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A Hybrid Obstacle-Avoidance Method of Spatial Hyper-Redundant Manipulators for Servicing in Confined Space

Published online by Cambridge University Press:  14 January 2019

Zonggao Mu ,
Tianliang Liu ,
Wenfu Xu ,
Yunjiang Lou  and
Bin Liang
Zonggao Mu
Affiliation:
The School of Mechanical Engineering and Automation, Harbin Institute of Technology, Shenzhen 518055, China E-mails: [email protected], [email protected], [email protected]
Tianliang Liu
Affiliation:
The School of Mechanical Engineering and Automation, Harbin Institute of Technology, Shenzhen 518055, China E-mails: [email protected], [email protected], [email protected]
Wenfu Xu*
Affiliation:
The School of Mechanical Engineering and Automation, Harbin Institute of Technology, Shenzhen 518055, China E-mails: [email protected], [email protected], [email protected]
Yunjiang Lou
Affiliation:
The School of Mechanical Engineering and Automation, Harbin Institute of Technology, Shenzhen 518055, China E-mails: [email protected], [email protected], [email protected]
Bin Liang
Affiliation:
Department of Automation, School of Information Science and Technology, Tsinghua University, Beijing 100084, China E-mail: [email protected]
*
*Corresponding author. E-mail: [email protected]
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Summary

Due to a large number of redundant degrees of freedom (DOFs), the hyper-redundant manipulator shows outstanding dexterity and adaptability in avoiding the obstacles in confined space. In this paper, a hybrid obstacle-avoidance method of spatial hyper-redundant manipulators is proposed, with both efficiency and accuracy considered. The space around an obstacle is classified into safe, warning, and dangerous zones. A two-level protection strategy is then addressed to handle the obstacle-avoidance problem from qualitative (i.e., pseudo-distance based on super-quadric function) and quantitative (i.e., Euclidean distance based on practical geometry function) perspectives, respectively. The only condition for switching between the two-level protections is the value of pseudo-distance. Then, a modified modal method, which is a trajectory planning method, is presented to plan the collision-free trajectory of the manipulator by maximizing the minimum pseudo-distance or Euclidean distance in different zones. Some parameters, including the arm-angle parameters and the equivalent link length parameters, are defined to represent the manipulator configuration. They are adjusted to avoid the obstacle, singularity, and joint limit. The simulations of 12-DOF manipulator and an experiment of 18-DOF manipulator verify the proposed methods.

Keywords

Hyper-redundant manipulatorSpace manipulatorObstacle avoidanceModified modal methodConfined space
Type
Articles
Information
Robotica , Volume 37 , Issue 6 , June 2019 , pp. 998 - 1019
Copyright
Copyright © Cambridge University Press 2019 

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References

Huang, P., Zhang, F., Meng, Z. and Liu, Z., “Adaptive control for space debris removal with uncertain kinematics, dynamics and states,” Acta Astronaut. 128, 416–430 (2016).CrossRefGoogle Scholar
Huang, P., Liu, B. and Zhang, F., “Configuration maintaining control of three-body ring tethered system based on thrust compensation,” Acta Astronaut. 123, 37–50 (2016).CrossRefGoogle Scholar
Flores-Abad, A., Ma, O., Pham, K. and Ulrich, S., “A review of space robotics technologies for on-orbit servicing,” Prog. Aerosp. Sci. 68, 1–26 (2014).CrossRefGoogle Scholar
Xu, W., Yan, L., Mu, Z. and Wang, Z., “Dual arm-angle parameterisation and its applications for analytical inverse kinematics of redundant manipulators,” Robotica 34, 2669–2688 (2016).CrossRefGoogle Scholar
Colbaugh, R., Seraji, H. and Glass, K. L., “Obstacle avoidance for redundant robots using configuration control,” J. Rob. Syst. 6(6), 721–744 (1989).CrossRefGoogle Scholar
Rahmanian-Shahri, N. and Troch, I., “Collision-avoidance control for redundant articulated robots,” Robotica 13(02), 159–168 (1995).CrossRefGoogle Scholar
Perdereau, V., Passi, C. and Drouin, M., “Real-time control of redundant robotic manipulators for mobile obstacle avoidance,” Rob. Auton. Syst. 41(1), 41–59 (2002).CrossRefGoogle Scholar
Bonner, S. and Kelley, R. B., “A novel representation for planning 3-D collision-free paths,” IEEE Trans. Syst. Man Cybern. 20(6), 1337–1351 (1990).CrossRefGoogle Scholar
Choi, S. I. and Kim, B. K., “Obstacle avoidance control for redundant manipulators using collidability measure,” Robotica 18(02), 143–151 (2000).CrossRefGoogle Scholar
Hwang, K. S. and Ju, M. Y., “3D collision-free motion based on collision index,” J. Intell. Rob. Syst. 33(1), 45–60 (2002).CrossRefGoogle Scholar
Patel, R. V., Shadpey, F., Ranjbaran, F. and Angeles, J., “A collision-avoidance scheme for redundant manipulators: theory and experiments,” J. Rob. Syst. 22(12), 737–757 (2005).CrossRefGoogle Scholar
Volpe, R. and Khosla, P., “Manipulator control with superquadric artificial potential functions: theory and experiments,” IEEE Trans. Syst. Man Cybern. 20(6), 1423–1436 (1990).CrossRefGoogle Scholar
Kim, J. and Khosla, P. K., “Real-time obstacle avoidance using harmonic potential functions,” IEEE Trans. Rob. Autom. 8(3), 338–349 (1992).CrossRefGoogle Scholar
Mu, Z., Yang, Y., Xu, W., Gao, X. and Xue, L., “Collision-free trajectory planning of redundant space manipulators based on pseudo-distance,” Proceeding of the 11th World Congress on Intelligent Control and Automation, Shenyang, China (2014) pp. 5223–5228.Google Scholar
Mu, Z., Xu, W. and Liang, B., “Avoidance of multiple moving obstacles during active debris removal using a redundant space manipulator,” Int. J. Cont. Autom. Syst. 15(2), 815–826 (2017).CrossRefGoogle Scholar
Glass, K., Colbaugh, R., Lim, D. and Seraji, H., “Real-time collision avoidance for redundant manipulators,” IEEE Trans. Rob. Autom. 11(3), 448–457 (1995).CrossRefGoogle Scholar
Yoshida, E., Esteves, C., Belousov, I., Laumond, J. P., Sakaguchi, T. and Yokoi, K., “Planning 3-D collision-free dynamic robotic motion through iterative reshaping,” IEEE Trans. Rob. 24(5), 1186–1198 (2008).CrossRefGoogle Scholar
Freund, E., Schluse, M. and Rossmann, J., “Dynamic collision avoidance for redundant multi-robot systems,” Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems, Maui, HI (2001) pp. 1201–1206.Google Scholar
Mayorga, R. V., “An appropriate bounded method for the on-line obstacle avoidance of redundant manipulators,” Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems, Grenoble, France (1997) pp. 1700–1705.Google Scholar
Seraji, H. and Bon, B., “Real-time collision avoidance for position-controlled manipulators,” IEEE Trans. Rob. Autom. 15(4), 670–677 (1999).CrossRefGoogle Scholar
Xu, W., Zhang, J., Qian, H. and Chen, Y., “Identifying the singularity conditions of Canadarm2 based on elementary Jacobian transformation,” IEEE/RSJ International Conference on Intelligent Robots and Systems, Tokyo, Japan (2013) pp. 795–800.Google Scholar
Xu, W., Zhang, J., Liang, B. and Li, B., “Singularity analysis and avoidance for robot manipulators with nonspherical wrists,” IEEE Trans. Ind. Electron 63(1), 277–290 (2015).CrossRefGoogle Scholar
Chiaverini, S., Siciliano, B. and Egeland, O., “Review of damped least squares inverse kinematics with experiments on an industrial robot manipulator,” IEEE Trans. Contr. Syst. Technol. 2(2), 123–134 (1994).CrossRefGoogle Scholar
Colomé, A. and Torras, C., “Closed-loop inverse kinematics for redundant robots: comparative assessment and two enhancements,” IEEE/ASME Trans. Mech. 20(2), 944–955 (2015).CrossRefGoogle Scholar
Chirikjian, G. S. and Burdick, J. W., “A modal approach to hyper-redundant manipulator kinematics,” IEEE Trans. Rob. Autom. 10(3), 343–354 (1994).CrossRefGoogle Scholar
Chirikjian, G. S. and Burdick, J. W., “An obstacle avoidance algorithm for hyper-redundant manipulators,” Proceedings of IEEE International Conference on Robotics and Automation, Cincinnati, OH (1990) pp. 625–631.CrossRefGoogle Scholar
Chirikjian, G. S., Theory and applications of hyper-redundant robotic mechanisms. Ph.D. Dissertation (California Institute of Technology, 1992).Google Scholar
Xu, W., Mu, Z., Liu, T. and Liang, B., “A modified modal method for solving the mission-oriented inverse kinematics of hyper-redundant space manipulators for on-orbit servicing,” Acta Astronaut. 139, 54–66 (2017).CrossRefGoogle Scholar
Fahimi, F., Ashrafiuon, H. and Nataraj, C., “Obstacle avoidance for spatial hyper-redundant manipulators using harmonic potential functions and the mode shape technique,” J. Rob. Syst. 20(1), 23–33 (2003).CrossRefGoogle Scholar
Mochiyama, H., and Kobayashi, H., “The shape Jacobian of a manipulator with hyper degrees of freedom,” IEEE International Conference on Robotics and Automation, Detroit, Michigan (1999) pp. 2837–2842.Google Scholar