Skip to main content

Advertisement

SpringerLink
Log in

Low Impact Force and Energy Consumption Motion Planning for Hexapod Robot with Passive Compliant Ankles

  • Published:
Journal of Intelligent & Robotic Systems Aims and scope Submit manuscript

Abstract

Motion planning plays an important role in the performance optimization of legged robots. This paper presents a method to minimize the impact force and energy consumption effectively by providing an integrated strategy of motion planning subject to velocity and acceleration constraints. The parameters defined for the motion planning are computed to generate the foot trajectory. A foot–terrain interaction model and an energy-consumption model are formulated to evaluate the contact force and power consumption for statically stable gaits. The proposed method has been implemented on a hexapod robot. The acceleration of foot landing is reduced, and constant velocity control of the trunk body with passive compliant ankles is achieved for reducing the impact force and energy consumption. Extensive experiments have been carried out, and the experimental results have demonstrated the effectiveness of the proposed method in comparison with a conventional method.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. Reina, G., Foglia, M.: On the mobility of all-terrain rovers. Ind. Robot. 40(2), 121–131 (2013)

    Article  Google Scholar 

  2. Nagatani, K., Noyori, T., Yoshida, K.: Development of multi-D.O.F. tracked vehicle to traverse weak slope and climb up rough slope. In: Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, Tokyo, pp. 2849–2854 (2013)

  3. Wooden, D., Malchano, M., Blankespoor, K., Howardy, A., Rizzi, A.A., Raibert, M.: Autonomous navigation for BigDog. In: Proceedings of the IEEE International Conference on Robotics and Automation, Anchorage, pp. 4736–4741 (2010)

  4. Chen, S.C., Huang, K.J., Chen, W.H., Shen, S.Y., Li, C.H, Lin, P.C.: Quattroped: a leg–wheel transformable robot. IEEE/ASME Trans. Mechatron. 19(2), 730–742 (2014)

    Article  Google Scholar 

  5. Zhuang, H.C., Gao, H.B., Deng, Z.Q., Ding, L.: A review of heavy-duty legged robots. Sci. China Technol. Sci. 57(2), 298–314 (2014)

    Article  Google Scholar 

  6. Lee, W.: The kinematics of motion planning for multilegged vehicles over uneven terrain. IEEE J. Robot. Autom. 4(2), 204–212 (1988)

    Article  Google Scholar 

  7. Irawan, A., Nonami, K.: Optimal impedance control based on body inertia for a hydraulically driven hexapod robot walking on uneven and extremely soft terrain. J. Field Rob. 28(5), 690–713 (2011)

    Article  MATH  Google Scholar 

  8. Irawan, A., Nonami H Ohroku, K., Akutsu, Y., Imamura, S.: Adaptive impedance control with compliant body balance for hydraulically driven hexapod robot. J. Syst. Des. Dyn. 5(5), 893–908 (2011)

    Google Scholar 

  9. Raibert, M., Blankespoor, K., Nelson, G., Playter, R.: BigDog, the rough-terrain quadruped robot. In: Proceedings of 17th World Congress on the International Federation of Automatic Control, Seoul. 10822–10825 (2008)

  10. Kalakrishnan, M., Buchli, J.: Learning, planning, and control for quadruped locomotion over challenging terrain. Int. J. Robot. Res. 30(2), 236–258 (2011)

    Article  Google Scholar 

  11. Townsend, J., Biesiadecki, J., Collins, C.: ATHLETE mobility performance with active terrain compliance. In: Proceedings of the IEEE Aerospace Conference, Big Sky, pp. 1–7 (2010)

  12. Chavez-Clemente, D.: Gait optimization for multi-legged walking robots, with application to a lunar hexapod, pp. 1–150. Department of Aeronautics and Astronautics, Stanford University (2011)

  13. Saranli, U., Koditschek, M., Buehler, D.E.: RHex: a simple and highly mobile hexapod robot. Int. J. Robot. Res. 20(7), 616–631 (2001)

    Article  Google Scholar 

  14. Chettibi, T., Haddada, M., Labedb, A., Hanchi, S.: Generating optimal dynamic motions for closed-chain robotic systems. Eur. J. Mech. Solids 24, 504–518 (2005)

    Article  MathSciNet  MATH  Google Scholar 

  15. Manjanna, S., Dudek, G.: Autonomous gait selection for energy efficient walking. In: 2015 IEEE International Conference on Robotics and Automation, pp. 5155–5162 (2015)

  16. Shabestari, S.S., Emami, M.R.: Gait planning for a hopping robot. Robotica 34(8), 1822–1840 (2016)

    Article  Google Scholar 

  17. Potts, A.S.: Optimal power loss motion planning in legged robots. Robotica 34(2), 423–448 (2015)

    Article  Google Scholar 

  18. Roy, S.S., Pratihar, D.K.: Kinematics, dynamics and power consumption analyses for turning motion of a six-legged robot. J. Intell. Robot. Syst. 74(3), 663–688 (2014)

    Article  Google Scholar 

  19. Kottege, N., Parkinson, C.: Energetics-informed hexapod gait transitions across terrains. In: 2015 IEEE International Conference on Robotics and Automation, pp. 5140–5147 (2015)

  20. Jin, B., Chen, C., Li, W.: Power consumption optimization for a hexapod walking robot. J. Intell. Robot. Syst. 71(2), 195–209 (2013)

    Article  Google Scholar 

  21. Deng, Z.Q., Liu, Y.Q., Ding, L., Gao, H.B., Yu, H.T., Liu, Z: Motion planning and simulation verification of a hydraulic hexapod robot based on reducing energy/flow consumption. J. Mech. Sci. Technol. 29(10), 4427–4436 (2015)

    Article  Google Scholar 

  22. Usherwood, J.R., Bertram, J.E.A.: Understanding brachiation, insight from a collisional perspective. J. Exp. Biol. 206(10), 1631–1642 (2003)

    Article  Google Scholar 

  23. Ruina, A., Bertram, J.E., Srinivasan, M.: A collisional model of the energetic cost of support work qualitatively explains leg sequencing in walking and galloping pseudo-elastic leg behavior in running and the walk-to-run transition. J. Theor. Biol. 237(2), 170–192 (2005)

    Article  MathSciNet  Google Scholar 

  24. Wilson, D.M.: Insect walking. Annu. Rev. Entomol. 11(1), 103–122 (1996)

    Article  Google Scholar 

  25. Nishii, J.: Legged insects select the optimal locomotor pattern based on the energetic cost. Biol. Cybern. 83(5), 435–442 (2000)

    Article  Google Scholar 

  26. Siciliano, B., Khatib, O.: Springer Handbook of Robotics. Springer, Berlin (2016)

    Book  MATH  Google Scholar 

  27. Gonzalez de Santos, P., Garcia, E., Ponticelli, R., Armada, M.: Minimizing energy consumption in hexapod robots. Adv. Robot. 23, 681–704 (2009)

    Article  Google Scholar 

  28. Nishii, J.: An analytical estimation of the energy cost for legged locomotion. J. Theor. Biol. 238(3), 636–645 (2006)

    Article  MathSciNet  Google Scholar 

  29. Dupont, P.E.: Friction modeling in dynamic robot simulation. In: Proceedings. 1990 IEEE International Conference on Robotics and Automation, pp. 1370–1376 (1990)

  30. Gogoussis, A., Donath, M.: Coulomb friction joint and drive effects in robot mechanisms. In: Proceedings. 1987 IEEE International Conference on Robotics and Automation, vol. 4, pp. 828–836 (1987)

  31. Zhuang, H.C., Gao, H.B., Ding, L., Liu, Z., Deng, Z.Q.: Method for analyzing articulated torques of heavy-duty six-legged robot. Chin. J. Mech. Eng. 26(4), 801–812 (2013)

    Article  Google Scholar 

  32. Ding, L., Gao, H.B., Deng, Z.Q., Song, J.H., Liu, Y.Q., Liu, G.J., Iagnemma, K.: Foot-terrain interaction mechanics for legged robots: modeling and experimental validation. Int. J. Robot. Res. 32(13), 1585–1606 (2013)

    Article  Google Scholar 

  33. Hunt, K.H., Crossley, F.R.E.: Coefficient of restitution interpreted as damping in vibroimpact. J. Appl. Mech. 42(2), 440–445 (1975)

    Article  Google Scholar 

Download references

Acknowledgements

This study was supported in part by the National Natural Science Foundation of China (Grant No. 51575120/61370033), National Basic Research Program of China (Grant No. 2013CB035502), Foundation for Innovative Research Groups of the National Natural Science Foundation of China (Grant No. 51521003), Foundation of Chinese State Key Laboratory of Robotics and Systems (Grant No. SKLRS201501B, SKLRS20164B), Harbin Talent Program for Distinguished Young Scholars (No. 2014RFYXJ001), and the “111 Project” (Grant No. B07018).

Author information

Authors and Affiliations

  1. State Key Laboratory of Robotics and System, Harbin Institute of Technology, Harbin, 150001, China

    Haibo Gao, Yufei Liu, Liang Ding, Zongquan Deng & Haitao Yu

  2. Department of Aerospace Engineering, Ryerson University, 350 Victoria Street, Toronto, M5B 2K3, ON, Canada

    Guangjun Liu

  3. School of Automotive Engineering, Harbin Institute of Technology, Weihai, 264209, China

    Yiqun Liu

Authors
  1. Haibo Gao
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Yufei Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Liang Ding
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Guangjun Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Zongquan Deng
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Yiqun Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Haitao Yu
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Liang Ding.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Gao, H., Liu, Y., Ding, L. et al. Low Impact Force and Energy Consumption Motion Planning for Hexapod Robot with Passive Compliant Ankles. J Intell Robot Syst 94, 349–370 (2019). https://doi.org/10.1007/s10846-018-0828-2

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10846-018-0828-2

Keywords

Search

Navigation