A Method of Autonomous Assembly of Large Spacecraft Components Using Robot
MENG Shaohua1,2, HU Ruiqin1,2, ZHANG Lijian1,2, DONG Que1,2
1. Beijing Institute of Spacecraft Environment Engineering, Beijing 100094, China;
2. Beijing Engineering Research Center of the Intelligent Assembly Technology and Equipment for Aerospace Product, Beijing 100094, China
Abstract：When the large components of a spacecraft are installed in a narrow space, there are some problems such as a limited visual field and an invisible target position. The traditional hoisting approach can't accurately adjust the position and attitude of the component, and is prone to cause collision. A path planning method for robot assisted assembly using binocular vision localization is proposed. The binocular vision system is employed to precisely localize the geometric features of installation positions on the spacecraft, based on the 3D model of assembly elements such as the spacecraft, components to be installed and the robot. The relative position and attitude relationship between the robot and the spacecraft can be computed using the measured results, so as to construct the virtual environment of the spacecraft assembly scenes. In the virtual environment, geometric constraints in the assembly process are recognized and a collision detection is implemented using the axis-aligned bounding box (AABB) method. After that, the probabilistic roadmap method is adopted to generate a collision-free path, and then executable assembly sequences for robot are produced through off-line programming. An assembly experiment is carried out for a laser altimeter instrument of a spacecraft. The installation of the large component is completed in a narrow concave cabin without collision. Results show that the proposed method can localize the precise position of thread holes, rapidly generate a collision-free assembly path, and control the robot to safely and efficiently accomplish large component installations in the narrow space of a spacecraft.
 谭维炽,胡金刚.航天器系统工程[M].北京:中国科学技术出版社,2009.Tan W Z, Hu J G. Spacecraft systems engineering[M]. Beijing:China Science and Technology Press, 2009.
 张立建,胡瑞钦,易旺民.基于六维力传感器的工业机器人末端负载受力感知研究[J].自动化学报,2017,43(3):427-435.Zhang L J, Hu R Q, Yi W M. Research on force sensing for the load at the end of industrial robot based on a 6-axis force/torque sensor[J]. Acta Automatica Sinica, 2017, 43(3):427-435.
 Bauer W, Bender M, Rally P, et al. Lightweight robots and human interaction in assembly systems[M]//Advances in Ergonomics of Manufacturing:Managing the Enterprise of the Future. Berlin, Germany:Springer-Verlag, 2016:113-122.
 夏群峰,彭勇刚.基于视觉的机器人抓取系统应用研究综述[J].机电工程,2014,31(6):697-710.Xia Q F, Peng Y G. Review on application research of robots scraping system based on visual[J]. Journal of Mechanical & Electrical Engineering, 2014, 31(6):697-710.
 Chang W C, Shao C K. Hybrid fuzzy control of an eye-to-hand robotic manipulator for autonomous assembly tasks[C]//49th Annual Conference of the Society of Instrument and Control Engineers of Japan. Piscataway, USA:IEEE, 2010:408-414.
 Xu F, Wang S, Li B Y. Industrial robot base assembly based on improved Hough transform of circle detection algorithm[C]//11th World Conference on Intelligent Control and Automation. Piscataway, USA:IEEE, 2014:2446-2450.
 朱大奇,颜明重.移动机器人路径规划技术综述[J].控制与决策,2010,25(7):961-967.Zhu D Q, Yan M Z. Survey on technology of mobile robot path planning[J]. Control and Decision, 2010, 25(7):961-967.
 高云峰,黄海.复杂环境下基于势场原理的路径规划方法[J].机器人,2004,26(2):114-118.Gao Y F, Huang H. A path planning algorithm based on potential field for complex environment[J]. Robot, 2004, 26(2):114-118.
 李天成,孙树栋,高扬.基于扇形栅格地图的移动机器人全局路径规划[J].机器人,2010,32(4):547-552.Li T C, Sun S D, Gao Y. Fan-shaped grid based global path planning for mobile robot[J]. Robot, 2010, 32(4):547-552.
 Gomez-Bravo F, Carbone G, Fortes J C. Collision free trajectory planning for hybrid manipulators[J]. Mechatronics, 2012, 22(6):836-851.
 刘传领.基于势场法和遗传算法的机器人路径规划技术研究[D].南京:南京理工大学, 2012. Liu C L. Researches on technologies for robot path planning based on artificial potential field and genetic algorithm[D]. Nanjing:Nanjing University of Science & Technology, 2012.
 祁若龙,周维佳,王铁军.一种基于遗传算法的空间机械臂避障轨迹规划方法[J].机器人, 2014, 36(3):263-270. Qi R L, Zhou W J, Wang T J. An obstacle avoidance trajectory planning scheme for space manipulators based on genetic algorithm[J]. Robot, 2014, 36(3):263-270.
 Kavrkil E, Latombe J C, Overmars M. Probabilistic roadmap for path planning in high-dimensional configuration spaces[J]. IEEE Transactions on Robotics and Automation, 1996, 12(4):566-580.
 谭民.先进机器人控制[M].北京:高等教育出版社, 2007. Tan M. Advanced robot control[M]. Beijing:Higher Education Press, 2007.
 王晓荣.基于AABB包围盒的碰撞检测算法的研究[D]. 武汉:华中师范大学, 2007. Wang X R. Research on collision detection algorithm based on AABB bounding volume[D]. Wuhan:Central China Normal University, 2007.