China Mechanical Engineering ›› 2021, Vol. 32 ›› Issue (16): 1963-1971.

### Research and Implementation of Trajectory Planning Algorithm for Attacking Robots on Wind Tunnel

SUN Xiaojun1;SONG Daiping1;LIN Jingzhou2;HAN Weihang3

1. 1.State Key Laboratory of Mechanical Transmissions,Chongqing University,Chongqing，400044
2.Hypervelocity Aerodynamics Institute,China Aerodynamics Research and Development Center,Mianyang，Sichuan,621000
3.School of Information and Control Engineering,Liaoning Shihua University,Fushun,Liaoning,113001
• Online:2021-08-25 Published:2021-09-10

### 风洞上攻角机器人轨迹规划算法研究与实现

1. 1.重庆大学机械传动国家重点实验室,重庆,400044
2.中国空气动力学研究与发展中心超高速空气动力研究所,绵阳，621000
3. 辽宁石油化工大学信息与控制工程学院, 抚顺，113001
• 通讯作者: 宋代平（通信作者），男，1978年生，副教授。研究方向为智能制造及装备、现代机械设计理论与方法、机器人技术。获中国机械工业科学技术奖一等奖。E-mail:songdp@cqu.edu.cn。
• 作者简介:孙晓军，男，1993年生，硕士研究生。研究方向为机器人轨迹规划与运动控制。
• 基金资助:
国家重点研发计划（2018YFC0808004）

Abstract:  In order to increase the speeds of the robot arms tracking the target trajectory, the target trajectory of the robots was re-planned. By introducing path parameters, constraints such as joint velocity and force/moment were transformed into constraints on trajectory parameters in the trajectory planning algorithm. The maximum velocity curves of path parameters under joint velocity and force/moment constraints were obtained respectively. The maximum velocity curves with multiple constraints were obtained by calculating the intersection of the above maximum velocity curves. In order to improve the computational efficiency of the algorithm, the fuzzy inference method was used to discretize the target trajectory to reduce the optimization scales, and the maximum velocity curves of the joint force/torque constraint were replaced by the velocity curves of the zero value acceleration curves multiplied by the proportional coefficient. The planned trajectory was modified through the speed feature point algorithm and the modification-target algorithm to ensure that the modified target trajectory meets the constraints of joint speed and force/torque, and the velocity curve is smooth. The trajectory planning experimental results shows that the trajectory planning algorithm have better planning performance for target trajectories of different complexity, and may obtain continuous and smooth time approximate optimal trajectories.

CLC Number: