Inverse Kinematics Solution of Deformable Manipulator for Point Touching Task
XU Shan1,2, LI Gaofeng1,2, LIU Jingtai1,2, HAO Jie1,2
1. Institute of Robotics and Automatic Information System, Nankai University, Tianjin 300071, China;
2. Tianjin Key Laboratory of Intelligent Robotics, Tianjin 300071, China
Abstract:For the human-robot interaction in home environment, a 4-joint deformable manipulator is designed, whose links can deform to perform specific tasks. Compared with traditional rigid ones, the deformable manipulator is more dexterous, lower-cost and intrinsically safe. However, the arbitrary arm-shape brings extra difficulties into the manipulator inverse kinematics solution. For the the spatial touching task of the deformable manipulator, the concept of "touching angle" is introduced to relax the orientation constraint of end-effector. Therefore the original inverse kinematics problem with the underactuation constraint is converted into an inverse optimization problem of redundant manipulator to minimizes the touching angle under the constraint of the touching position. For the solving time and touching accuracy of the problem, an improved sequential quadratic programming (SQP) and the particle swarm optimization and Paden-Kahan subproblems (PSO-PK) hybrid algorithm are proposed respectively based on the screw model. The SQP algorithm solves the nonlinear optimization problem directly at position level, and the results show that the time consumption won't increase as the arm-shape changes from a special one to an arbitrary one. It's suitable for online real-time control due to its high solving efficiency. The layered search method is used to decrease the possibility of local minimum through initial value setting. In the PSO-PK algorithm, the analytical inverse solution of Paden-Kahan subproblems is utilized to reduce the dimension of particle swarm optimization (PSO) algorithm. The experiment results demonstrate that the method can obtain the stable minimum touching angle without error in touching position and improve the touching performance.
[1] 周延武, 宗光华. Cleanbot-I擦窗机器人的智能化技术[J]. 机器人, 2002, 24(1):6-11.Zhou Y W, Zong G H, Intelligence technologies of Cleanbot-I glass-wall cleaning robot[J]. Robot, 2002, 24(1):6-11.
[2] Liu S, Zheng L, Wang S, et al. Cognitive abilities of indoor cleaning robots[C]//World Congress on Intelligent Control and Automation. Piscataway, USA:IEEE, 2016:1508-1513.
[3] Gao Y, Chang H J, Demiris Y. User modelling for personalized dressing assistance by humanoid robots[C]//International Conference on Intelligent Robots and Systems. Piscataway, USA:IEEE, 2015:1840-1845.
[4] 刘景泰,于宁波,许林,等.用于服务机器人的柔性操作臂:中国,ZL201310173918.1[P].2013-05-10.Liu J T, Yu N B, Xu L, et al. Flexible operating arm used for service robot:China, ZL201310173918.1[P]. 2013-05-10.
[5] Whitney D E. Resolved motion rate control of manipulators and human prostheses[J]. IEEE Transactions on Man-Machine Systems, 2007, 10(2):47-53.
[6] Liegeois B A. Automatic supervisory control of the configuration and behavior of multibody mechanisms[J]. IEEE Transactions on Systems, Man, and Cybernetics, 2007, 7(12):868-871.
[7] Chan T F, Dubey R V. A weighted least-norm solution based scheme for avoiding joint limits for redundant manipulators[C]//IEEE International Conference on Robotics and Automation. Piscataway, USA:IEEE, 1993:395-402.
[8] Beeson P, Ames B. TRAC-IK:An open-source library for improved solving of generic inverse kinematics[C]//IEEE International Conference on Humanoid Robots. Piscataway, USA:IEEE, 2015:928-935.
[9] 梶田秀司.仿人机器人[M]. 北京:清华大学出版社, 2007.Kajita S. Humanoid robot[M]. Beijing:Tsinghua University Press, 2007.
[10] Chen I M, Yang G. Inverse kinematics for modular reconfigurable robots[C]//IEEE International Conference on Robotics and Automation. Piscataway, USA:IEEE, 1998:1647-1652.
[11] Köker R, Öz C, Çakar T, et al. A study of neural network based inverse kinematics solution for a three-joint robot[J]. Robotics and Autonomous Systems, 2004, 49(3/4):227-234.
[12] Nearchou A C. Solving the inverse kinematics problem of redundant robots operating in complex environments via a modified genetic algorithm[J]. Mechanism and Machine Theory, 1998, 33(3):273-292.
[13] 任子武,朱秋国,熊蓉.冗余仿人臂避关节物理约束的一种逆运动学问题求解方法[J].机械工程学报,2014,50(19):58-65.Ren Z W, Zhu Q G, Xiong R. A joint physical constraints avoidance method for inverse kinematics problem of redundant humanoid manipulator[J]. Journal of Mechanical Engineering, 2014, 50(19):58-65.
[14] Yin F, Wang Y N, Wei S N. Inverse kinematic solution for robot manipulator based on electromagnetism-like and modified DFP algorithms[J]. Acta Automatica Sinica, 2011, 37(1):74-82.
[15] Shimizu M, Kakuya H, Yoon W K, et al. Analytical inverse kinematic computation for 7-DOF redundant manipulators with joint limits and its application to redundancy resolution[J]. IEEE Transactions on Robotics, 2008, 24(5):1131-1142.
[16] 王英石,孙雷,刘景泰.基于空间几何方法的乒乓球机器人最优姿态求取[J].机器人,2014,36(2):203-209.Wang Y S, Sun L, Liu J T. Optimal pose solution based on space geometry method for ping-pong robot[J]. Robot, 2014, 36(2):203-209.
[17] Dubey R V, Euler J A, Babcock S M. Real-time implementation of an optimization scheme for seven-degree-of-freedom redundant manipulators[J]. IEEE Transactions on Robotics and Automation, 1991, 7(5):579-588.
[18] 祖迪,吴镇炜,谈大龙.一种冗余机器人逆运动学求解的有效方法[J].机械工程学报,2005,41(6):71-75.Zu D, Wu Z W, Tan D L. Efficient inverse kinematic solution for redundant manipulators[J]. Journal of Mechanical Engineering, 2005, 41(6):71-75.
[19] 阳方平,李洪谊,王越超,等.一种求解冗余操作臂逆运动学的优化方法[J].机器人,2012,34(1):17-21,31.Yang F P, Li H Y, Wang Y C, et al. An optimization method for solving the inverse kinematics of redundant manipulator[J]. Robot, 2012, 34(1):17-21,31.
[20] Fallon M, Kuindersma S, Karumanchi S, et al. An architecture for online affordance-based perception and whole-body planning[J]. Journal of Field Robotics, 2014, 32(2):229-254.
[21] Sugihara T. Robust solution of prioritized inverse kinematics based on Hestenes-Powell multiplier method[C]//IEEE/RSJ International Conference on Intelligent Robots and Systems. Piscataway, USA:IEEE, 2014:510-515.
[22] Starke S, Hendrich N, Magg S, et al. An efficient hybridization of genetic algorithms and particle swarm optimization for inverse kinematics[C]//IEEE International Conference on Robotics and Biomimetics. Piscataway, USA:IEEE, 2016:1782-1789.
[23] Coello C A C, Pulido G T, Lechuga M S. Handling multiple objectives with particle swarm optimization[J]. IEEE Transactions on Evolutionary Computation, 2004, 8(3):256-279.
[24] Kennedy J, Eberhart R. Particle swarm optimization[C]//IEEE International Conference on Neural Networks. Piscataway,USA:IEEE, 1995:1942-1948.
[25] Murray R M, Li Z X, Sastry S S. A mathematical introduction to robotic manipulation[M]. Boca Raton, USA:CRC Press, 1994.
[26] Chen W, Chen I M, Lim W K, et al. Cartesian coordinate control for redundant modular robots[C]//IEEE International Conference on Systems, Man, and Cybernetics. Piscataway, USA:IEEE, 2000:3253-3258.
[27] 杨明明,陈伟海,于守谦,等.基于Paden-Kahan子问题的冗余度机器人运动学求解[J].机器人,2004,26(3):250-255.Yang M M, Chen W H, Yu S Q, et al. Kinematic solutions for redundant robot based on Paden-Kahan subproblems[J]. Robot, 2004, 26(3):250-255.
[28] Lu X, Liu J, Hao J, et al. Self-calibration of deformable arm with a monocular camera[C]//IEEE International Conference on Robotics and Biomimetics. Piscataway, USA:IEEE, 2014:861-866.
[29] Li G, Sun L, Lu X, et al. A practical, fast, and low-cost kinematic calibration scheme for a deformable manipulator by using leap motion[C]//IEEE International Conference on Robotics and Biomimetics. Piscataway, USA:IEEE, 2016:719-724.
[30] 赵瑞安.非线性最优化理论和方法[M].杭州:浙江科学技术出版社,1992.Zhao R A. Theory and methods for nonlinear optimization[M]. Hangzhou:Zhejiang Publishing House of Science and Technology, 1992.