Global Minimum-Jerk Trajectory Planning of Space Manipulator
Global Minimum-Jerk Trajectory Planning of Space Manipulator
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DOI：
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发表时间：
2006-08
影响因子：
3.2
通讯作者：
Panfeng Huang;Yangsheng Xu;Bin Liang
中科院分区：
文献类型：
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作者：
Panfeng Huang;Yangsheng Xu;Bin Liang
提出了一种基于遗传算法的空间机械臂关节空间全局最小加加速度轨迹规划方法。加加速度是关节轨迹位置的三阶导数，它对控制算法的效率和整个空间机器人系统的稳定性有不利影响，因此应尽量减小加加速度。另一方面，最小化加加速度的重要性是减少机械手的振动。在该公式中，全局遗传方法通过最小化关节空间中的最大加加速度来确定轨迹。该规划过程考虑了关节角约束、关节速度约束、关节角加速度约束和力矩约束等约束条件，并采用遗传算法搜索最优的关节间参数，以实现最小加加速度。这些关节间参数主要包括关节角度和关节角速度。仿真结果表明，基于遗传算法的最小加加速度轨迹规划方法具有令人满意的性能和真实的工程意义。
A novel approach based on genetic algorithms (GA) is developed to find a global minimum-jerk trajectory of a space robotic manipulator in joint space. The jerk, the third derivative of position of desired joint trajectory, adversely affects the efficiency of the control algorithms and stabilization of whole space robot system and therefore should be minimized. On the other hand, the importance of minimizing the jerk is to reduce the vibrations of manipulator. In this formulation, a global genetic-approach determines the trajectory by minimizing the maximum jerk in joint space. The planning procedure is performed with respect to all constraints, such as joint angle constraints, joint velocity constraints, joint angular acceleration and torque constraints, and so on. We use an genetic algorithm to search the optimal joint inter-knot parameters in order to realize the minimum jerk. These joint inter-knot parameters mainly include joint angle and joint angular velocities. The simulation result shows that GA-based minimum-jerk trajectory planning method has satisfactory performance and real significance in engineering.