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Sampling-based finger gaits planning for multifingered robotic hand

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Abstract

To perform large scale or complicated manipulation tasks, a multi-fingered robotic hand sometimes has to sequentially adjust its grasp status to overcome constraints of the manipulation, such as workspace limits, force balance requirement, etc. Such a strategy of changing grasping status is called a finger gait, which exhibits strong hybrid characteristics due to the discontinuity caused by relocating limited fingers and the continuity caused by manipulating objects. This paper aims to explore the complicated finger gaits planning problem and provide a method for robotic hands to autonomously generate feasible finger gaits to accomplish given tasks. Based on the hybrid automaton formulation of a popular finger gaiting primitive, finger substitution, we formulate the finger gait planning problem into a classic motion planning problem with a hybrid configuration space. Inspired by the rapidly-exploring random tree (RRT) techniques, we develop a finger gait planner to quickly search for a feasible manipulation strategy with finger substitution primitives. To increase the search performance of the planner, we further develop a refined sampling strategy, a novel hybrid distance and an efficient exploring strategy with the consideration of the problem’s hybrid nature. Finally, we use a representative numerical example to verify the validity of our problem formulation and the performance of the RRT based finger gait planner.

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References

  1. Amato, N., & Wu, Y. (1996). A randomized roadmap method for path and manipulation planning. In Proceedings of IEEE international conference on robotics and automation (pp. 113–120) 1996.

  2. Branicky, M. S., & Curtiss, M. M. (2002). Nonlinear and hybrid control via RTTs. In Proc. of intl. symp. math. theory of networks and systems, August 2002.

  3. Branicky, M. S., Borkar, V. S., & Mitter, S. K. (1998). A unified framework for hybrid control: model and optimal control theory. IEEE Transactions on Automatic Control, 43(1), 31–45.

  4. Branicky, M. S., Curtiss, M. M., Levine, J., & Morgan, S. (2003). RRTs for nonlinear, discrete, and hybrid planning and control. In Proceedings IEEE conference decision & control, 2003.

  5. Buss, M., & Schimit, G. (1996). Hybrid system behavior specification for multiple robotic mechanisms. In IEEE/RSJ international conference on intelligent robots and systems (pp. 140–147) 1996.

  6. Buss, M., & Schlegl, T. (2000). A discrete-continuous control approach to dextrous manipulation. In Proceedings of IEEE international conference on robotics and automation (pp. 276–281) 2000.

  7. Chen, I. M., & Burdick, J. W. (1993). Finding antipodal point grasps on irregularly shaped objects. IEEE Transactions on Robotics and Automation, 9(4), 507–512.

  8. Frazzoli, E., Dahleh, M. A., & Feron, E. (2000). Real-time motion planning for agile autonomous vehicles. In American Institute of Aeronautics and Astronautics Paper.

  9. Goodwine, B., & Burdick, J. (2001). Controllability of kinematic control systems on stratified configuration spaces. IEEE Transactions on Automatic Control, 46(3), 358–368.

  10. Goodwine, B., & Burdick, J. (2002). Motion planning for kinematic stratified systems with application to quasi-static legged locomotion and finger gaiting. IEEE Transactions on Automatic Control, 18(2), 209–222.

  11. Han, L., & Trinkle, J. (1998). Dextrous manipulation by rolling and finger gaiting. In Proceedings of IEEE international conference on robotics and automation (pp. 730–735) 1998.

  12. Han, L., Trinkle, J. C., & Li, Z. X. (2000). Grasp analysis as linear matrix inequality problems. IEEE Transactions on Robotics and Automation, 16(6), 663–674.

  13. Henzinger, T. (1996). The theory of hybrid automata. In Proceedings of the 11th annual IEEE symposium on logic in computer science (pp. 278–292) 1996.

  14. Hong, J. W., Lafferriere, G., Mishra, B., & Tang, X. L. (1990). Fine manipulation with multifinger hand. In Proceedings of IEEE international conference on robotics and automation (pp. 1568–1573) (1990).

  15. Huber, M., & Grupen, R. A. (2002). Robust finger gaits from closed-loop controllers. In 2002 IEEE international conference on intelligent robots and systems (pp. 1578–1584) 2002.

  16. Kavraki, L. E., Svestka, P., Latombe, J. C., & Overmars, M. H. (1996). Probabilistic roadmaps for path planning in high-dimensional configuration spaces. IEEE Transactions on Robotics and Automation, 12(4), 566–580.

  17. Kuffner, J. J. (2004). Effective sampling and distance metrics for 3D rigid body path planning. In Proceedings IEEE international conference on robotics & automation, 2004.

  18. Kuffner, J., & LaValle, S. (2000). RRT-connect: An efficient approach to single-query path planning. In Proceedings of IEEE international conference on robotics and automation, 2000.

  19. Lantos, I., Harmati, B., & Payandeh, S. (2002). On fitted stratified and semi-stratified geometric manipulation planning with fingertip relocations. International Journal of Robotics Research, 21(5), 489–510.

  20. LaValle, S. M. (1998). Rapidly-exploring random trees: a new tool for path planning (TR 98-11). Department of Computer Science, Iowa State University.

  21. LaValle, S. M. (2000). Robot motion planning: A game-theoretic foundation. Algorithmica, 26(3), 430–465.

  22. LaValle, S. M. (2006). Planning algorithms. Cambridge: Cambridge University Press. Available at http://planning.cs.uiuc.edu/.

  23. LaValle, S. M., & Kuffner, J. J. (1999). Randomized kinodynamic planning. In Proceedings IEEE international conference on robotics and automation (pp. 473–479) 1999.

  24. LaValle, S. M., & Kuffner, J. J. (2000). Rapidly-exploring random trees: progress and prospects. In Proceedings workshop on the algorithmic foundations of robotics, 2000.

  25. LaValle, S. M., & Kuffner, J. J. (2001a). Rapidly-exploring random trees: progress and prospects. Algorithmic and Computational Robotics: New Directions. Wellesley: AK Peters.

  26. LaValle, S. M., & Kuffner, J. J. (2001b). Randomized kinodynamic planning. International Journal of Robotics Research, 20(5), 378–400.

  27. LaValle, S. M., & Kuffner, J. J. (2001c). Rapidly-exploring random trees: progress and prospects. In Donald, B. R., Lynch, K. M., & Rus, D. (Eds.) Algorithmic and computational robotics: new directions (pp. 293–308). Wellesley: AK Peters.

  28. Liu, Y.-H., Kitagaki, K., Ogasawara, T., & Arimoto, S. (1999). Model-based adaptive hybrid control for manipulators under multiple geometric constrains. IEEE Transactions on Control Systems Technology, 7(1), 97–109.

  29. Lygeros, J. (2003). Lecture notes on hybrid systems (Technical report). Cambridge University.

  30. Montana, D. (1988). The kinematics of contact and grasp. International Journal of Robotics Research, 7(3), 17–32.

  31. Mount, D. M. (1998). Ann programming manual (Technical report). Department of Computer Science, University of Maryland.

  32. Murray, R., Li, Z. X., & Sastry, S. (1994). A mathematical introduction to robotic manipulation. Boca Raton: CRC Press.

  33. Rodriguez, S., Tang, X., Lien, J., & Amato, N. (2006). An obstacle-based rapidly-exploring random tree. In Proceedings of IEEE international conference on robotics and automation (pp. 895–900) 2006.

  34. Schlegl, T., & Buss, M. (1998). Hybrid closed-loop control of robotic hand regrasping. In Proceedings of IEEE international conference on robotics and automation (pp. 3026–3032) 1998.

  35. Schlegl, T., & Buss, M. (1999). A discrete-continuous control architecture for dextrous manipulation. In 1999 IEEE international conference on systems, man, and cybernetics (pp. II-860–II-865) 1999.

  36. Sudsang, A., & Phoka, T. (2005). Geometric reformulation of 3-fingered force-closure condition. In Proceedings of IEEE international conference on robotics and automation (pp. 2338–2343) 2005.

  37. Tomlin, C., Lygeros, J., & Sastry, S. (2000). A game theoretic approach to controller design for hybrid systems. Proceedings of IEEE, 88(7).

  38. Xu, J., & Li, Z. (2006). Analysis and optimization of grasping force in whole hand grasp (HKUST Technical Report).

  39. Xu, J., & Li, Z. (2008). A kinematics model of finger gaits by multifingered hand as hybrid automaton. IEEE Transactions on Automation Science and Engineering, 5(3), 467–479.

  40. Yershova, A., & LaValle, S. M. (2007). Improving motion planning algorithms by efficient nearest-neighbor searching. IEEE Transactions on Robotics, 23(1), 151–157.

  41. Žefran, M. (2002). A feedback strategy for dextrous manipulation. In Proceedings of IEEE international conference on robotics and automation (pp. 2479–2484) 2002.

  42. Zhu, X., & Wang, J. (2003). Synthesis of force-closure grasps on 3-d objects based on the q distance. IEEE Transactions on Robotics and Automation, 19(4), 669–679.

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Author information

Correspondence to Jijie Xu.

Additional information

This work is supported by HK Research Grant Council Grant No. HKUST6226/02E and HKUST6301/03E, US National Science Foundation Grant No. CNS-0448234 and Grant No. CCR-0225610, National Natural Science Foundation of China, Li Ka Shing Foundation and Shantou University Faculty Development Fund.

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Xu, J., Koo, T.J. & Li, Z. Sampling-based finger gaits planning for multifingered robotic hand. Auton Robot 28, 385–402 (2010). https://doi.org/10.1007/s10514-009-9164-5

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  • Dextrous manipulation
  • Finger gaits
  • Manipulation planning
  • Hybrid automaton
  • Rapidly-exploring Random Tree