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Trajectory planning of mobile manipulators using dynamic programming approach

Published online by Cambridge University Press:  19 November 2012

M. H. Korayem*
Affiliation:
Robotic Research Laboratory, Center of Excellence in Experimental Solid Mechanics and Dynamics, School of Mechanical Engineering, Iran University of Science and Technology, P.O. Box 18846, Tehran, Iran
M. Irani
Affiliation:
Robotic Research Laboratory, Center of Excellence in Experimental Solid Mechanics and Dynamics, School of Mechanical Engineering, Iran University of Science and Technology, P.O. Box 18846, Tehran, Iran
A. Charesaz
Affiliation:
Robotic Research Laboratory, Center of Excellence in Experimental Solid Mechanics and Dynamics, School of Mechanical Engineering, Iran University of Science and Technology, P.O. Box 18846, Tehran, Iran
A. H. Korayem
Affiliation:
Robotic Research Laboratory, Center of Excellence in Experimental Solid Mechanics and Dynamics, School of Mechanical Engineering, Iran University of Science and Technology, P.O. Box 18846, Tehran, Iran
A. Hashemi
Affiliation:
Robotic Research Laboratory, Center of Excellence in Experimental Solid Mechanics and Dynamics, School of Mechanical Engineering, Iran University of Science and Technology, P.O. Box 18846, Tehran, Iran
*
*Corresponding author. E-mail: [email protected]

Summary

This paper presents a solution for optimal trajectory planning problem of robotic manipulators with complicated dynamic equations. The main goal is to find the optimal path with maximum dynamic load carrying capacity (DLCC). Proposed method can be implemented to problems of both motion along a specified path and point-to-point motion. Dynamic Programming (DP) approach is applied to solve optimization problem and find the positions and velocities that minimize a pre-defined performance index. Unlike previous attempts, proposed method increases the speed of convergence by using the sequential quadratic programming (SQP) formulation. This formulation is used for solving problems with nonlinear constraints. Also, this paper proposes a new algorithm to design optimal trajectory with maximum DLCC for both fixed and mobile base mechanical manipulators. Algorithms for DLCC calculations in previous works were based on indirect optimization method or linear programming approach. The proposed trajectory planning method is applied to a linear tracked Puma and the mobile manipulator named Scout. Application of this algorithm is confirmed and simulation results are compared with experimental results for Scout robot. In experimental test, results are obtained using a new stereo vision system to determine the position of the robot end-effector.

Type
Articles
Copyright
Copyright © Cambridge University Press 2012 

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References

1.Wang, L. T. and Ravani, B., “Dynamic load carrying capacity of mechanical manipulators: Part 1,” ASME J. Dyn. Syst. Meas. Control 110 (1), 4652 (1988).CrossRefGoogle Scholar
2.Korayem, M. H., Najafi, Kh. and Bamdad, M., “Synthesis of cable driven robots dynamic motion with maximum load carrying capacities: Iterative linear programming approach,” Scientia Iranica: Trans. B, Mech. Eng. 17 (3), 229239 (2010).Google Scholar
3.Korayem, M. H., Ghariblu, H. and Basu, A., “Maximum allowable load of mobile manipulator for two given end points of end-effector,” Int. J. AMT 24 (10), 743751 (2004).Google Scholar
4.Korayem, M. H., Firouzy, S. and Heidari, A., “Dynamic Load Carrying Capacity of Mobile-Base Flexible-Link Manipulators Using Finite Element Approach,” Proceedings of IEEE International Conference on Robotics and Biomemitics, Sanya, China (Dec. 15–18, 2007) pp. 21722177.Google Scholar
5.Korayem, M. H., Azimirad, V., Nikoobin, A. and Boroujeni, Z., “Maximum load-carrying capacity of autonomous mobile manipulator in an environment with obstacle considering tip over stability,” Int. J. Adv. Manuf. Technol. 46 (5–8), 811829 (2010).CrossRefGoogle Scholar
6.Bakker, B., Zivcovic, Z. and Ben, K., “Hierarchical Dynamic Programming for Robot Path PlanningIEEE/RSJ International Conference on Intelligent Robots and Systems, IROS, Edmonton, Canada (Aug. 2–6, 2005) pp. 37203725.Google Scholar
7.Eisler, G., Wilson, G. and Robinett, R., “Discrete Dynamic Programming for Optimized Path Planning of Flexible Robots,” IEEE/RSJ International Conference on Intelligent Robots and Systems, Sendai, Japan (Sep. 28–Oct. 2, 2004) pp. 29182923.Google Scholar
8.Gasparetto, A. and Zanotto, V., “A technique for time-jerk optimal planning of robot trajectories,” Robot. Comput.-Integr. Manuf. 24 (3), 415426 (2008).CrossRefGoogle Scholar
9.Parasuraman, S., Hou, Chiew Mun and Ganapathy, V., “Motion planning for a redundant manipulator using genetic algorithm,” Key Eng. Mater. 467–469, 782787 (2011).CrossRefGoogle Scholar
10.Radovnikovich, M., Cheok, C. and Vempaty, P., “Comparison of Optimal Path Planning Algorithms for an Autonomous Mobile Robot,” IEEE Conference on Technologies for Practical Robot Applications, Woburn, MA, USA (Apr. 11–12, 2011) pp. 3539.CrossRefGoogle Scholar
11.Stilman, M., Atkeson, C. G., Kuffner, J. J. and Zeglin, G., “Dynamic Programming in Reduced Dimensional Spaces: Dynamic Planning for Robust Biped Locomotion,” IEEE International Conference on Robotics and Automation, Barcelona, Spain (Apr. 18–22, 2005) pp. 23992404.Google Scholar
12.Sallaberger, C. and D'Eleuterio, G., “Optimal robotic path planning using dynamic programming and randomization,” 35 (2–3), 143156 (1995).Google Scholar
13.Lee, T. T. and Shih, C. L., “A study of the gait control of a quadruped walking vehicle,” IEEE J. Robot. Autom. 2 (2), 6169 (1986).Google Scholar
14.Korayem, M. H., Nikoobin, A. and Azimirad, V., “Maximum load carrying capacity of mobile manipulators: Optimal control approach,” Robotica 27 (1), 147159 (2009).CrossRefGoogle Scholar
15.Yamamoto, Y. and Yun, X., “Effect of the dynamic interaction on coordinated control of mobile manipulators,” IEEE Trans. Robot. Autom. 12 (5), 816824 (1996).CrossRefGoogle Scholar
16.Heikkilä, J. and Silvén, O., “A Four-Step Camera Calibration Procedure with Implicit Image Correction,” IEEE Computer Society Conference on Computer Vision and Pattern Recognition, San Juan, Puerto Rico (Jun. 17–19, 1997) pp. 11061112.Google Scholar
17.Zhang, Z., “A flexible new technique for camera calibration,” IEEE Trans. Pattern Anal. Mach. Intell. 22 (11), 13301334 (2000).CrossRefGoogle Scholar
18.Garcia, J. F. C., Yao, H. G. and Zheng, S., “3D reconstruction of objects using stereo imaging,” Opt. Lasers Eng. 22, 193213 (1995).CrossRefGoogle Scholar