Faculty of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, Shaanxi, China.
PLoS One. 2020 Apr 3;15(4):e0230790. doi: 10.1371/journal.pone.0230790. eCollection 2020.
This paper studies the inverse kinematics of two non-spherical wrist configurations of painting robot. The simplest analytical solution of orthogonal wrist configuration is deduced in this paper for the first time. For the oblique wrist configuration, there is no analytical solution for the configuration. So it is necessary to solve by general method, which cannot achieve high precision and high speed as analytic solution. Two general methods are optimized in this paper. Firstly, the elimination method is optimized to reduce the solving speed to 20% of the original one, and the completeness of the method is supplemented. Based on the Gauss damped least squares method, a new optimization method is proposed to improve the solving speed. The enhanced step length coefficient is introduced to conduct studies with the machine learning correlation method. It has been proved that, on the basis of ensuring the stability of motion, the number of iterations can be effectively reduced and the average number of iterations can be less than 5 times, which can effectively improve the speed of solution. In the simulation and experimental environment, it is verified.
本文研究了两种非球形手腕配置的绘画机器人逆运动学。本文首次推导出了正交手腕配置的最简单解析解。对于斜手腕配置，没有解析解。因此，有必要采用一般方法来求解，这无法达到解析解的高精度和高速。本文对两种通用方法进行了优化。首先，优化消元法，将求解速度降低到原来的 20%，并补充方法的完整性。基于高斯阻尼最小二乘法，提出了一种新的优化方法来提高求解速度。引入增强步长系数，通过机器学习相关方法进行研究。已经证明，在保证运动稳定性的基础上，可以有效地减少迭代次数，平均迭代次数可以小于 5 次，从而可以有效地提高求解速度。在模拟和实验环境中进行了验证。
