全方位移动仿人型机器人运动规划研究
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摘要
全方位移动仿人型机器人具有平面移动灵活性和可模拟人类上肢操作的特点，是服务机器人研究领域中的一个前沿应用课题，在家政服务、餐厅接待、宾客导引等领域有着极其广泛的应用前景。
由于全方位移动仿人型机器人工作环境具有动态非结构性，机器人必须具备智能化运动的能力来适应环境的变化。而全方位移动仿人型机器人结构复杂、自由度数目较多，其几何约束、运动和驱动力约束下的在线运动规划问题的研究具有很大挑战性。
本文以自主开发的全方位移动仿人型机器人系统为对象，以实现动态非结构环境中机器人无碰撞搬运物料操作的在线运动规划为研究目的，由于受起始、终止位形约束和受工作空间运动过程中的姿态约束，因此对运动学奇异规避、无碰撞路径规划和时间最优轨迹规划及轨迹跟踪鲁棒性问题进行了有创新性的研究，提出了一些新的方法并做了大量仿真和实验验证。论文的主要工作如下：
(1)在工作空间中，针对全方位移动仿人型机器人末端执行器的路径规划过程要求末端执行器位姿变换的平滑和连续性，采用了四元数方法描述末端执行器在工作空间中的旋转运动。针对机器人从工作空间向位形空间映射的逆运动学计算和奇异问题，基于全方位移动仿人型机器人运动的自主性特点，采用了结合机器人速度比椭球修改工作空间期望运动轨迹在线规避机器人奇异位形的方法，并通过构造多目标融合的二次目标函数，计算机器人的优化运动路径。
(2)全方位移动仿人型机器人在动态非结构环境中运动时，需要具备实时判断运动的安全性和完成任务的能力。由于自由度数较多，在结合算法完备性和效率基础上，本文提出了基于随机路标法（PRM）和快速随机扩展树方法（RRT）的综合路径规划方法。其中，随机路标法可以为快速随机扩展树提供根节点，并搜索位形空间内最短自由路径，而基于快速随机扩展树的方法则用于搜索满足工作空间位姿约束的位形空间节点。该方法通过获取完整的环境信息模型，为全方位移动仿人型机器人在线规划出一条无碰撞的运动路径。对于传感器测量范围受限制的情况，可通过运动路径规划的优化来保证机器人在运动过程中对传感测控目标感知的可靠性。
(3)本文针对机器人电机驱动能力有限以及离散控制模式的特点，提出了根据在线规划的无碰撞运动路径进行时间最优轨迹规划的方法。该方法采用四阶三次B样条曲线拟合原始路径节点，构造离散轨迹搜索图，并通过建立机器人动力学模型规划时间最优运动轨迹。同时，针对离散控制模式，对连续时间最优轨迹按照控制周期间隔进行了离散化处理，并通过控制器设计解决了存在扰动情况下的轨迹跟踪鲁棒性问题。
(4)为验证本文所提出的方法的有效性，构建了全方位移动仿人型机器人运动规划的仿真和实验平台。整个系统为本文通过实验验证所提出的运动规划算法提供了平台和基础，也是研制全方位移动仿人型机器人系统的关键实现技术之一。
本文有关全方位移动仿人型机器人搬运物料操作的在线运动规划的相关研究，将有助于提高全方位移动仿人型机器人的运动智能化，从而提高其实际应用性，在理论和应用上都具有一定的借鉴作用和参考价值。
Omni-directional mobile humanoid robots have advantages for their agile movingability on planar floors and the ability to imitate the operation ways of the human’s arm.As a front research topic in service robots field, they have a wide application prospect inhousehold management services, welcome and guide the guests in restaurant or any othercommercial places.
Because the work environment for omni-directional mobile humanoid robots is usuallydynamic and unstructured, robots must have the ability to adapt variable environment.Furthermore as omni-directional mobile humanoid robots have complicated structures andmany degrees of freedom, it is a great challenge for on-line motion planning with collisionavoidance when the geometry constraints, kinematic constraints and driving forceconstraints are taken into account.
In order to study on on-line motion planning for omni-directional mobile humanoidrobots transporting materials in dynamic and unstructured environment, a robot prototypehas been developed. This dissertation concentrates on the motion whose position andposture in the initial and termination are restricted, as well as the motion whose posture isrestricted from the initial to the termination. Some key problems including singularityavoidance, collision-free path planning, time-optimum trajectory planning and robustnessof control are studied. Simulations and experiments have also been performed todemonstrate the methods presented in the dissertation. The mainly research work are listedas follows.
The inverse kinematics calculation and singular problems are discussed. Because thecontinuity of the posture transform in work space is necessary, the quaternion is used todescribe its rotation. As the omni-directional mobile humanoid robot can plan its motionautomatically, we apply a method of changing the trajectory of end-effector in work spaceto avoid its singularity. A quadratic optimization function including multi-objectives isconstructed for optimal motion calculation.
It is necessary for the omni-directional mobile humanoid robot on-line determines itsmotion without collision occurring in dynamic and unstructured environment. As the robothas many degrees of freedom, a path-planning method synthesizing probabilistic roadmapmethod (PRM) and rapidly-exploring random trees method (RRT) is proposed which takesthe completeness and efficiency of algorithm into consideration. The probabilisticroadmap method provides roots of RRT, and search the shortest collision-free path in thejoint space. While the RRT search the joint space nodes meeting the pose constraintsrequirement in the work space. This proposed method can plan collision-free paths for theomni-directional mobile humanoid robot by sensing the3D models in the environment.The path should be optimized to ensure physical sensors work reliably as the sensorsrange is usually limited.
In this paper, it is proposed a time optimal trajectory planning method based on thelimited capacity of the robot motor drive and the discrete control model. This method usescubic B-spline curve fitting the discrete path nodes, and the time optimal robot trajectoryis obtained by constructing a discrete trajectory net. Meanwhile, the time optimaltrajectory is discretized to control real robot, and the robustness of trajectory trackingcontrol is demonstrated when the disturbances exist in practical using.
In order to demonstrate the effectiveness of the proposed method, simulation softwareand an omni-directional mobile humanoid robot are developed. The details of the motiongeneration and motion implementation system are introduced. The whole system providesthe prerequisite and foundation of experimental verification for the proposed motionplanning algorithms. Furthermore it is one of the key technologies for developing theomni-directional mobile humanoid robot.
The on-line motion planning research for the omni-directional mobile humanoid robotwill help to improve its intelligent of motion, so as to enhance its adaptability in practicalapplication. Both in theory and application the research in this dissertation has somereference value.
由于全方位移动仿人型机器人工作环境具有动态非结构性，机器人必须具备智能化运动的能力来适应环境的变化。而全方位移动仿人型机器人结构复杂、自由度数目较多，其几何约束、运动和驱动力约束下的在线运动规划问题的研究具有很大挑战性。
本文以自主开发的全方位移动仿人型机器人系统为对象，以实现动态非结构环境中机器人无碰撞搬运物料操作的在线运动规划为研究目的，由于受起始、终止位形约束和受工作空间运动过程中的姿态约束，因此对运动学奇异规避、无碰撞路径规划和时间最优轨迹规划及轨迹跟踪鲁棒性问题进行了有创新性的研究，提出了一些新的方法并做了大量仿真和实验验证。论文的主要工作如下：
(1)在工作空间中，针对全方位移动仿人型机器人末端执行器的路径规划过程要求末端执行器位姿变换的平滑和连续性，采用了四元数方法描述末端执行器在工作空间中的旋转运动。针对机器人从工作空间向位形空间映射的逆运动学计算和奇异问题，基于全方位移动仿人型机器人运动的自主性特点，采用了结合机器人速度比椭球修改工作空间期望运动轨迹在线规避机器人奇异位形的方法，并通过构造多目标融合的二次目标函数，计算机器人的优化运动路径。
(2)全方位移动仿人型机器人在动态非结构环境中运动时，需要具备实时判断运动的安全性和完成任务的能力。由于自由度数较多，在结合算法完备性和效率基础上，本文提出了基于随机路标法（PRM）和快速随机扩展树方法（RRT）的综合路径规划方法。其中，随机路标法可以为快速随机扩展树提供根节点，并搜索位形空间内最短自由路径，而基于快速随机扩展树的方法则用于搜索满足工作空间位姿约束的位形空间节点。该方法通过获取完整的环境信息模型，为全方位移动仿人型机器人在线规划出一条无碰撞的运动路径。对于传感器测量范围受限制的情况，可通过运动路径规划的优化来保证机器人在运动过程中对传感测控目标感知的可靠性。
(3)本文针对机器人电机驱动能力有限以及离散控制模式的特点，提出了根据在线规划的无碰撞运动路径进行时间最优轨迹规划的方法。该方法采用四阶三次B样条曲线拟合原始路径节点，构造离散轨迹搜索图，并通过建立机器人动力学模型规划时间最优运动轨迹。同时，针对离散控制模式，对连续时间最优轨迹按照控制周期间隔进行了离散化处理，并通过控制器设计解决了存在扰动情况下的轨迹跟踪鲁棒性问题。
(4)为验证本文所提出的方法的有效性，构建了全方位移动仿人型机器人运动规划的仿真和实验平台。整个系统为本文通过实验验证所提出的运动规划算法提供了平台和基础，也是研制全方位移动仿人型机器人系统的关键实现技术之一。
本文有关全方位移动仿人型机器人搬运物料操作的在线运动规划的相关研究，将有助于提高全方位移动仿人型机器人的运动智能化，从而提高其实际应用性，在理论和应用上都具有一定的借鉴作用和参考价值。
Omni-directional mobile humanoid robots have advantages for their agile movingability on planar floors and the ability to imitate the operation ways of the human’s arm.As a front research topic in service robots field, they have a wide application prospect inhousehold management services, welcome and guide the guests in restaurant or any othercommercial places.
Because the work environment for omni-directional mobile humanoid robots is usuallydynamic and unstructured, robots must have the ability to adapt variable environment.Furthermore as omni-directional mobile humanoid robots have complicated structures andmany degrees of freedom, it is a great challenge for on-line motion planning with collisionavoidance when the geometry constraints, kinematic constraints and driving forceconstraints are taken into account.
In order to study on on-line motion planning for omni-directional mobile humanoidrobots transporting materials in dynamic and unstructured environment, a robot prototypehas been developed. This dissertation concentrates on the motion whose position andposture in the initial and termination are restricted, as well as the motion whose posture isrestricted from the initial to the termination. Some key problems including singularityavoidance, collision-free path planning, time-optimum trajectory planning and robustnessof control are studied. Simulations and experiments have also been performed todemonstrate the methods presented in the dissertation. The mainly research work are listedas follows.
The inverse kinematics calculation and singular problems are discussed. Because thecontinuity of the posture transform in work space is necessary, the quaternion is used todescribe its rotation. As the omni-directional mobile humanoid robot can plan its motionautomatically, we apply a method of changing the trajectory of end-effector in work spaceto avoid its singularity. A quadratic optimization function including multi-objectives isconstructed for optimal motion calculation.
It is necessary for the omni-directional mobile humanoid robot on-line determines itsmotion without collision occurring in dynamic and unstructured environment. As the robothas many degrees of freedom, a path-planning method synthesizing probabilistic roadmapmethod (PRM) and rapidly-exploring random trees method (RRT) is proposed which takesthe completeness and efficiency of algorithm into consideration. The probabilisticroadmap method provides roots of RRT, and search the shortest collision-free path in thejoint space. While the RRT search the joint space nodes meeting the pose constraintsrequirement in the work space. This proposed method can plan collision-free paths for theomni-directional mobile humanoid robot by sensing the3D models in the environment.The path should be optimized to ensure physical sensors work reliably as the sensorsrange is usually limited.
In this paper, it is proposed a time optimal trajectory planning method based on thelimited capacity of the robot motor drive and the discrete control model. This method usescubic B-spline curve fitting the discrete path nodes, and the time optimal robot trajectoryis obtained by constructing a discrete trajectory net. Meanwhile, the time optimaltrajectory is discretized to control real robot, and the robustness of trajectory trackingcontrol is demonstrated when the disturbances exist in practical using.
In order to demonstrate the effectiveness of the proposed method, simulation softwareand an omni-directional mobile humanoid robot are developed. The details of the motiongeneration and motion implementation system are introduced. The whole system providesthe prerequisite and foundation of experimental verification for the proposed motionplanning algorithms. Furthermore it is one of the key technologies for developing theomni-directional mobile humanoid robot.
The on-line motion planning research for the omni-directional mobile humanoid robotwill help to improve its intelligent of motion, so as to enhance its adaptability in practicalapplication. Both in theory and application the research in this dissertation has somereference value.
引文
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