mobile robot,and completes the keeping and feedback of formation in real time. A distributed state estimation algorithm is proposed to provide the running state of robot for the trigger mechanism. The proposed strategy is applied to the actual robot formation control by constructing a multi-mobile robot platform,and the effectiveness and stability of the algorithm are verified.
Traditional multi-mobile robot formation control algorithms,such as artificial potential field method,virtual structure method,leader-follower method and behavior-based method,have good effects in a specific part of formation control,and have not effectively solve a series of complete movement of formation,marching,transformation and obstacle avoidance. For the advantages and disadvantages of the algorithms mentioned above,the switching system is applied,and a distributed multi-robot formation control algorithm based on state switching is proposed. A state-switching trigger mechanism based on complex information is designed. The switching mechanism is triggered by the robot's own state and the surrounding environment,and one or more algorithms of formation control are reasonably selected. A formation feedback mechanism based on ultra-wideband( UWB) rangefinding is proposed,which makes use of the simple data structure of UWB to facilitate the processing of the micro-mobile robot,and completes the keeping and feedback of formation in real time. A distributed state estimation algorithm is proposed to provide the running state of robot for the trigger mechanism. The proposed strategy is applied to the actual robot formation control by constructing a multi-mobile robot platform,and the effectiveness and stability of the algorithm are verified.
引文
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[16]卫恒,吕强,王国胜,等.基于超宽带测距的异构移动机器人轨迹跟踪控制[J].北京航空航天大学学报,2018,44(7):1461-1471.WEI H,LQ,WANG G S,et al. Trajectory tracking control for heterogeneous mobile robots based on improved UWB ranging[J]. Journal of Beijing University of Aeronautics and Astronautics,2018,44(7):1461-1471.(in Chinese)
[2] Al ONSO-MORA J,MONTIJANO E,NAGELI T,et al. Distributed multi-robot formation control in dynamic environments[J/OL].Autonomous Robots,2018[2018-07-10]. https:∥doi. org/10.1007/s10514-018-9783-9.
[3] YANG X,HUA C C,YAN J,et al. Adaptive formation control of cooperative teleoperators with intermittent communications[J].IEEE Transactions on Cybernetics,2018,99(3):1-10.
[4] TRINH M H,ZHAO S,SUN Z,et al. Bearing-based formation control of A group of agents with leader-first follower structure[J/OL]. IEEE Transactions on Automatic Control:1-17[2018-06-24]. https:∥doi. org/10. 1109/TAC. 2018. 2836022.
[5] CUNNINGHAM A G,EUSTICE R M,OLSON E et al. Multipolicy decision-making for autonomous driving via change point-based behavior prediction:theory and experiment[J]. Autonomous Robots,2017,41(6):1367-1382.
[6] LI X X,XIE L H. Dynamic formation control over directed networks using graphical Laplacian approach[J]. IEEE Transactions on Automatic Control,2018,56(7):21-35.
[7]潘无为,姜大鹏,庞永杰,等.人工势场和虚拟结构相结合的多水下机器人编队控制[J].兵工学报,2017,38(2):326-334.PAN W W,JIANG D P,PANG Y J,et al. A multi-AUV formation algorithm combining artificial potential field and virtual structure[J]. Acta Armamentarii,2017,38(2):326-334.(in Chinese)
[8] DESAI J P,OSTROWSKI J,KUMAR V. Controlling formations of multiple mobile robots[C]∥Proceedings of IEEE International Conference on Robotics and Automation. Leuven, Belgium:IEEE,1998:2864-2869.
[9] TAKAHASHI H,NISHI H,OHNISHI K. Autonomous decentralized control for formation of multiple mobile robots considering ability of robot[J]. IEEE Transactions on Industrial Electronics,2004,51(6):1272-1279.
[10] LEWIS M A,TAN K H. High precision formation control of mobile robots using virtual structures[J]. Autonomous Robots,1997,4(4):387-403.
[11]贾一帆,初亮,许楠,等.车用双电源开绕组电机驱动系统绕组模式切换及电流控制策略[J].吉林大学学报(工学版),2018,48(1):20-29.JIA Y F,CHU L,XU N,et al. Winding mode shifting and current control strategy of dual power open-winding PMSM drive system for electric vehicle[J]. Journal of Jilin University(Engineering and Technical Edition),2018,48(1):20-29.(in Chinese)
[12]程代展,郭宇骞.切换系统进展[J].控制理论与应用,2005,22(6):954-960.CHENG D Z,GUO Y Q. Advances on switched systems[J].Control Theory&Applications,2005,22(6):954-960.(in Chinese)
[13]付主木,李东卫,宋书中,等.单轴联结式并联混合动力汽车分层切换控制设计[J].控制理论与应用,2017,34(10):1339-1348.FU Z M,LI D W,SONG S Z,et al. Hierarchical switching control design for single-axle parallel hybrid electric vehicles[J].Control Theory&Applications,2017,34(10):1339-1348.(in Chinese)
[14] SMITH A J,HOLLINGER G A. Distributed inference-based multi-robot exploration[J]. Autonomous Robots,2018,42(2):1651-1668.
[15] Lü Q,WEI H,LIN H C,et al. Design and implementation of multi robot research platform based on UWB[C]∥Proceedings of the 29th Chinese Control and Decision Conference. Shenyang:Northeastern University Press,2017:7246-7251.
[16]卫恒,吕强,王国胜,等.基于超宽带测距的异构移动机器人轨迹跟踪控制[J].北京航空航天大学学报,2018,44(7):1461-1471.WEI H,LQ,WANG G S,et al. Trajectory tracking control for heterogeneous mobile robots based on improved UWB ranging[J]. Journal of Beijing University of Aeronautics and Astronautics,2018,44(7):1461-1471.(in Chinese)