| 刘伟,马利强,马彪,陈雪辉,黄磊,李昊.机器人无迹微分动态规划算法研究[J].安徽建筑大学学报,2021,29(): |
| 机器人无迹微分动态规划算法研究 |
| Research on unscented Kalman dynamic programming algorithm of robot |
| 投稿时间：2020-10-26 修订日期：2021-05-25 |
| DOI： |
| 中文关键词: 关键词：轨迹规划 无迹微分动态规划 仿真对比 二阶收敛 时间缩短 |
| 英文关键词: Keywords: trajectory planning trackless differential dynamic programming simulation second order convergence Reduce time |
| 基金项目:安徽建筑大学引进人才及博士启动基金项目(2018QD16)；安徽省高校协同创新项目(GXXT-2019-036) |
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| 中文摘要: |
| 摘 要：针对机器人非线性系统轨迹规划中微分动态规划算法由于动力学导数计算导致的实时性差与梯度下降慢问题，采用微分动态规划算法与无迹卡尔曼思想相结合的方式，以采样与差分方式代替动力学导数计算，建立无迹微分动态规划算法。将无迹微分动态规划与微分动态规划在非线性的倒立摆模型上进行模拟仿真对比。实验结果表明，系统参数相同时，无迹微分动态规划算法在保证良好的二阶收敛性和相同控制效果的前提下，既能减少迭代次数，又对成本压缩更敏感，且梯度下降更快，从而整体的运行时间缩短。 |
| 英文摘要: |
| Abstract: In order to solve the problems of poor real-time performance and slow gradient descent of differential dynamic programming algorithm due to the calculation of dynamic derivative in robot nonlinear system trajectory planning, the method of combining differential dynamic programming algorithm with unscented Kalman thought is adopted, and the dynamic derivative calculation is replaced by sampling and difference method. The traceless differential dynamic programming and differential dynamic programming are compared on the nonlinear inverted pendulum model. The experimental results show that when the system parameters are the same, the traceless differential dynamic programming algorithm can not only reduce the number of iterations, but also be more sensitive to cost compression, and the gradient descent is faster, so the overall running time is shortened. |
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