Hostname: page-component-cd9895bd7-8ctnn Total loading time: 0 Render date: 2024-12-25T04:21:27.513Z Has data issue: false hasContentIssue false
  • English
  • Français

Push recovery of a quadruped robot on challenging terrains

Published online by Cambridge University Press:  30 June 2016

Mahdi Khorram  and
S. Ali A. Moosavian
Mahdi Khorram*
Affiliation:
Center of Excellence in Robotics and Control, Advanced Robotics and Automated Systems Lab, Department of Mechanical Eng, K. N. Toosi Univ of Technology, Tehran, Iran E-mail: [email protected]
S. Ali A. Moosavian
Affiliation:
Center of Excellence in Robotics and Control, Advanced Robotics and Automated Systems Lab, Department of Mechanical Eng, K. N. Toosi Univ of Technology, Tehran, Iran E-mail: [email protected]
*
*Corresponding author. E-mail: [email protected]
Get access Rights & Permissions [Opens in a new window]

Summary

Legged robots may become unstable when subjected to unexpected disturbances such as external pushes and environmental irregularities mostly while moving on natural terrains. To enhance the mobility performance, legged robots should be able to keep or restore their balanced configuration when a sudden disturbance is exerted. The aim of this article is to design a controller for a quadruped robot to restore its balanced configuration despite exerting external pushes. This is achieved based on developing a full-dynamics model of the robot moving over even and uneven terrains. The proposed controller is based on a PD module which calculates the required accelerations for restoring the robot equilibrium. However, these accelerations may make the robot unstable and also cause the slippage of stance feet. Therefore, an optimization algorithm is used to compute the maximum admissible accelerations. The constraints of the optimization problem are the conditions which guarantee the robot stability and the stance feet slippage avoidance. The optimization algorithm is transformed into a linear constrained least-squares problem to be solved in real-time. The main contributions of this article are the development of a push recovery algorithm for quadruped robots and also the introduction of an appropriate condition which guarantees the stability of the robot even on uneven terrains. This stability condition is developed based on a full-dynamics model of the robot. The proposed algorithm is applied on an 18-DOF quadruped robot when the robot is standing over both even and uneven terrains. The obtained results show that the robot can successfully restore its balanced configuration by precise adjustment of the position and orientation of its main body while a massive external disturbance is exerted.

Keywords

Quadruped robotsPush recoveryDynamic stabilityWhole-body dynamicsUneven terrains
Type
Articles
Information
Robotica , Volume 35 , Issue 8 , August 2017 , pp. 1670 - 1689
Copyright
Copyright © Cambridge University Press 2016 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

1. Yu, W., Bao, G. and Wang, Z., “Balance Recovery for Humanoid Robot in the Presence of Unknown External Push,” Proceedings of the International Conference on Mechatronics and Automation, ICMA, Changchun, China (2009) pp. 1928–1933.Google Scholar
2. Yoshida, Y., Takeuchi, K., Miyamoto, Y., Sato, D. and Nenchev, D., “Postural balance strategies in response to disturbances in the frontal plane and their implementation with a humanoid robot systems,” IEEE Trans. Man Cybern.: Syst. 44 (6), 692–704 (2014).Google Scholar
3. Nenchev, D. N. and Nishio, A., “Ankle and hip strategies for balance recovery of a biped subjected to an impact,” Robotica 26 (05), 643–653 (2008).CrossRefGoogle Scholar
4. Pratt, J., Carff, J., Drakunov, S. and Goswami, A., “Capture Point: A Step Toward Humanoid Push Recovery,” Proceedings of IEEE-RAS International Conference on Humanoid Robots, Genova, Italy (2006) pp. 200–207.Google Scholar
5. Stephens, B. J. and Atkeson, C. G., “Push Recovery by Stepping for Humanoid Robots with Force Controlled Joints,” 10th IEEE-RAS International Conference on Humanoid Robots (Humanoids), Nashville, TN (2010) pp. 52–59.Google Scholar
6. Goswami, A., Yun, S.-k., Nagarajan, U., Lee, S.-H., Yin, K. and Kalyanakrishnan, S., “Direction-changing fall control of humanoid robots: Theory and experiments,” Auton. Robots 36 (3), 199–223 (2014).CrossRefGoogle Scholar
7. Yun, S.-k. and Goswami, A., “Tripod Fall: Concept and Experiments of a Novel Approach to Humanoid Robot Fall Damage Reduction,” Proceedings of IEEE International Conference on Robotics and Automation, Hong Kong (2014) pp. 2799–2805.Google Scholar
8. Chung, J.-W., Lee, I.-H., Cho, B.-K. and Oh, J.-H., “Posture stabilization strategy for a trotting point-foot quadruped robot,” J. Intell. Robot. Syst. 72 (3–4), 325–341 (2013).CrossRefGoogle Scholar
9. Raibert, M., “BigDog, the Rough-Terrain Quadruped Robot,” In Chung, M. (ed.), Proceedings of the 17th IFAC World Congress, COEX, Korea, South (2008) pp. 10822–10825.Google Scholar
10. Stephens, B., “Humanoid Push Recovery,” Proceedings of IEEE-RAS International Conference on Humanoid Robots, Pittsburgh, PA (2007) pp. 589–595.Google Scholar
11. Urata, J., Nshiwaki, K., Nakanishi, Y., Okada, K., Kagami, S. and Inaba, M., “Online Walking Pattern Generation for Push Recovery and Minimum Delay to Commanded Change of Direction and Speed,” IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), (2012), pp. 3411–3416.Google Scholar
12. Prahlad, V., Dip, G. and Meng-Hwee, C., “Disturbance rejection by online ZMP compensation,” Robotica 26 (01), 9–17 (2008).CrossRefGoogle Scholar
13. Wieber, P.-B., “Trajectory Free Linear Model Predictive Control for Stable Walking in the Presence of Strong Perturbations,” IEEE-RAS International Conference on Humanoid Robots, IEEE, Genova, Italy (2006) pp. 137–142.Google Scholar
14. Aftab, Z., Robert, T. and Wieber, P.-B., “Ankle, Hip and Stepping Strategies for Humanoid Balance Recovery with a Single Model Predictive Control Scheme,” Proceedings of IEEE-RAS International Conference on Humanoid Robots, Osaka, Japan (2012) pp. 159–164.Google Scholar
15. Atkeson, C. G. and Stephens, B., “Multiple Balance Strategies from One Optimization Criterion,” Proceedings of 7th IEEE-RAS International Conference on Humanoid Robots, IEEE (2007) pp. 57–64.Google Scholar
16. Komura, T., Leung, H., Kudoh, S. and Kuffner, J., “A Feedback Controller for Biped Humanoids that Can Counteract Large Perturbations During Gait,” Proceedings of the 2005 IEEE International Conference on Robotics and Automation, ICRA 2005. (2005) pp. 1989–1995.Google Scholar
17. Wang, Y., Xiong, R., Zhu, Q. and Chu, J., “Compliance Control for Standing Maintenance of Humanoid Robots Under Unknown External Disturbances,” IEEE International Conference on Robotics and Automation (ICRA), Hong Kong (2014) pp. 2297–2304.CrossRefGoogle Scholar
18. Hyon, S., Hale, J. G. and Cheng, G., “Full-body compliant human–humanoid interaction: Balancing in the presence of unknown external forces,” IEEE Trans. Robot. 23 (5), 884–898 (2007).CrossRefGoogle Scholar
19. Stephens, B. J. and Atkeson, C. G., “Dynamic Balance Force Control for Compliant Humanoid Robots,” Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems, Taipei (2010) pp. 1248–1255.Google Scholar
20. Kim, Y.-J., Lee, J.-Y. and Lee, J.-J., “A force-resisting balance control strategy for a walking biped robot under an unknown, continuous force,” Robotica, 1–22 (2014).Google Scholar
21. Ott, C., Roa, M. A. and Hirzinger, G., “Posture and Balance Control for Biped Robots Based on Contact Force Optimization,” Proceedings of IEEE-RAS International Conference on Humanoid Robots, Bled, Slovenia (2011). pp. 26–33.Google Scholar
22. Henze, B., Ott, C. and Roa, M. A., “Posture and Balance Control for Humanoid Robots in Multi-contact Scenarios Based on Model Predictive Control,” Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems, Chicago, IL (2014) pp. 3253–3258.Google Scholar
23. Kajita, S., Kanehiro, F., Kaneko, K., Fujiwara, K., Harada, K., Yokoi, K. and Hirukawa, H., “Resolved Momentum Control: Humanoid Motion Planning Based on the Linear and Angular Momentum,” Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems, vol. 1642 (2003) pp. 1644–1650.Google Scholar
24. Macchietto, A., Zordan, V. and Shelton, C. R., “Momentum control for balance,” ACM Trans. Graph. 28 (3), 80–90 (2009).CrossRefGoogle Scholar
25. Lee, S.-H. and Goswami, A., “A momentum-based balance controller for humanoid robots on non-level and non-stationary ground,” Auton. Robot. 33 (4), 399–414 (2012).CrossRefGoogle Scholar
26. Herzog, A., Righetti, L., Grimminger, F., Pastor, P. and Schaal, S., “Momentum-based balance control for torque-controlled humanoids,” technical report, Computing Research Repository, arXiv preprint abs/1305.2042 (2013) pp. 1–7.Google Scholar
27. Chen, X., Huang, Q., Yu, Z. and Lu, Y., “Robust push recovery by whole-body dynamics control with extremal accelerations,” Robotica 32 (03), 467–476 (2014).CrossRefGoogle Scholar
28. Barasuol, V., Buchli, J., Semini, C., Frigerio, M., De Pieri, E. R. and Caldwell, D. G., “A Reactive Controller Framework for Quadrupedal Locomotion on Challenging Terrain,” IEEE International Conference on Robotics and Automation (ICRA), Karlsruhe, Germany (2013) pp. 2554–2561.Google Scholar
29. Maufroy, C., Kimura, H. and Takase, K., “Stable Dynamic Walking of a Quadruped via Phase Modulations Against Small Disturbances,” IEEE International Conference on Robotics and Automation, ICRA'09. (2009) pp. 4201–4206.Google Scholar
30. Havoutis, I., Semini, C., Buchli, J. and Caldwell, D. G., “Quadrupedal Trotting with Active Compliance,” Proceedings of IEEE International Conference on Mechatronics, IEEE, Vicenza, Italy (2013) pp. 610–616.Google Scholar
31. Gehring, C., Coros, S., Hutter, M., Bloesch, M., Hoepflinger, M. A. and Siegwart, R., “Control of Dynamic Gaits for a Quadrupedal Robot,” IEEE International Conference on Robotics and Automation (ICRA), IEEE, Karlsruhe, Germany (2013) pp. 3287–3292.Google Scholar
32. Moosavian, S. A. A. and Papadopoulos, E., “Explicit dynamics of space free-flyers with multiple manipulators via SPACEMAPLE,” Adv. Robot. 18 (2), 223–244 (2004).CrossRefGoogle Scholar
33. Mistry, M., Buchli, J. and Schaal, S., “Inverse Dynamics Control of Floating Base Systems Using Orthogonal Decomposition,” Proceedings of IEEE International Conference on Robotics and Automation, (2010) pp. 3406–3412.Google Scholar
34. Aghili, F., “A unified approach for inverse and direct dynamics of constrained multibody systems based on linear projection operator: Applications to control and simulation,” IEEE Trans. Robot. 21 (5), 834–849 (2005).CrossRefGoogle Scholar
35. Hutter, M., Gehring, C., Bloesch, M., Hoepflinger, M. A., Remy, C. D., and Siegwart, R., “StarlETH: A Compliant Quadrupedal Robot for Fast, Efficient, and Versatile Locomotion,” In: 15th International Conference on Climbing and Walking Robot, USA (2012).Google Scholar