论文部分内容阅读
针对Stewart平台运动学正解映射关系的复杂性,引入极端学习机算法进行运动学正解研究.分别建立Stewart上、下平台的动坐标系和参考坐标系,并利用运动学反解产生极端学习机的的样本数据,确立对应于并联机器人6个自由度的极端学习机网络模型,运用matlab进行仿真实验.仿真结果表明,极端学习机求解并联机器人的运动学正解快速有效,且具有良好的模型辨识能力,为求运动学正解提供了新方法.“,”For the complexity of Stewart platform kinematics mapping, the extreme learning machine algorithm is introduced into the research of the forward kinematics. The moving coordinate system and reference coordinate system are established separately for the upper platform and lower platform of Stewart, and the sample data of extreme learning machine is generated by the inverse kinematics. The network model of extreme learning machine corresponding to the six degrees of freedom of the parallel robot is established, a simulation experiment is carried out by MATLAB. The simulation results show that the extreme learning machine is fast and effective to solve the kinematics of the parallel robot and it has a good ability to systematic identification. This proposed algorithm provides a new method for solving the forward kinematics solution problem.