Skip to main content
Log in

Inverse Kinematics Analysis and COG Trajectory Planning Algorithms for Stable Walking of a Quadruped Robot with Redundant DOFs

  • Published:
Journal of Bionic Engineering Aims and scope Submit manuscript

Abstract

This paper presents a new Center of Gravity (COG) trajectory planning algorithm for a quadruped robot with redundant Degrees of Freedom (DOFs). Each leg has 7 DOFs, which allow the robot to exploit its kinematic redundancy for various locomotion and manipulation tasks. Also, the robot can suitably adapt to different environment (e.g., passing through a narrow gap) by simply changing the body posture. However, the robot has significant COG movement during the leg swinging phase due to the heavy leg weights; the weight of all the four legs takes up 80% of the robot’s total weight. To achieve stable walking in the presence of undesired COG movements, a new COG trajectory planning algorithm was proposed by using a combined Jacobian of COG and centroid of a support polygon including a foot contact constraint. Additionally, the inverse kinematics of each leg was solved by modified improved Jacobian pseudoinverse (mIJP) algorithm. The mIJP algorithm could generate desired trajectories for the joints even when the robot’s leg is in a singular posture. Owing to these proposed methods, the robot was able to perform various modes of locomotion both in simulations and experiments with improved stability.

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

Access this article

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

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. Chiaverini S, Oriolo G, Walker I D. Kinematically redundant manipulators. In: Siciliano B, Khatib O, eds., Handbook of Robotics, Springer, Berlin-Heidelberg, Germany, 2008, 245–268.

    Chapter  Google Scholar 

  2. Omrčen D, Žlajpah L, Nemec B. Compensation of velocity and/or acceleration joint saturation applied to redundant manipulator. Robotics and Autonomous Systems, 2007, 55, 337–344.

    Article  Google Scholar 

  3. Zhao Y J, Jin L, Zhang P, Li J Y. Inverse displacement analysis of a hyper-redundant elephant’s trunk robot. Journal of Bionic Engineering, 2018, 15, 397–407.

    Article  Google Scholar 

  4. Kwak B, Park H, Bae J. Development of a quadruped robot with redundant DOFs for high-degree of functionality and adaptation. Proceedings of IEEE International Conference on Advanced Intelligent Mechatronics (AIM), Banff, Canada, 2016, 608–613.

    Google Scholar 

  5. Shkolnik A, Tedrake R. Inverse kinematics for a point-foot quadruped robot with dynamic redundancy resolution. Proceedings of IEEE International Conference on Robotics and Automation (ICRA), Rome, Italy, 2007, 4331–4336.

    Google Scholar 

  6. Byl K, Byl M, Satzinger B. Algorithmic optimization of inverse kinematics tables for high degree-of-freedom limbs. Proceedings of ASME Dynamic Systems and Control Conference (DSCC), San Antonio, USA, 2014.

    Google Scholar 

  7. Byl K, Byl M. Design of fast walking with one-versus two-at-a-time swing leg motions for RoboSimian. Proceedings of IEEE International Conference on Technologies for Practical Robot Applications (TePRA), Woburn, USA, 2015, 1–7.

    Google Scholar 

  8. Chan T F, Dubey R V. A weighted least-norm solution based scheme for avoiding joint limits for redundant joint manipulators. IEEE Transactions on Robotics and Automation, 1995, 11, 286–292.

    Article  Google Scholar 

  9. Sciavicco L, Siciliano B. A solution algorithm to the inverse kinematic problem for redundant manipulators. IEEE Journal on Robotics and Automation, 1988, 4, 403–410.

    Article  Google Scholar 

  10. Siciliano B, Slotine J-J E. A general framework for managing multiple tasks in highly redundant robotic systems. Proceedings of International Conference on Advanced Robotics, Pisa, Italy, 1991, 1211–1216.

    Google Scholar 

  11. Cheng F T, Lee H L, Orin D E. Increasing the locomotive stability margin of multilegged vehicles. Proceedings of IEEE International Conference on Robotics and Automation (ICRA), Detroit, USA, 1999, 1708–1714.

    Google Scholar 

  12. Pongas D, Mistry M, Schaal S. A robust quadruped walking gait for traversing rough terrain. Proceedings of IEEE International Conference on Robotics and Automation (ICRA), Roma, Italy, 2007, 1474–1479.

    Google Scholar 

  13. Zhang S S, Rong X W, Li Y B, Li B. A composite cog trajectory planning method for the quadruped robot walking on rough terrain. International Journal of Control and Automation, 2015, 8, 101–118.

    Article  Google Scholar 

  14. ROBOTIS Dynamixel, [2018-03-13], http://www.robotis.com/.

  15. SMOOTH-ON Dragon skin, [2018-03-13], https://www.smooth-on.com/product-line/dragon-skin/.

  16. He J, Gao F. Type synthesis for bionic quadruped walking robots. Journal of Bionic Engineering, 2015, 12, 527–538.

    Article  Google Scholar 

  17. Gonzalez-Rodriguez A G, Gonzalez-Rodriguez A, Castillo- Garcia F. Improving the energy efficiency and speed of walking robots. Mechatronics, 2014, 24, 476–488.

    Article  Google Scholar 

  18. Whitney D E. Resolved motion rate control of manipulators and human prostheses. IEEE Transactions on Man-machine Systems, 1969, 10, 47–53.

    Article  Google Scholar 

  19. Siciliano B, Sciavicco L, Villani L, Oriolo G. Robotics: Modeling, Planning and Control, Springer, London, UK, 2009.

    Book  Google Scholar 

  20. Zghal H, Dubey R V, Euler J A. Efficient gradient projection optimization for manipulators with multiple degrees of redundancy. Proceedings of IEEE International Conference on Robotics and Automation (ICRA), Cincinnati, USA, 1990, 1006–1011.

    Chapter  Google Scholar 

  21. MathWorks MATLAB, [2018-03-01], https://www.mathworks.com/.

  22. McGhee R B, Frank A A. On the stability properties of quadruped creeping gaits. Mathematical Biosciences, 1968, 3, 331–351.

    Article  MATH  Google Scholar 

  23. Coppelia Robotics V-REP, [2018-03-01], http://www.coppeliarobotics.com/.

  24. Song S M, Waldron K J. An analytical approach for gait study and its applications on wave gaits. The International Journal of Robotics Research, 1987, 6, 60–71.

    Article  Google Scholar 

  25. Hirose S, Tsukagoshi H, Yoneda K. Normalized energy stability margin and its contour of walking vehicles on rough terrain. Proceedings of IEEE International Conference on Robotics and Automation (ICRA), Seoul, Korea, 2001, 181–186.

    Google Scholar 

  26. Vukobratović M, Borovac B. Zero-moment point — thirty five years of its life. International Journal of Humanoid Robotics, 2004, 1, 157–173.

    Article  Google Scholar 

  27. Messuri D A, Klein C A. Automatic body regulation for maintaining stability of a legged vehicle during rough-terrain locomotion. IEEE Journal on Robotics and Automation, 1985, 1, 132–141.

    Article  Google Scholar 

Download references

Acknowledgment

This work was supported by the 2018 Research Fund (1.180015.01) of UNIST (Ulsan National Institute of Science and Technology), the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science and ICT (No. NRF-2015R1C1A1A01053763), and the NRF Grant funded by the Korean Government (MSIT) (No. NRF-2016R1A5A1938472).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Joonbum Bae.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Park, H., Kwak, B. & Bae, J. Inverse Kinematics Analysis and COG Trajectory Planning Algorithms for Stable Walking of a Quadruped Robot with Redundant DOFs. J Bionic Eng 15, 610–622 (2018). https://doi.org/10.1007/s42235-018-0050-8

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s42235-018-0050-8

Keywords

Navigation