未知环境下多机器人协调编队运动控制方法的研究
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摘要
随着机器人应用范围的扩大,对其能力的要求越来越高,多个机器人协作可以完成单个机器人无法完成的复杂任务。编队运动是常用协作策略,但目前多机器人编队研究主要集中于足球机器人和室内机器人等已知环境,室外未知复杂环境中的编队研究较少。本文以室外动态未知环境为应用背景,对多机器人协调编队运动控制进行了研究。
在多机器人控制中,系统结构的选择很重要。由于机器人数目较少且存在相互通讯,本文多机器人系统采用混合式群体结构,队形控制采用领航者跟随法,机器人个体结构选择反应速度快的基于行为的设计。为了提高输出行为的针对性,本文设计了一种分层融合式结构。
室外环境未知,基于采样的运动规划可以避免环境建模,本文设计了一种基于传感器的确定性采样树法(SDT)。在具体行为设计时,考虑到团队侦察的优势,躲避静态障碍物行为采用两种方法(确定性采样法和切线可通行域法)分别设计。利用最小二乘法拟合出动态障碍物的运动轨迹,并采用模糊控制原理来改变机器人运动速度实现避障。
为了适应复杂环境,本文采用队形不完全保持策略。在形成队形时,采用最远距离最小-平均距离最小算法分配队形点,而且机器人能够自行更改队形点,以解决队形点被占的问题。目标点附近可能出现由固定步长带来的震荡问题,为此本文划分了减速区和队形目标区。在保持队形过程中,leader采用队形的条件反馈,并可以根据环境的需要自主进行队形的转换。
针对目前的研究多数以实现编队控制为目的,为了将编队控制与工作任务相结合,本文使用有限状态机的概念,将多机器人系统在不同阶段的任务定义为不同的状态,在每种状态中分别进行编队控制,从而将编队控制变为一种完成任务的手段。最后,对机器人在未知环境下的动态围捕任务进行了仿真,证明了上述方法的有效性和正确性。
With the expansion of robot application, the demand to its ability is more and more high, and robot can cooperatively complete more complex task. Formation is a common cooperation strategy, and most research concentrate in the known environment, few in outdoor unknown complex environment. This thesis focuses on the multi-robot coordination formation in outdoor dynamic unknown environment.
System structure is very important in multi-robot control. Considering robots are few and can intercommunicate, the multi-robot system uses hybrid architecture and leader-follower formation control method. Robot individual structure is based on behavior, and this thesis has designed a layered fusion architecture in order to enhance the output behavior’s pertinency.
Outdoor environment is unknown, and sampling-based motion planning can avoid environment modeling. This thesis has designed one kind method of Sensor-based Deterministic-sampling Tree (SDT). Considering the advantage of sensoring by group, behavior avoiding static obstacle adopted deterministic-sampling method and tangent available- territory method. Fuzzy control was used to change velocity to avoid dynamic obstacle whose track was be curve-fitted by Least-square principle.
Formation wasn’t incompletely kept to adapt to the complex circumstances. Formation point distribution used the farthest-minist-average-minist algorithm, moreover robot can self-determinately change the formation spot when it’s occupied. Deceletaration-zone and goal–zone method was adopted to avoid concussion near the target position. During keeping formation, leader used formation conditional feedback and self-determinately changing figure due to environment.
Aiming at actuality research taking formation control as the goal, the formation control unified with the work mission is researched. The different stage duty was defined as the different state, which carried on formation control separately. The Finite-State Machine(FSM) was used to transformate different states. Finally, the problem that multiple robots cooperatively hunt with unknown environment is disussed , and the validity of proposed method if proved by simulation experiment.
在多机器人控制中,系统结构的选择很重要。由于机器人数目较少且存在相互通讯,本文多机器人系统采用混合式群体结构,队形控制采用领航者跟随法,机器人个体结构选择反应速度快的基于行为的设计。为了提高输出行为的针对性,本文设计了一种分层融合式结构。
室外环境未知,基于采样的运动规划可以避免环境建模,本文设计了一种基于传感器的确定性采样树法(SDT)。在具体行为设计时,考虑到团队侦察的优势,躲避静态障碍物行为采用两种方法(确定性采样法和切线可通行域法)分别设计。利用最小二乘法拟合出动态障碍物的运动轨迹,并采用模糊控制原理来改变机器人运动速度实现避障。
为了适应复杂环境,本文采用队形不完全保持策略。在形成队形时,采用最远距离最小-平均距离最小算法分配队形点,而且机器人能够自行更改队形点,以解决队形点被占的问题。目标点附近可能出现由固定步长带来的震荡问题,为此本文划分了减速区和队形目标区。在保持队形过程中,leader采用队形的条件反馈,并可以根据环境的需要自主进行队形的转换。
针对目前的研究多数以实现编队控制为目的,为了将编队控制与工作任务相结合,本文使用有限状态机的概念,将多机器人系统在不同阶段的任务定义为不同的状态,在每种状态中分别进行编队控制,从而将编队控制变为一种完成任务的手段。最后,对机器人在未知环境下的动态围捕任务进行了仿真,证明了上述方法的有效性和正确性。
With the expansion of robot application, the demand to its ability is more and more high, and robot can cooperatively complete more complex task. Formation is a common cooperation strategy, and most research concentrate in the known environment, few in outdoor unknown complex environment. This thesis focuses on the multi-robot coordination formation in outdoor dynamic unknown environment.
System structure is very important in multi-robot control. Considering robots are few and can intercommunicate, the multi-robot system uses hybrid architecture and leader-follower formation control method. Robot individual structure is based on behavior, and this thesis has designed a layered fusion architecture in order to enhance the output behavior’s pertinency.
Outdoor environment is unknown, and sampling-based motion planning can avoid environment modeling. This thesis has designed one kind method of Sensor-based Deterministic-sampling Tree (SDT). Considering the advantage of sensoring by group, behavior avoiding static obstacle adopted deterministic-sampling method and tangent available- territory method. Fuzzy control was used to change velocity to avoid dynamic obstacle whose track was be curve-fitted by Least-square principle.
Formation wasn’t incompletely kept to adapt to the complex circumstances. Formation point distribution used the farthest-minist-average-minist algorithm, moreover robot can self-determinately change the formation spot when it’s occupied. Deceletaration-zone and goal–zone method was adopted to avoid concussion near the target position. During keeping formation, leader used formation conditional feedback and self-determinately changing figure due to environment.
Aiming at actuality research taking formation control as the goal, the formation control unified with the work mission is researched. The different stage duty was defined as the different state, which carried on formation control separately. The Finite-State Machine(FSM) was used to transformate different states. Finally, the problem that multiple robots cooperatively hunt with unknown environment is disussed , and the validity of proposed method if proved by simulation experiment.
引文
[1] Koivo A J, Bekey G A. Report of Workshop on Coordinated Multiple Robots:Planning, Control and Application. Robotic and Automation, 1998.14(1):91-93
[2]谭民,王硕,曹志强.多机器人系统.北京:清华大学出版社,2005.7-16,110-114,128
[3] Jin K, Liang P, Beni G. Stability of synchronized distributed control of discrete swarm structures. Proceedings of IEEE International conference on robotics and automation, San Diego, 1994: 1033- 1038(W)
[4] http://www.globalsecurity.org/military/systems/ground/xuv.htm
[5]黄闪,蔡鹤皋,谈大龙.面向装配作业的多机器人合作协调系统.机器人.1999.21(1):50-56
[6]原魁,李园,房立新.多移动机器人系统研究发展近况.自动化学报.2007.33(8):786-794
[7]石桂芬.多移动机器人编队容错控制与稳定性研究.华中科技大学硕士学位论文.2004:49-56
[8]任德华,卢桂章.对队形控制的思考.控制与决策.2005.20(6):601-606
[9] N.Nilsson. Shakey the robot. Technical Report 323. SRI International. Menlc Park.1984
[10] Arkin R C. Motor schema-based mobile robot navigation. The International Journal of Robotics Research,1989.8(4):92-112
[11] Brooks R A. A robust layered control system for a mobile robot.IEEE Journal of Robotics and Automation,1986.2(1):14-23
[12] Saridis G.Tword the realization of intelligent controls.Proceedings of the IEEE,1979.67(8):1115-1133
[13]蔡自兴.基于功能/行为集成的自主式移动机器人进化控制体系结构.机器人.2000.22(3):169-175
[14]赵忆文,谈大龙.多移动机器人合作系统中单机器人控制体系统结构研究.机器人. 1999.21(6):421-425
[15] Connell J H. SSS: A Hybrid Architecture Applied to Robot Navigation. Proceedings of the IEEE International Conference on Robotics and Automaiton. 1992:2719-2724
[16]曹志强.未知环境下多机器人协调与控制的队形问题研究.中国科学院自动化研究所博士学位论文.2002:31-34
[17]张磊.多智能体机器人系统设计与编队问题的研究.华中科技大学硕士生论文.2005:11-13
[18]苏治宝,陆际联.多移动机器人队形控制的研究方法.机器人.2003.1(25):88-91
[19]恽为民.基于行为的机器人学.华中科技大学学报(自然科学版).2004.10(32):15-19
[20]谭民,范永,徐国华.机器人群体协作与控制的研究.机器人.2001.23(2):178-182
[21]章苏书,吴敏,曹卫华.混合体系结构在多足球机器人协作中的应用研究.马特斯杯2003年中国机器人大赛暨研讨会论文集,2003.324-330
[22] Wang P.K.C. Navigation strategies for multiple autonomous mobile robots moving in formation.Journal of Robotic Systems.1991. 8(2): 177-195
[23] Jaydev P Desai,Jim Ostrowski,Vijay Kumar.Controlling formations of multiple mobile robots.IEEE Int Conf on Robotics and Automation Belgium,1998:2864-2869
[24] Hiroacki Yamaguchi,Joel W Burdick.Asymptotic stabilization of multiple nonholonomic mobile robots forming group formations.IEEE Int Conf on Robotics and Automation[c].Belgium,1998:3573-3580.
[25] Pereira G A S,Das A K,Kumar V,et a1.Formation control with configuration space constraints.Proc of the IEEE/RJS Int Conf on Intelligent Robots attd Systems.Las Vegas,2003:2755-2760.
[26] Anthony L M, Tan K H. High precision formation control of mobile robots using virtual structures autonomous. Autonomous Robotics, 1997.4: 387-403
[27] Desai J P.A graph theoretic approach for modeling mobile robot team formations.Journal of Robotic Systems,2002.19(11):511-525.
[28] Reza Olfati-Saber ,Richard M. Murray .Graph rigidity and distributed formation stabilization of multi-vehicle systems.41st IEEE Conference on Decision and Control,2002.3:2965-2971
[29] William B D. Model predictive control:extension to coordinated multi-vehicle formations and real-time implementation.Pasadena:California Institute of Technology.2001
[30] Leonard J, Durrant-Whyte H F. Mobile robot localization by tracking geometric beacons.IEEE transaction on robotics and automation, 1991.7(3):376-382
[31] Lozano-Perez T, Wesley M A. An Algorithm for Planning Collision-free Paths Among Polyhedral Obstacles. Communication of the ACM,1979. 22(10):560-570
[32] Liu Y H,Arimoto S. Computation of the tangent graph of polygonal obstacles by moving line processing.IEEE Transaction on Robotics and Automation,1994.10(6):823-830
[33]吴峰光,奚宏生.一种新的基于切线的路径规划方法.机器人,2004.26(3):193-197
[34] Lindemann S R,LaValle S M. Current Issues in Sampling-Based Motion Planning. Proc.Int.Symp.on Robotics Research。Springer-Verlag,2004
[35] Barraquand J,Latombe J C.A monte-carlo algorithm for path planning with many degrees of freedom.IEEE Int.Conf.Robot&Autom,1990.(3),1712-17l7
[36] Kavraki L, Svestka P, Latombe J C, et a1.Probabilistic Road Maps for Path Planning in High-dimensional Configuration Spaces.IEEETrans on Robotics and Automation,1996.12(4):566-580
[37] LaValle S M.Rapidly-Exploring Random Trees: A New Tool for Path Planning.TR 98-11,Computer Science Dept, Iowa State University,1998.
[38] Bekris K E,Chen B Y,Ladd A M.et a1.Multiple Query Probabilistic Roadmap Planning Using Single Query Planning Primitives.Proc of the IEEE / RSJ Int. Conf. on Intelligent Robots & Systems. Las Vegas·2003.(1):656-661
[39] Vallejo D, Jones C, Amato N. An Adaptive Framework for `Single shot` Motion Planning. Proc of the IEEE/RSJ Int. Conf. on Intelligent Robots and Systems.Takamatsu,2000.(3):1722-1727
[40] Oriolo G, Vendittelli M,et a1. The SRT Method: Randomized Strategies for Exploration.Proc IEEE Int. Conf. on Robotics and Automation.New Orleans,2004:4688-4694.
[41] Michael S B, Steven M L, et al. Deterministic vs. Probabilistic Roadmaps[DB/OL],http://dora.cwru.edu/msb/pubs.html,2002
[42]董胜龙,陈卫东,席裕庚.多移动机器人编队的分布式控制系统.机器人, 2000.22(6):433-438.
[43]李少逸.基于极限环的移动机器人避障算法及其实现.沈阳理工大学硕士论文.2004:31-35
[44] Khabit O. Real-time obstacle avoidance for manipulators and mobile robots. International Journal of Robotics Research, 1986.5(1):90-98
[45]覃柯,孙茂相,孙昌志.动态环境下基于改进人工势场法的机器人运动控制.沈阳工业大学学报,2004.26(5):568-571
[46]孙增圻.智能控制理论与技术.北京:清华大学出版社,2000.16-114
[47] Balch T R, Arkin R C. Behavior-based Formation Control for Multirobot Teams. IEEE Transaction on Robotics And Automation,1998.14(6): 926-939
[48] Arkin R C. Motor Schema Based Mobile Robot Navigation. International Journal Robotics Reserch,1989.8(4):92-112
[49] Jing Wang, Suparerk Premvuti, Abdullah Tabbara. A wireless medium access protocol (CSMA/CD-W) for mobile robot based distributed robotic systems. IEEE Proc of Int. Conf. on Robotics and Automation, 1995.2561-2566.
[50]史忠植.智能主体及其应用.北京:科学出版社,2000.30-34
[51]刘维.精通Matlab与C/C++混合程序设计.北京:北京航空航天大学出版社,2005.145-165
[52] Xiaoping Yun, Gokhan Albayrak. Line and circle formation of distributed physical mobile robots, Journal of Robotic Systems,1997. 14(2):63-76
[53]程磊.多移动机器人协调控制系统的研究与实现.华中理工大学博士论文,2005.37-42
[54]唐小禹.多机器人系统中队形控制及避障算法研究.沈阳理工大学硕士生论文,2007.42-46
[2]谭民,王硕,曹志强.多机器人系统.北京:清华大学出版社,2005.7-16,110-114,128
[3] Jin K, Liang P, Beni G. Stability of synchronized distributed control of discrete swarm structures. Proceedings of IEEE International conference on robotics and automation, San Diego, 1994: 1033- 1038(W)
[4] http://www.globalsecurity.org/military/systems/ground/xuv.htm
[5]黄闪,蔡鹤皋,谈大龙.面向装配作业的多机器人合作协调系统.机器人.1999.21(1):50-56
[6]原魁,李园,房立新.多移动机器人系统研究发展近况.自动化学报.2007.33(8):786-794
[7]石桂芬.多移动机器人编队容错控制与稳定性研究.华中科技大学硕士学位论文.2004:49-56
[8]任德华,卢桂章.对队形控制的思考.控制与决策.2005.20(6):601-606
[9] N.Nilsson. Shakey the robot. Technical Report 323. SRI International. Menlc Park.1984
[10] Arkin R C. Motor schema-based mobile robot navigation. The International Journal of Robotics Research,1989.8(4):92-112
[11] Brooks R A. A robust layered control system for a mobile robot.IEEE Journal of Robotics and Automation,1986.2(1):14-23
[12] Saridis G.Tword the realization of intelligent controls.Proceedings of the IEEE,1979.67(8):1115-1133
[13]蔡自兴.基于功能/行为集成的自主式移动机器人进化控制体系结构.机器人.2000.22(3):169-175
[14]赵忆文,谈大龙.多移动机器人合作系统中单机器人控制体系统结构研究.机器人. 1999.21(6):421-425
[15] Connell J H. SSS: A Hybrid Architecture Applied to Robot Navigation. Proceedings of the IEEE International Conference on Robotics and Automaiton. 1992:2719-2724
[16]曹志强.未知环境下多机器人协调与控制的队形问题研究.中国科学院自动化研究所博士学位论文.2002:31-34
[17]张磊.多智能体机器人系统设计与编队问题的研究.华中科技大学硕士生论文.2005:11-13
[18]苏治宝,陆际联.多移动机器人队形控制的研究方法.机器人.2003.1(25):88-91
[19]恽为民.基于行为的机器人学.华中科技大学学报(自然科学版).2004.10(32):15-19
[20]谭民,范永,徐国华.机器人群体协作与控制的研究.机器人.2001.23(2):178-182
[21]章苏书,吴敏,曹卫华.混合体系结构在多足球机器人协作中的应用研究.马特斯杯2003年中国机器人大赛暨研讨会论文集,2003.324-330
[22] Wang P.K.C. Navigation strategies for multiple autonomous mobile robots moving in formation.Journal of Robotic Systems.1991. 8(2): 177-195
[23] Jaydev P Desai,Jim Ostrowski,Vijay Kumar.Controlling formations of multiple mobile robots.IEEE Int Conf on Robotics and Automation Belgium,1998:2864-2869
[24] Hiroacki Yamaguchi,Joel W Burdick.Asymptotic stabilization of multiple nonholonomic mobile robots forming group formations.IEEE Int Conf on Robotics and Automation[c].Belgium,1998:3573-3580.
[25] Pereira G A S,Das A K,Kumar V,et a1.Formation control with configuration space constraints.Proc of the IEEE/RJS Int Conf on Intelligent Robots attd Systems.Las Vegas,2003:2755-2760.
[26] Anthony L M, Tan K H. High precision formation control of mobile robots using virtual structures autonomous. Autonomous Robotics, 1997.4: 387-403
[27] Desai J P.A graph theoretic approach for modeling mobile robot team formations.Journal of Robotic Systems,2002.19(11):511-525.
[28] Reza Olfati-Saber ,Richard M. Murray .Graph rigidity and distributed formation stabilization of multi-vehicle systems.41st IEEE Conference on Decision and Control,2002.3:2965-2971
[29] William B D. Model predictive control:extension to coordinated multi-vehicle formations and real-time implementation.Pasadena:California Institute of Technology.2001
[30] Leonard J, Durrant-Whyte H F. Mobile robot localization by tracking geometric beacons.IEEE transaction on robotics and automation, 1991.7(3):376-382
[31] Lozano-Perez T, Wesley M A. An Algorithm for Planning Collision-free Paths Among Polyhedral Obstacles. Communication of the ACM,1979. 22(10):560-570
[32] Liu Y H,Arimoto S. Computation of the tangent graph of polygonal obstacles by moving line processing.IEEE Transaction on Robotics and Automation,1994.10(6):823-830
[33]吴峰光,奚宏生.一种新的基于切线的路径规划方法.机器人,2004.26(3):193-197
[34] Lindemann S R,LaValle S M. Current Issues in Sampling-Based Motion Planning. Proc.Int.Symp.on Robotics Research。Springer-Verlag,2004
[35] Barraquand J,Latombe J C.A monte-carlo algorithm for path planning with many degrees of freedom.IEEE Int.Conf.Robot&Autom,1990.(3),1712-17l7
[36] Kavraki L, Svestka P, Latombe J C, et a1.Probabilistic Road Maps for Path Planning in High-dimensional Configuration Spaces.IEEETrans on Robotics and Automation,1996.12(4):566-580
[37] LaValle S M.Rapidly-Exploring Random Trees: A New Tool for Path Planning.TR 98-11,Computer Science Dept, Iowa State University,1998.
[38] Bekris K E,Chen B Y,Ladd A M.et a1.Multiple Query Probabilistic Roadmap Planning Using Single Query Planning Primitives.Proc of the IEEE / RSJ Int. Conf. on Intelligent Robots & Systems. Las Vegas·2003.(1):656-661
[39] Vallejo D, Jones C, Amato N. An Adaptive Framework for `Single shot` Motion Planning. Proc of the IEEE/RSJ Int. Conf. on Intelligent Robots and Systems.Takamatsu,2000.(3):1722-1727
[40] Oriolo G, Vendittelli M,et a1. The SRT Method: Randomized Strategies for Exploration.Proc IEEE Int. Conf. on Robotics and Automation.New Orleans,2004:4688-4694.
[41] Michael S B, Steven M L, et al. Deterministic vs. Probabilistic Roadmaps[DB/OL],http://dora.cwru.edu/msb/pubs.html,2002
[42]董胜龙,陈卫东,席裕庚.多移动机器人编队的分布式控制系统.机器人, 2000.22(6):433-438.
[43]李少逸.基于极限环的移动机器人避障算法及其实现.沈阳理工大学硕士论文.2004:31-35
[44] Khabit O. Real-time obstacle avoidance for manipulators and mobile robots. International Journal of Robotics Research, 1986.5(1):90-98
[45]覃柯,孙茂相,孙昌志.动态环境下基于改进人工势场法的机器人运动控制.沈阳工业大学学报,2004.26(5):568-571
[46]孙增圻.智能控制理论与技术.北京:清华大学出版社,2000.16-114
[47] Balch T R, Arkin R C. Behavior-based Formation Control for Multirobot Teams. IEEE Transaction on Robotics And Automation,1998.14(6): 926-939
[48] Arkin R C. Motor Schema Based Mobile Robot Navigation. International Journal Robotics Reserch,1989.8(4):92-112
[49] Jing Wang, Suparerk Premvuti, Abdullah Tabbara. A wireless medium access protocol (CSMA/CD-W) for mobile robot based distributed robotic systems. IEEE Proc of Int. Conf. on Robotics and Automation, 1995.2561-2566.
[50]史忠植.智能主体及其应用.北京:科学出版社,2000.30-34
[51]刘维.精通Matlab与C/C++混合程序设计.北京:北京航空航天大学出版社,2005.145-165
[52] Xiaoping Yun, Gokhan Albayrak. Line and circle formation of distributed physical mobile robots, Journal of Robotic Systems,1997. 14(2):63-76
[53]程磊.多移动机器人协调控制系统的研究与实现.华中理工大学博士论文,2005.37-42
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