A Topological Approach to Globally-Optimal Redundancy Resolution with Dynamic Programming

  • Enrico FerrentinoEmail author
  • Pasquale Chiacchio
Conference paper
Part of the CISM International Centre for Mechanical Sciences book series (CISM, volume 584)


Redundancy resolution schemes based on calculus of variations present several drawbacks limiting the intrinsic potential, in terms of augmented dexterity and flexibility, of redundant manipulators. In particular, they do not guarantee the achievement of the globally-optimal solution. Grid search algorithms can be designed starting from dynamic programming (DP) which overcome the limits of calculus of variations. This paper, in particular, presents a novel algorithm that considers the employment of multiple DP grids to be searched together at the same time. Such a technique achieves the global optimum, while allowing for pose reconfiguration of the manipulator while the task is executed.


Inverse kinematics Redundant robots Redundancy resolution Dynamic programming Self-motion manifolds 


  1. 1.
    Burdick, J.W.: On the inverse kinematics of redundant manipulators: characterization of the self-motion manifolds. In: IEEE International Conference on Robotics and Automation, pp. 264–270 (1989)Google Scholar
  2. 2.
    Chen, Y.C., O’Neil, K.: Stabilization of pseudoinverse acceleration control of redundant mechanisms. Robotics 1998, 293–299 (1998)Google Scholar
  3. 3.
    Ferrentino, E., Chiacchio, P.: Redundancy parameterization in globally-optimal inverse kinematics. In: The 16th International Symposium on Advances in Robot Kinematics (ARK) (2018, accepted)Google Scholar
  4. 4.
    Ferrentino, E., Chiacchio, P.: Topological analysis of inverse kinematic solutions for redundant manipulators. In: The 22nd CISM-IFToMM Symposium (RoManSy) (2018, accepted)Google Scholar
  5. 5.
    Guigue, A., Ahmadi, M., Hayes, M.J.D., Langlois, R., Tang, F.C.: A dynamic programming approach to redundancy resolution with multiple criteria. In: IEEE International Conference on Robotics and Automation, pp. 1375–1380 (2007)Google Scholar
  6. 6.
    Guigue, A., Ahmadi, M., Langlois, R., Hayes, M.J.D.: Pareto optimality and multiobjective trajectory planning for a 7-DOF redundant manipulator. IEEE Trans. Robot. 26(6), 1094–1099 (2010)CrossRefGoogle Scholar
  7. 7.
    Hollerbach, J.M., Suh, K.C.: Redundancy resolution of manipulators through torque optimization. IEEE J. Robot. Autom. 3(4), 308–316 (1987)CrossRefGoogle Scholar
  8. 8.
    Kazerounian, K., Wang, Z.: Global versus local optimization in redundancy resolution of robotic manipulators. Int. J. Robot. Res. 7(5), 3–12 (1988)CrossRefGoogle Scholar
  9. 9.
    Nakamura, Y., Hanafusa, H.: Optimal redundancy control of robot manipulators. Int. J. Robot. Res. 6(1), 32–42 (1987)CrossRefGoogle Scholar
  10. 10.
    Pámanes, J.A., Wenger, P., Zapata, J.L.: Motion planning of redundant manipulators for specified trajectory tasks. In: Advances in Robot Kinematics, pp. 203–212 (2002)Google Scholar
  11. 11.
    Suh, K.C., Hollerbach, J.M.: Local versus global torque optimization of redundant manipulators. In: IEEE International Conference on Robotics and Automation, pp. 619–624 (1987)Google Scholar
  12. 12.
    Wenger, P., Chedmail, P., Reynier, F.: A global analysis of following trajectories by redundant manipulators in the presence of obstacles. In: IEEE International Conference on Robotics and Automation, pp. 901–906 (1993)Google Scholar
  13. 13.
    Zhou, Z., Nguyen, C.C.: Globally optimal trajectory planning for redundant manipulators using state space augmentation method. J. Intell. Robot. Syst. Theory Appl. 19(1), 105–117 (1997)CrossRefGoogle Scholar

Copyright information

© CISM International Centre for Mechanical Sciences 2019

Authors and Affiliations

  1. 1.Università degli Studi di SalernoFiscianoItaly

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