机器人系统运动规划与协调的研究
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摘要
随着计算机、电子、通信、控制、传感器及其它相关技术的发展,机器人技术得到了迅猛发展,应用领域层出不穷。一方面,研究者致力于设计更复杂的机构,在个体机器人上安装更加先进、更多种类的传感器,设计更为复杂高效的算法以提高单个机器人的智能和能力,使其能够更好地完成任务,适应更复杂的环境;另一方面,人们采用多个功能相对简单的机器人相互合作,共同完成单个机器人无法完成的具有复杂性、不确定性、并发性、实时性等特点的任务。
单机器人系统在执行给定的任务前,需进行路径规划,同样,多机器人系统也需协调各机器人间的运动以规避冲突。当前常用的运动规划与协调方法虽然得到了广泛应用,取得了较好的效果,但均局限于特定的应用场合,与具体任务及系统特性紧密相关,当任务或环境改变后,原来的方法不能应用,因此缺乏灵活性与统一性。另外,现有的方法都是假定任务可完成情况下的规划与协调,而很少涉及系统的能力范围及任务不能完成的情况。
本文提出一种通用的机器人系统运动规划与协调策略,把单机器人系统的规划问题与多机器人系统的协调问题统一起来,适用于不同环境、不同任务及不同机器人系统中。根据任务要求与系统特性,合理选择状态变量构造系统的状态空间,把系统内部固有的物理约束、外部施加的障碍约束及任务约束映射为状态空间中的不可达区域,则可达区域就表明该机器人系统完成任务的能力范围。将任务的执行过程看作是系统状态在状态可达空间的变迁过程,这样就把机器人系统的规划与协调问题统一转化为状态空间中的轨迹求解。
给出了任务的可完成条件,即当系统初始状态与任务终止状态均位于可达空间,且可达区域内存在起止状态间的连通路径时,任务可完成,此时可根据给定的性能指标在状态空间求解任务实现的最优解。如以上任一条件不满足,则任务无法完成,通过修改系统配置或任务约束将任务转化为可完成,并求解任务可实现的转化条件,以此指导机器人任务的设计、规划与协调。
基于状态空间法实现了不同机器人系统任务的规划与协调,验证了该方法的有效性与通用性。针对单机械臂轨迹规划任务,分析了无障碍约束及障碍约束下机械臂系统完成任务的能力范围及特点,在状态空间求解点到点任务的末端执行器路径最短轨迹,并分析了任务无法完成的情况,求得任务实现的临界配置与临界约束条件,从仿真与硬件实体上实现了状态轨迹跟踪;分别实现了单移动机器人与移动机械臂的路径规划,在基于Internet的办公室服务机器人上实现了动态环境下路径的实时规划与跟踪,对于移动机械臂,在状态空间求解出不同任务要求下移动机械臂的最优轨迹;针对多机器人编队任务,在状态空间求解出约束条件下编队的路径最短变迁轨迹,同时对任务无法完成的情况进行了分析,求得任务实现的约束转化条件,通过仿真与实验实现了轨迹跟踪;针对多机械臂协同操作同一物体的任务,在构造的两种不同状态空间中分别求得不同任务要求下的最优解,实现了多机械臂间的协调运动。
With the development of computer, electronics, communication, control, sensor, and other related technologies, robotics develops rapidly and is applied to a wide range of domains. On the one hand, the researchers aim to design more complicated mechanisms, to mount various advanced sensors on robots, and to develop more efficient algorithms, which improve the intelligence and ability of the single robot to make it capable of performing successfully the tasks and adapting to more complex environments. On the other hand, multiple robots with relatively simple functions are employed to complete the tasks with complicated, uncertain, intercurrent, and real-time properties that cannot be done by a single robot.
Before executing the given task by a single robot, path planning is necessary. It is the same case for a multi-robot system. Motion coordination among the robots is needed in order to avoid collision. It has been widely used for current motion planning and coordination methods in various tasks. However, they can only be exploited on special occasions and are heavily relevant to the tasks and system properties. If the tasks or environments are changed, these methods may not work well. Therefore, they lack of flexibility and generality. In addition, these approaches are able to plan and coordinate the robotic tasks on the implicit condition that the tasks are realizable, whereas the system capability as well as the solutions to unachievable tasks have seldom been addressed.
In this dissertation, we propose a general motion planning and coordination strategy for robot systems, which offers a unified way for planning of single robot systems and coordination of multi-robot systems. It is available in different environments, tasks, and robot systems. The State Space for robot systems is constructed by choosing rationally state variables according to the task requirements and system characteristics. The internal physical constraints, inherent in the system, and external obstacle constraints and task constraints, imposed externally, are mapped into the unrealizable areas in the State Space. Then reachable areas of the system state denote the system ability to complete the tasks. Task execution is considered as transition of the system state in reachable State Space. Thus, the planning and coordination problem of the robot systems is translated into a trajectory solving problem in State Space.
The realizable conditions for the tasks are given. If the system’s initial state and the task’s goal state are both in the reachable space, as well as there exists a connectable path in between within the reachable areas, the task is realizable. The optimal strategy for task fulfillment can be investigated and obtained according to the given performance index. If any condition above is not satisfied, the task is unrealizable. It could be transformed to be realizable by adjusting the system’s configuration and/or task constraint, and the transformation condition for task realization could also be figured out. This lends itself to task designing, planning, and coordination.
It is applied to planning and coordination of different robot systems and tasks in order to validate the effectiveness and generalization of the proposed method. In manipulator path planning tasks, the system ability and characteristic with/without obstacle constraints are analyzed. The shortest trajectory of the end-effector is obtained in the State Space for a Point-to-Point task. The unrealizable task is also addressed, as well as the conditions of critical configurations and critical constraints are derived. The state trajectory trackings are conducted both in simulation and experiment. Path planning for a mobile robot and a mobile manipulator are conducted. Real-time path planning and tracking are realized on an internet-based office robot in dynamic environment. The optimal trajectories of the mobile manipulator under different task requirements are obtained in State Space. For a multi-robot formation task, the minimal path transition trajectory of the formation is solved in State Space. The unrealizable task is addressed, and the constraint transformation contion for task realization is derived. The trajectory trackings are done both in simulation and experiment. In a multi-manipulator task of operating cooperatively a single object, the optimal solutions under different task requirements are obtained in different State Space. Then motion coordination between multiple manipulators is realized.
单机器人系统在执行给定的任务前,需进行路径规划,同样,多机器人系统也需协调各机器人间的运动以规避冲突。当前常用的运动规划与协调方法虽然得到了广泛应用,取得了较好的效果,但均局限于特定的应用场合,与具体任务及系统特性紧密相关,当任务或环境改变后,原来的方法不能应用,因此缺乏灵活性与统一性。另外,现有的方法都是假定任务可完成情况下的规划与协调,而很少涉及系统的能力范围及任务不能完成的情况。
本文提出一种通用的机器人系统运动规划与协调策略,把单机器人系统的规划问题与多机器人系统的协调问题统一起来,适用于不同环境、不同任务及不同机器人系统中。根据任务要求与系统特性,合理选择状态变量构造系统的状态空间,把系统内部固有的物理约束、外部施加的障碍约束及任务约束映射为状态空间中的不可达区域,则可达区域就表明该机器人系统完成任务的能力范围。将任务的执行过程看作是系统状态在状态可达空间的变迁过程,这样就把机器人系统的规划与协调问题统一转化为状态空间中的轨迹求解。
给出了任务的可完成条件,即当系统初始状态与任务终止状态均位于可达空间,且可达区域内存在起止状态间的连通路径时,任务可完成,此时可根据给定的性能指标在状态空间求解任务实现的最优解。如以上任一条件不满足,则任务无法完成,通过修改系统配置或任务约束将任务转化为可完成,并求解任务可实现的转化条件,以此指导机器人任务的设计、规划与协调。
基于状态空间法实现了不同机器人系统任务的规划与协调,验证了该方法的有效性与通用性。针对单机械臂轨迹规划任务,分析了无障碍约束及障碍约束下机械臂系统完成任务的能力范围及特点,在状态空间求解点到点任务的末端执行器路径最短轨迹,并分析了任务无法完成的情况,求得任务实现的临界配置与临界约束条件,从仿真与硬件实体上实现了状态轨迹跟踪;分别实现了单移动机器人与移动机械臂的路径规划,在基于Internet的办公室服务机器人上实现了动态环境下路径的实时规划与跟踪,对于移动机械臂,在状态空间求解出不同任务要求下移动机械臂的最优轨迹;针对多机器人编队任务,在状态空间求解出约束条件下编队的路径最短变迁轨迹,同时对任务无法完成的情况进行了分析,求得任务实现的约束转化条件,通过仿真与实验实现了轨迹跟踪;针对多机械臂协同操作同一物体的任务,在构造的两种不同状态空间中分别求得不同任务要求下的最优解,实现了多机械臂间的协调运动。
With the development of computer, electronics, communication, control, sensor, and other related technologies, robotics develops rapidly and is applied to a wide range of domains. On the one hand, the researchers aim to design more complicated mechanisms, to mount various advanced sensors on robots, and to develop more efficient algorithms, which improve the intelligence and ability of the single robot to make it capable of performing successfully the tasks and adapting to more complex environments. On the other hand, multiple robots with relatively simple functions are employed to complete the tasks with complicated, uncertain, intercurrent, and real-time properties that cannot be done by a single robot.
Before executing the given task by a single robot, path planning is necessary. It is the same case for a multi-robot system. Motion coordination among the robots is needed in order to avoid collision. It has been widely used for current motion planning and coordination methods in various tasks. However, they can only be exploited on special occasions and are heavily relevant to the tasks and system properties. If the tasks or environments are changed, these methods may not work well. Therefore, they lack of flexibility and generality. In addition, these approaches are able to plan and coordinate the robotic tasks on the implicit condition that the tasks are realizable, whereas the system capability as well as the solutions to unachievable tasks have seldom been addressed.
In this dissertation, we propose a general motion planning and coordination strategy for robot systems, which offers a unified way for planning of single robot systems and coordination of multi-robot systems. It is available in different environments, tasks, and robot systems. The State Space for robot systems is constructed by choosing rationally state variables according to the task requirements and system characteristics. The internal physical constraints, inherent in the system, and external obstacle constraints and task constraints, imposed externally, are mapped into the unrealizable areas in the State Space. Then reachable areas of the system state denote the system ability to complete the tasks. Task execution is considered as transition of the system state in reachable State Space. Thus, the planning and coordination problem of the robot systems is translated into a trajectory solving problem in State Space.
The realizable conditions for the tasks are given. If the system’s initial state and the task’s goal state are both in the reachable space, as well as there exists a connectable path in between within the reachable areas, the task is realizable. The optimal strategy for task fulfillment can be investigated and obtained according to the given performance index. If any condition above is not satisfied, the task is unrealizable. It could be transformed to be realizable by adjusting the system’s configuration and/or task constraint, and the transformation condition for task realization could also be figured out. This lends itself to task designing, planning, and coordination.
It is applied to planning and coordination of different robot systems and tasks in order to validate the effectiveness and generalization of the proposed method. In manipulator path planning tasks, the system ability and characteristic with/without obstacle constraints are analyzed. The shortest trajectory of the end-effector is obtained in the State Space for a Point-to-Point task. The unrealizable task is also addressed, as well as the conditions of critical configurations and critical constraints are derived. The state trajectory trackings are conducted both in simulation and experiment. Path planning for a mobile robot and a mobile manipulator are conducted. Real-time path planning and tracking are realized on an internet-based office robot in dynamic environment. The optimal trajectories of the mobile manipulator under different task requirements are obtained in State Space. For a multi-robot formation task, the minimal path transition trajectory of the formation is solved in State Space. The unrealizable task is addressed, and the constraint transformation contion for task realization is derived. The trajectory trackings are done both in simulation and experiment. In a multi-manipulator task of operating cooperatively a single object, the optimal solutions under different task requirements are obtained in different State Space. Then motion coordination between multiple manipulators is realized.
引文
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