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Tri-Criteria Optimization Motion Planning at Acceleration-Level of Dual Redundant Manipulators

Published online by Cambridge University Press:  23 July 2019

Zhaoli Jia
Affiliation:
College of Engineering, South China Agricultural University, Guangzhou510642, China. E-mails: jiazhaoli0810@163.com, ouyangfan@scau.edu.cn Research and Development Center, Guang Dong Siwun Logistics Equipment Co., Ltd, Guangzhou510507, China
Siyuan Chen
Affiliation:
School of Automation Science and Engineering, South China University of Technology (SCUT), Guangzhou510641, China. E-mails: c.sy05@mail.scut.edu.cn, 915887584@qq.com
Zhijun Zhang*
Affiliation:
School of Automation Science and Engineering, South China University of Technology (SCUT), Guangzhou510641, China. E-mails: c.sy05@mail.scut.edu.cn, 915887584@qq.com
Nan Zhong*
Affiliation:
College of Engineering, South China Agricultural University, Guangzhou510642, China. E-mails: jiazhaoli0810@163.com, ouyangfan@scau.edu.cn
Pengchao Zhang
Affiliation:
Key Laboratory of Industrial Automation of Shaanxi Province, Shaanxi University of Technology, Hanzhong, Shaanxi723000, China. E-mail: snutzpc@126.com
Xilong Qu
Affiliation:
School of Information Technology and Management, Hunan University of Finance and Economics, Changsha, Hunan410205, China. E-mail: quxilong@126.com
Jinhua Xie
Affiliation:
School of Automation Science and Engineering, South China University of Technology (SCUT), Guangzhou510641, China. E-mails: c.sy05@mail.scut.edu.cn, 915887584@qq.com
Fan Ouyang
Affiliation:
College of Engineering, South China Agricultural University, Guangzhou510642, China. E-mails: jiazhaoli0810@163.com, ouyangfan@scau.edu.cn
*
*Corresponding author. E-mails: auzjzhang@scut.edu.cn, zhongnan@scau.edu.cn
*Corresponding author. E-mails: auzjzhang@scut.edu.cn, zhongnan@scau.edu.cn

Summary

In order to solve joint-angle drift problem of dual redundant manipulators at acceleration-level, an acceleration-level tri-criteria optimization motion planning (ALTC-OMP) scheme is proposed, which combines the minimum acceleration norm, repetitive motion planning, and infinity-norm acceleration minimization solutions via weighting factor. This scheme can resolve the joint-angle drift problem of dual redundant manipulators which will arise in single criteria or bi-criteria scheme. In addition, the proposed scheme considers joint-velocity joint-acceleration physical limits. The proposed scheme can not only guarantee joint-velocity and joint-acceleration within their physical limits, but also ensure that final joint-velocity and joint-acceleration are near to zero. This scheme is realized by dual redundant manipulators which consist of left and right manipulators. In order to ensure the coordinated operation of manipulators, two motion planning problems are reformulated as two general quadratic program (QP) problems and further unified into one standard QP problem, which is solved by a simplified linear-variational-inequalities-based primal-dual neural network at the acceleration-level. Computer-simulation results based on dual PUMA560 redundant manipulators further demonstrate the effectiveness and feasibility of the proposed ALTC-OMP scheme to resolve joint-angle drift problem arising in the dual redundant manipulators.

Type
Articles
Copyright
© Cambridge University Press 2019

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References

Canali, C, Rahman, N, Chen, F, D’Imperio, M, Caldwell, D and Cannella, F, “Theoretical and kinematic solution of high reconfigurable grasping for industrial manufacturing,” Procedia Manuf. 11, 265274 (2017).CrossRefGoogle Scholar
Ul Islam, R, Iqbal, J, Manzoor, S, Khalid, A and Khan, S, “An Autonomous Image-Guided Robotic System Simulating Industrial Applications,” International Conference on System of Systems Engineering, Genoa, Italy (2013) pp. 344349.Google Scholar
Mustafa, W, Pugeault, N, Buch, A.G. and Krüger, N, “Multi-view object instance recognition in an industrial context,” Robotica 35(2), 271292 (2017).CrossRefGoogle Scholar
Yang, Y, Chen, H, Lou, Y and Lin, W, “Remote Master-Slave Control of a 6D Manipulator for Cardiac Surgery Application,” IEEE International Conference on Robotics and Biomimetics, Bali, Indonesia (2015) pp. 17991804.Google Scholar
Wang, J, Yao, Y and Kong, X, “A reconfigurable tri-prism mobile robot with eight modes,” Robotica, 36(10), 14541476 (2018).CrossRefGoogle Scholar
Mazzini, F and Dubowsky, S, “An experimental validation of robotic tactile mapping in harsh environments such as deep sea oil well sites,” Springer Tracts Adv. Robot. 79, 557570 (2014).CrossRefGoogle Scholar
Zheng, T, Branson, D. T., Guglielmino, E, Kang, R, Cerda, G. A. M., Cianchetti, M, Follador, M, Godage, I. S. and Caldwell, D. G., “Model validation of an octopus inspired continuum robotic arm for use in underwater environments,” J. Mech. Robot. 5(2), 021004 (2013).CrossRefGoogle Scholar
La, H. M., “Automated robotic monitoring and inspection of steel structures and bridges,” Robotica. 37(5), 947967 (2018).CrossRefGoogle Scholar
Madhava Krishna, K, Alami, R and Simeon, T, “Safe proactive plans and their execution,” Robot. Auton. Syst. 54(3), 244255 (2006).CrossRefGoogle Scholar
Farzanehkaloorazi, M. H., Masouleh, M. T. and Caro, S, “Collision-free workspace of parallel mechanisms based on an interval analysis approach,” Robotica 35(8), 17471760 (2018).CrossRefGoogle Scholar
Khanpoor, A, Khalaji, A. K. and Moosavian, S. A. A., “Modeling and control of an underactuated tractortrailer wheeled mobile robot,” Robotica 35(12), 22972318 (2017).CrossRefGoogle Scholar
Xu, Q and Sun, X, “Adaptive Operation-Space Control of Redundant Manipulators with Joint Limits Avoidance,” Tenth International Conference on Advanced Computational Intelligence, Xiamen, China (2018) pp. 358363.Google Scholar
Meng, H, Lin, M, Li, S, Chen, Z and Rong, D, “A Multi-Strategy Path Planner Based on Space Accessibility.”IEEE International Conference on Robotics and Biomimetics, Macau SAR, China (2018) pp. 21542161.Google Scholar
Ferrús, R. M. and Somonte, M. D., “Design in robotics based in the voice of the customer of household robots,” Robot. Auton. Syst. 79, 99107 (2016).CrossRefGoogle Scholar
Singh, A. K. and Madhava Krishna, K, “Feasible acceleration count: A novel dynamic stability metric and its use in incremental motion planning on uneven terrain,” Robot. Auton. Syst. 79, 156171 (2016).CrossRefGoogle Scholar
Yahya, S, Moghavvemi, M and Mohamed, H. A. F., “Manipulability Constraint Locus for a Six Degrees of Freedom Redundant Planar Manipulator,” International Symposium on Computer, Consumer and Control, Taichung, Taiwan (2012) pp. 290293.Google Scholar
Ge, X and Jin, J, “Dynamics Analyze of a Dual-Arm Space Robot System Based on Kane’s Method,” International Conference on Industrial Mechatronics and Automation, Wuhan, China (2010) pp. 646649.Google Scholar
Yazdani, M, Novin, R. S., Masouleh, M. T. and Menhaj, M. B., “An Experimental Study on the Failure Tolerant Control of a Redundant Planar Serial Manipulator via Pseudo-Inverse Approach,” RSI International Conference on Robotics and Mechatronics, Tehran, Iran (2015) pp. 365370.Google Scholar
Cai, B and Zhang, Y, “Different-level redundancy-resolution and its equivalent relationship analysis for robot manipulators using gradient-descent and Zhang’s neural-dynamic methods,” IEEE Trans. Ind. Electron. 59(8), 31463155 (2012).CrossRefGoogle Scholar
Guo, D, Yan, X, Jin, L and Tan, H, “Ze in iZ1eD1 Manner for MKE Redundancy Resolution at Velocity and Acceleration levels,” International Conference on Systems and Informatics, Shanghai, China (2014) pp. 4550.Google Scholar
Cheng, F. T., Chen, T. H. and Sun, Y. Y., “Resolving manipulator redundancy under inequality constraints,” IEEE Trans. Robot. Automat. 10(1), 6571 (1994).CrossRefGoogle Scholar
Chen, K, Guo, D, Tan, Z, Yang, Z and Zhang, Y, “Cyclic Motion Planning of Redundant Robot Arms: Simple Extension of Performance Index may not Work,” The Workshop on Intelligent Information Technology Applications, NanChang, China (2009) pp. 635639.Google Scholar
Zhang, Y and Guo, D, “Linear programming versus quadratic programming in robots’ repetitive redundancy resolution: A chattering phenomenon investigation,” IEEE Conference on Industrial Electronics and Applications, ICIEA 2009, Xi’an, China (2009) pp. 28222827.Google Scholar
Xu, W, Liu, T and Li, Y, “Kinematics, dynamics, and control of a cable-driven hyper-redundant manipulator,” IEEE/ASME Trans. Mechatron. 23(4), 16931704 (2018).CrossRefGoogle Scholar
Pedrammehr, S, Danaei, B, Abdi, H, Masouleh, M. T. and Nahavandi, S, “Dynamic analysis of hexarot: Axis-symmetric parallel manipulator,” Robotica 36(2), 225240 (2018).CrossRefGoogle Scholar
Choi, H. B., Lee, S and Lee, J, “Minimum infinity-norm joint velocity solutions for singularity-robust inverse kinematics,” Int. J. Precis. Eng. Manufact. 12(3), 469474 (2011).CrossRefGoogle Scholar
Zhang, Y and Li, K, “Bi-criteria velocity minimization of robot manipulators using LVI-based primal-dual neural network and illustrated via puma560 robot arm,” Robotica 28(4), 525537 (2010).CrossRefGoogle Scholar
Guo, D and Zhang, Y, “Acceleration-level inequality-based man scheme for obstacle avoidance of redundant robot manipulators,” IEEE Trans. Indus. Electron. 61(12), 69036914 (2014).CrossRefGoogle Scholar
Zhang, Y, Yin, J and Cai, B, “Infinity-norm acceleration minimization of robotic redundant manipulators using the LVI-based primal–dual neural network,” Robot. Comput. Integr. Manufact. 25(2), 358365 (2009).CrossRefGoogle Scholar
Wimbock, T and Ott, C, “Dual-arm manipulation,” Springer Tracts Adv. Robot. 76(10), 353366 (2012).CrossRefGoogle Scholar
Zhang, Y, Cai, B, Zhang, L and Li, K, “Bi-criteria velocity minimization of robot manipulators using a linear variational inequalities-based primal-dual neural network and puma560 example,” Adv. Robot. 22(13–14), 14791496 (2008).CrossRefGoogle Scholar
Guo, D and Zhang, Y, “Different-level two-norm and infinity-norm minimization to remedy joint-torque instability/divergence for redundant robot manipulators,” Robot. Auton. Syst. 60(6), 874888 (2012).CrossRefGoogle Scholar
Liu, S and Wang, J, “A Dual Neural Network for Bi-Criteria Torque Optimization of Redundant Robot Manipulators,” In: Lecture Notes in Computer Science, vol. 3316 (2004) pp. 11421147.CrossRefGoogle Scholar
Liu, S and Wang, J, “Bi-Criteria Torque Optimization of Redundant Manipulators Based on a Simplified Dual Neural Network,” IEEE International Joint Conference on Neural Networks, IJCNN ’05 Proceedings, Montreal, Quebec, Canada, vol. 5 (2005) pp. 27962801.Google Scholar
Liao, B and Liu, W, “Pseudoinverse-type bi-criteria minimization scheme for redundancy resolution of robot manipulators,” Robotica 33(10), 21002113 (2015).CrossRefGoogle Scholar
Wells, T. S., Maclachlan, R. A. and Riviere, C. N., “Toward Hybrid Position/Force Control for an Active Handheld Micromanipulator,” IEEE International Conference on Robotics and Automation, Hong Kong, China (2014) pp. 772777.Google Scholar
Tsuji, T, Ohkuma, J and Sakaino, S, “Dynamic object manipulation considering contact condition of robot with tool,” IEEE Trans. Ind. Electron. 63(3), 19721980 (2016).CrossRefGoogle Scholar
Nicolis, D, Zanchettin, A. M. and Rocco, P, “Constraint-based and sensorless force control with an application to a lightweight dual-arm robot,” IEEE Robot. Automat. Lett. 1(1), 340347 (2016).CrossRefGoogle Scholar
Khansari, M, Kronander, K and Billard, A, “Modeling Robot Discrete Movements with State-Varying Stiffness and Damping: A Framework for IntegratedMotion Generation and Impedance Control,” Robotics: Science and Systems, Berkeley, California (2014).Google Scholar
Li, L. I. H., Wang, D., Yang, D, Zhang, G and Tiejun, L. I., “Research for dual-arm robot coordinated handling methods based on impedance control,” Mach. Tool Hydraul. 45(21), 6497 (2017).Google Scholar
Zhang, Z and Zhang, Y, “Variable joint-velocity limits of redundant robot manipulators handled by quadratic programming,” IEEE/ASME Trans. Mechatron. 18(2), 674686 (2013).CrossRefGoogle Scholar
Asfour, T, Azad, P, Gyarfas, F and Dillmann, R, “Imitation learning of dual-arm manipulation tasks in humanoid robots,” Int. J. Human. Robot. 5(02), 183202 (2006).CrossRefGoogle Scholar
Tsai, Y. C. and Huang, H. P., “Motion Planning of a Dual-Arm Mobile Robot in the Configuration-Time Space, IEEE RSJ International Conference on Intelligent Robots and Systems, St. Louis, USA (2009) pp. 24582463.Google Scholar
Cohen, B, Chitta, S and Likhachev, M, “Search-Based Planning for Dual-Arm Manipulation with Upright Orientation Constraints,” IEEE International Conference on Robotics and Automation, St. Paul, Minnesota, USA (2012) pp. 37843790.Google Scholar
Peng, S, Ding, X, Fan, Y and Xu, K, “Motion planning and implementation for the self-recovery of an overturned multi-legged robot,” Robotica 35(5), 11071120 (2017).CrossRefGoogle Scholar
Wang, M, Luo, J, Yuan, J and Walter, U, “Coordinated trajectory planning of dual-arm space robot using constrained particle swarm optimization,” Acta Astronaut. 146, 259272 (2018).CrossRefGoogle Scholar
Huang, Z, Chu, D, Wu, C and Yi, He, “Path planning and cooperative control for automated vehicle platoon using hybrid automata,” IEEE Trans. Intell. Transport. Syst. 20(3), 116 (2018).Google Scholar
Zhang, Y, Cai, B, Zhang, L and Li, K, “Bi-criteria velocity minimization of robot manipulators using a linear variational inequalities-based primal-dual neural network and puma560 example,” Adv. Robot. 22(13–14), 14791496 (2008).CrossRefGoogle Scholar
Zhang, Y, Wang, Y, Guo, D, Yu, X and Xiao, L, “Simultaneous repetitive motion planning of two redundant robot arms for acceleration-level cooperative manipulation,” Phys. Lett. Sect. A: Gen. Atom. Solid State Phys. 377(34–36), 19791983 (2013).CrossRefGoogle Scholar
Zhang, Z and Zhang, Y, “Acceleration-level cyclic-motion generation of constrained redundant robots tracking different paths,” IEEE Trans. Syst. Man Cybern. Part B (Cybern.) 42(4), 12571269 (2012).CrossRefGoogle Scholar
Zhang, Y, Tan, Z, Chen, K, Yang, Z and Lv, X, “Repetitive motion of redundant robots planned by three kinds of recurrent neural networks and illustrated with a four-link planar manipulators straight-line example,” Robot. Auton. Syst. 57(6), 645651 (2009).CrossRefGoogle Scholar
Ge, S. S., Zhang, Y and Tong, H. L., “An Acceleration-BasedWeighting Scheme for Minimum-Effort Inverse Kinematics of Redundant manipulators, IEEE International Symposium on Intelligent Control (2004) pp. 275280.Google Scholar
Zhang, Y, “On the LVI-Based Primal–Dual Neural Network for Solving Online Linear and Quadratic Programming Problems, American Control Conference, Portland, OR, USA, vol. 2 (2005) pp. 13511356.Google Scholar
Zhang, Y, Li, Z, Tan, H. Z. and Fan, Z, “On the Simplified LVI-Based Primal–Dual Neural Network for Solving LP and QP Problems,” IEEE International Conference on Control and Automation, Guangzhou, China (2007) pp. 31293134.Google Scholar
Zhang, Z, Zheng, L, Yu, J, Li, Y and Yu, Z, “Three recurrent neural networks and three numerical methods for solving a repetitive motion planning scheme of redundant robot manipulators,” IEEE/ASME Trans. Mechatron. 22(3), 14231434 (2017).CrossRefGoogle Scholar