Trajectory Planning of 7-DOF Humanoid Manipulator under Rapid and Continuous Reaction and Obstacle Avoidance Environment
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摘要: 人类经长期学习训练后能对高速物体 (如棒球、乒乓球等)具有快速连续反应作业的运动技能, 从深层次上揭示是由于人体在其训练过程中不断学习优选了相应手臂的动作轨迹, 并储存了丰富的经验和知识. 受人体手臂动作此行为机制启发, 本文提出一种 7-DOF灵巧臂快速连续反应-避障作业的轨迹规划方法. 该方法将灵巧臂对高速物体目标作业的轨迹规划问题转化为动作轨迹参数化优选问题, 考虑作业过程中灵巧臂的机构物理约束和障碍约束条件, 以灵巧臂目标可作业度指标构建适应度函数, 采用粒子群优化 (Particle swarm optimization, PSO)方法优选作业轨迹中的冗余参数; 在此基础上 利用灵巧臂动作轨迹参数化优选方法构建相应作业环境下的知识数据库, 实现灵巧臂对高速物体目标的快速连续反应作业. 以仿人机器人乒乓球对弈作业为例, 将该方法应用于 7-DOF灵巧臂乒乓球作业的轨迹规划中. 数值实验及实际对弈试验结果表明, 该方法不仅能使灵巧臂所规划的轨迹 满足灵巧臂机构物理约束与障碍约束条件, 同时能实现灵巧臂对乒乓球体的快速连续反应作业, 验证了该方法的有效性.
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关键词:
- 七自由度灵巧臂 /
- 快速连续反应-避障作业 /
- 轨迹参数化 /
- 知识数据库 /
- 粒子群优化
Abstract: Human being can master rapid and continuous reaction skill for high speed targets (e.g., baseball, ping-pong ball, etc.) after a long-term training process. Taking a deep sight into this phenomenon, it is due to the fact that human being select frequently optimal movement trajectories of the arm, and then store rich knowledge or experience in brain during the training process. Inspired by this mechanism of human being, a trajectory planning method of for a 7-DOF humanoid manipulator under rapid and continuous reaction and obstacle avoidance environment is presented. Through this method, the trajectory planning problem of the humanoid manipulator for high speed targets can be transformed into a trajectory parameterization optimum problem. Considering the physical constraint and obstacles constraint conditions of the humanoid manipulator in operation, a target operation level of the humanoid manipulator for high speed targets is defined to constitute the fitness function and optimization goal, then particle swarm optimization (PSO) is used to search the optimal combination of the redundant parameters of the movement trajectory. Based on these, a knowledge database of the corresponding operation environment is constructed through the trajectory parameterization optimum method, which can make the 7-DOF humanoid manipulator achieve rapid and continuous reaction operation for the high speed target. Finally, a humanoid robot for ping-pong playing is adopted as an example, and the method is employed to solve the trajectory planning problem of humanoid manipulator for ping-pong hitting. Both numerical simulation and actual humanoid robot testing results indicate that the proposed method can not only make the operation trajectory meet the physical constraint and obstacles constraint limitation of the 7-DOF humanoid manipulator, but also make the humanoid manipulator operate with rapid and continuous reaction, which demonstrates the effectiveness of this method for the trajectory planning problem studied. -
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