3维细长管路测量系统扫描路径自主规划

doi:10.13973/j.cnki.robot.190006

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庄金雷, 李瑞峰, 曹雏清, 高云峰, 陈盟. 3维细长管路测量系统扫描路径自主规划[J]. 机器人, 2019, 41(5): 628-636.DOI: 10.13973/j.cnki.robot.190006. ZHUANG Jinlei, LI Ruifeng, CAO Chuqing, GAO Yunfeng, CHEN Meng. Autonomous Scan Path Planning of Measurement System for 3D Long and Thin Tube. ROBOT, 2019, 41(5): 628-636. DOI: 10.13973/j.cnki.robot.190006.

摘要针对弯折加工而成的3维细长管路的测量问题，设计了一种由工业机器人和多种传感器组成的自主测量系统．为完成测量中关键的管路点云自主扫描，提出了一种基于遗传算法的管路扫描路径规划算法，可求取出能够完整扫描管路且扫描次数尽可能少的1组无碰关键扫描点，并且在关键扫描点处机器人的姿态被约束在竖直方向周围的一定范围内．此外，在每代群体产生后根据向前覆盖因子更新探索步长，并据此调整新采样个体的采样区间用以快速采集到更合适的个体．路径规划算法的性能验证中，首先实施了弯曲管路仿真，然后进行了圆柱段和圆环段在不同姿态下的扫描路径规划的仿真，最后开展了汽车管路扫描路径规划的仿真和实测实验．仿真结果中最优个体扫描长度随迭代次数增加而增大，且两种管路段和汽车管路的扫描覆盖率均超过0.99，表明规划得到的关键扫描点数量少，且关键扫描点的扫描体可近乎完整地扫描对应管路．汽车管路仿真与实测实验结果表明该算法对复杂管路可规划出合适的扫描路径．

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关键词 ：管路重构, 自主测量, 扫描路径规划, 遗传算法, 3维点云

Abstract：For the measurement problem of the 3D long and thin bent tube, an autonomous measurement system consisting of the industrial robot and multiple sensors is presented. An optimized scan path planning algorithm is proposed based on genetic algorithm, to autonomously scan the point cloud of the tube (as a crucial part of the measurement). With the algorithm a collision free scan path is acquired, satisfying that all the segments of the tube can be scanned, and the scan times are as small as possible. And the robot pose at each key scan point is restricted in a certain range around the vertical direction. Moreover, the searching step is updated based on the forward cover coefficient after the generation of each population, and the sampling interval of the new sample individual is also adjusted for quick acquisition of better individuals. In the part of the performance verification of the scan path planning algorithm, the simulation on a bent tube is implemented firstly. Then the scan path planning simulations of cylinder segment and toroidal segment, which are placed with different pose, are conducted. Finally, the simulation and the practical experiment of the scan path planning of a practical car tube are carried out. As the simulation results, the scan length of the best individual increases with the number of iterations, and the coverage ratios of the two kinds of tube segments and the car tube are all above 0.99. The results demonstrate that the number of the planned key scan points is small and the scan volumes of the key scan points can almost scan the tube completely. Simulation and practical experiment results indicate that the algorithm can obtain a suitable scan path for complex tubes.

Key words： tube reconstruction autonomous measurement scan path planning genetic algorithm 3D point cloud

收稿日期: 2019-01-02 录用日期: 2019-05-16

TP241.2

基金资助:国家自然科学基金（61673136）；机器人技术与系统国家重点实验室（哈尔滨工业大学）自主研究课题（SKLRS201609B）

通讯作者: 庄金雷,16B308005@hit.edu.cn E-mail: 16B308005@hit.edu.cn

作者简介: 庄金雷(1989-),男,博士生.研究领域:机器人路径规划,机器人标定,图像处理.
李瑞峰(1965-),男,教授,博士生导师.研究领域:工业机器人设计,机器人自主导航,3维重构,图像处理.
曹雏清(1983-),男,博士.研究领域:图像处理,机器人控制.

链接本文:

https://robot.sia.cn/CN/10.13973/j.cnki.robot.190006 或 https://robot.sia.cn/CN/Y2019/V41/I5/628

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