Solution for Forward Kinematics of 6-DOF Parallel Robot Based on Particle Swarm Optimization
Solution for Forward Kinematics of 6-DOF Parallel Robot Based on Particle Swarm Optimization
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DOI：
10.1109/icma.2007.4304032
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发表时间：
2007-09
期刊：
影响因子：
--
通讯作者：
Lei Li;Qidan Zhu;Liyan Xu
中科院分区：
文献类型：
--
作者：
Lei Li;Qidan Zhu;Liyan Xu
运动学正解分析是研究并联机器人其它性能的基础。利用6自由度并联机器人运动学逆解容易获得的特点，通过训练学习，利用运动学逆解结果对6自由度并联机器人的正运动学进行变换。通过位置和姿态的求解，实现了平台关节变量空间到操作变量空间的非线性映射。采用BP神经网络求解机器人的正运动学问题，并采用粒子群优化算法对神经网络进行训练。仿真结果表明，该方法可用于并联机器人的在线控制，具有更快的计算速度和更高的精度。
The analysis of the forward kinematics is the foundation for studying other performances of the parallel robot. Making use of the property that it is easy to obtain the inverse kinematics of 6-DOF parallel robot, the forward kinematics of the 6-DOF parallel robot is transformed by using inverse kinematics results through training and learning. The nonlinear mapping from the joint variable space to the operation variable space for the platform is accomplished solving the location and posture. The BP neural network is used to solve the forward kinematics, and the particle swarm optimization is applied to train the neural network. Simulation results show that this approach can be used for the online control of parallel robot with faster computing speed and more accurate solution.