移动机械臂跟踪控制与运动规划研究
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摘要
移动机械臂是由移动平台与固定在其上的机械臂组成的机器人系统。该系统集移动机器人工作空间的广阔性与工业机械臂的运动灵巧性于一身。这种组合极大地扩展了机器人的应用领域。现在,移动机械臂已被应用到家用服务、工业生产和国防安全等各个领域,具有广泛的应用价值。因此研究移动机械臂的理论知识具有非常强的现实意义。而由移动平台带给整体机器人系统的机构冗余和非完整性约束的特性,也使得机器人可以避免奇异位姿并通过优化自身轨迹来完成指定任务。这些都是移动机械臂研究中的重点和难点。
目前对于移动机器人与工业机械臂的研究已有相当多的进展,开发出了不少成熟的运动规划与跟踪控制算法。但移动机械臂在运动过程中,其移动平台与固定其上的机械臂是同时运动的,而由于这两部分的动力学相互耦合,使得分别对这两部分进行跟踪控制时存在较大干扰,这就对移动机械臂的控制算法提出了新的要求。另外,移动机械臂的运动轨迹由移动平台与机械臂两者构成,比之单独的移动机器人或机械臂的运动规划要额外考虑两者间的协调问题,比如如何运动才能最节省能耗,而这就需要新的运动规划思路。因此,研究移动机械臂运动规划与跟踪控制算法是非常有意义的工作。
本文主要从理论研究的角度,以通用的移动机械臂模型为研究对象,设计了一种新的移动机械臂跟踪控制策略和运动规划思路。其中,针对移动机械臂的跟踪控制问题,本文引入了一种运动解耦的方法,充分利用其机构冗余的特点,构建了一种将机器人移动平台和机械臂的轨迹跟踪分开进行控制的框架,并针对两者分别设计了基于自抗扰技术的跟踪控制器。为了验证设计的控制策略的正确性与有效性,本文搭建了在验证中采用的移动机械臂系统仿真平台。该仿真平台采用MATLAB中的SIMULINK和S函数实现,完成了移动机械臂前向动力学仿真模块用来模拟机器人,并设计了仿真中所需的反馈回路、控制综合与轨迹生成等模块,并在其上完成了移动机械臂跟踪控制的仿真研究。
此外,本文还将表征空间的思路应用到移动机械臂运动规划上来。将描述移动机械臂系统的变量投射到表征空间中进行统一的运动规划与协调研究。本文在表征空间采用了基于A星算法的搜索策略,对移动机械臂通过障碍物时移动平台与机械臂的协调问题进行了分析与研究。
A mobile manipulator system is formed by a mobile platform and a robotic arm that fixed upon it. This system has both the advantages of mobile platform’s large workspace and the dexterity of a robotic arm, and such a combination greatly extends the robot’s application field. Now, mobile manipulator has already been used in a wide range of applications such as household services, industrial production and national security, etc. Therefore, the study of mobile manipulators’theoretical knowledge has a very strong practical significance. Moreover, most of mobile manipulators are redundant and non-holonomic, and these qualities bring the possibilities for robotic system to avoid singular pose and optimize its own trajectories when completing tasks. All these are important points and difficulties in the study of mobile manipulators.
Up to now, there are already many progresses in the research of mobile robot and industrial robot arm, and many well-known algorithms concerning motion planning and trajectory tracking control have been developed. But in the case of a mobile manipulator, its’mobile platform and robotic arm are moving simultaneously. Since the two parts’dynamics are coupled together, their individual tracking control has a lot of disturbance. And it is central to develop new method to solve such a problem. In addition, compared to a single mobile robot or a robotic arm, the motion trajectories of mobile manipulators are composed by its’two subsystems, so the coordination of two must bring into consideration, such as how to plan the moving trajectories to achieve energy saving goal. This requires new thoughts in the motion planning of mobile manipulators. So now, we can see it is very meaningful to study the trajectory tracking and motion planning problems of mobile manipulators.
This paper mainly focuses on the theoretical research perspective, using common mobile manipulators’model as research objects, designs a new method for mobile manipulator’s tracking control and motion planning. For the problem of tracking control, this paper introduces a motion decoupling method into mobile manipulators’model and designs an architecture for separating the control of the mobile platform and robotic arm. In order to verify the correctness and effectiveness of this control strategy, this paper also introduces the simulation platform designed for the algorithm verification. This platform uses SIMULINK and s-function in MATLAB to simulate a mobile manipulator in the real world, which includes a forward dynamic module, a feedback loop, a control integration module and motion generation module, etc. All the simulation researches for mobile manipulator are done using this platform.
Also, this paper introduces the idea of using representation space into the motion planning for mobile manipulators, which putting all the necessary variables that describe the mobile manipulator system into one the representation space, and unified motion planning and coordination are achieved. Moreover, this paper uses A-star based searching method in dealing with representation space trajectory searching, and analysis and researches are done concerning the coordination in motion planning when a mobile manipulator passing through channels.
目前对于移动机器人与工业机械臂的研究已有相当多的进展,开发出了不少成熟的运动规划与跟踪控制算法。但移动机械臂在运动过程中,其移动平台与固定其上的机械臂是同时运动的,而由于这两部分的动力学相互耦合,使得分别对这两部分进行跟踪控制时存在较大干扰,这就对移动机械臂的控制算法提出了新的要求。另外,移动机械臂的运动轨迹由移动平台与机械臂两者构成,比之单独的移动机器人或机械臂的运动规划要额外考虑两者间的协调问题,比如如何运动才能最节省能耗,而这就需要新的运动规划思路。因此,研究移动机械臂运动规划与跟踪控制算法是非常有意义的工作。
本文主要从理论研究的角度,以通用的移动机械臂模型为研究对象,设计了一种新的移动机械臂跟踪控制策略和运动规划思路。其中,针对移动机械臂的跟踪控制问题,本文引入了一种运动解耦的方法,充分利用其机构冗余的特点,构建了一种将机器人移动平台和机械臂的轨迹跟踪分开进行控制的框架,并针对两者分别设计了基于自抗扰技术的跟踪控制器。为了验证设计的控制策略的正确性与有效性,本文搭建了在验证中采用的移动机械臂系统仿真平台。该仿真平台采用MATLAB中的SIMULINK和S函数实现,完成了移动机械臂前向动力学仿真模块用来模拟机器人,并设计了仿真中所需的反馈回路、控制综合与轨迹生成等模块,并在其上完成了移动机械臂跟踪控制的仿真研究。
此外,本文还将表征空间的思路应用到移动机械臂运动规划上来。将描述移动机械臂系统的变量投射到表征空间中进行统一的运动规划与协调研究。本文在表征空间采用了基于A星算法的搜索策略,对移动机械臂通过障碍物时移动平台与机械臂的协调问题进行了分析与研究。
A mobile manipulator system is formed by a mobile platform and a robotic arm that fixed upon it. This system has both the advantages of mobile platform’s large workspace and the dexterity of a robotic arm, and such a combination greatly extends the robot’s application field. Now, mobile manipulator has already been used in a wide range of applications such as household services, industrial production and national security, etc. Therefore, the study of mobile manipulators’theoretical knowledge has a very strong practical significance. Moreover, most of mobile manipulators are redundant and non-holonomic, and these qualities bring the possibilities for robotic system to avoid singular pose and optimize its own trajectories when completing tasks. All these are important points and difficulties in the study of mobile manipulators.
Up to now, there are already many progresses in the research of mobile robot and industrial robot arm, and many well-known algorithms concerning motion planning and trajectory tracking control have been developed. But in the case of a mobile manipulator, its’mobile platform and robotic arm are moving simultaneously. Since the two parts’dynamics are coupled together, their individual tracking control has a lot of disturbance. And it is central to develop new method to solve such a problem. In addition, compared to a single mobile robot or a robotic arm, the motion trajectories of mobile manipulators are composed by its’two subsystems, so the coordination of two must bring into consideration, such as how to plan the moving trajectories to achieve energy saving goal. This requires new thoughts in the motion planning of mobile manipulators. So now, we can see it is very meaningful to study the trajectory tracking and motion planning problems of mobile manipulators.
This paper mainly focuses on the theoretical research perspective, using common mobile manipulators’model as research objects, designs a new method for mobile manipulator’s tracking control and motion planning. For the problem of tracking control, this paper introduces a motion decoupling method into mobile manipulators’model and designs an architecture for separating the control of the mobile platform and robotic arm. In order to verify the correctness and effectiveness of this control strategy, this paper also introduces the simulation platform designed for the algorithm verification. This platform uses SIMULINK and s-function in MATLAB to simulate a mobile manipulator in the real world, which includes a forward dynamic module, a feedback loop, a control integration module and motion generation module, etc. All the simulation researches for mobile manipulator are done using this platform.
Also, this paper introduces the idea of using representation space into the motion planning for mobile manipulators, which putting all the necessary variables that describe the mobile manipulator system into one the representation space, and unified motion planning and coordination are achieved. Moreover, this paper uses A-star based searching method in dealing with representation space trajectory searching, and analysis and researches are done concerning the coordination in motion planning when a mobile manipulator passing through channels.
引文
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[2] Dong Hun Shin, Bradley S. Hamner, etc. Motion Planning for a Mobile Manipulator with Imprecise Locomotion[C]. IEEE/RSJ International Conference on Intelligent Robots and Systems, Oct. 2003, 847-853.
[3] Kazunori Ohno, Shouich Morimura, etc. Semi-autonomous Control System of Rescue Crawler Robot Having Flippers for Getting Over Unknown-Steps[C]. IEEE/RSJ International Conference on Intelligent Robots and Systems, Oct. 2007, 3012-3018.
[4] Kenji INOUE, Yusuke NISHIHAMA, etc. Mobile Manipulator of Humanoid Robots– Body and Leg Control for Dual Arm Manipulation[C]. IEEE International Conference on Robotics and Automation, May 2002, 2259-2264.
[5] M. Carreras, P. Ridao, R. Garcia and T. Nicosevici. Vision-based Localization of an Underwater Robot in a Structured Environment[C]. IEEE International Conference on Robotics and Automation, Sep. 2003, 971-976.
[6] Side Zhao, Junku Yuh. Experimental Study on Advanced Underwater Robot Control[J]. IEEE Transactions on Robotics, Aug. 2005, 21(4): 695-703.
[7] Yangsheng Xu, Samuel Kwok-Wai Au. Stabilization and Path Following of a Single Wheel Robot[J]. IEEE/ASME Transactions on Mechatronics, Jun. 2004, 9(2): 407-418.
[8] Nakano Eiji, Nagasaka Sei. Leg-Wheel Robot: A Futuristic Mobile Platform for Forestry Industry[C]. IEEE/Tsukuba International Workshop on Advanced Robotics, Nov. 1993, 109-112.
[9] Homayoun Seraji. Motion Control of Mobile Maniupualtors[C]. IEEE/RSJ International Conference on Intelligent Robots and Systems, Jul. 1993, 2056-2063.
[10] G.J. Wiens, W.M. Jang. Passive Joint Control of Dynamic Coupling in Mobile Robots[J]. The International Journal of Robotics Research, Dec. 2011, 13(3): 209-219.
[11] Yoshio Yamamoto and Xiaoping Yun. Control of Mobile Manipulators Following a Moving Surface[C]. IEEE International Conference on Robotics and Automation, May 1993, 1-6.
[12] Homayoun Seraji. Motion Control of Mobile Manipulators[C]. IEEE/RSJ International Conference on Intelligent Robots and Systems, Jul. 1993, 2056-2063.
[13] Sheng Lin and A. A. Goldenberg. Neural-Network Control of Mobile Manipulators[J]. IEEE Transactions on Neural Networks, Sep. 2001, 12(5): 1121-1133.
[14] Kai Liu and Frank L. Lewis. Decentralized Continuous Robust Controller for Mobile Robots[C]. IEEE International Conference on Robotics and Automation, May 1990, 1822-1827.
[15] P. Ogren, M. Egerstedt, and X. Hu. Reactive Mobile Manipulator using Dynamic Trajectory Tracking[C]. IEEE International Conference on Robotics and Automation, Apr. 2000, 3473-3478.
[16] Serdar Soylu, Bradley J. Buckham, Ron P. Podhorodeski. Redundancy resolution for underwater mobile manipulators[J]. Ocean Engineering, 2010, 37(2), 325-343.
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