Hostname: page-component-cd9895bd7-dk4vv Total loading time: 0 Render date: 2024-12-23T11:11:48.876Z Has data issue: false hasContentIssue false
  • English
  • Français

Active disturbance rejection for walking bipedal robots using the acceleration of the upper limbs

Published online by Cambridge University Press:  27 February 2014

Joshua Hill  and
Farbod Fahimi
Joshua Hill
Affiliation:
Department of Mechanical & Aerospace Engineering, UAHuntsville, Huntsville, AL 35805, USA
Farbod Fahimi*
Affiliation:
Department of Mechanical & Aerospace Engineering, UAHuntsville, Huntsville, AL 35805, USA
*
*Corresponding author. E-mail: [email protected]
Get access Rights & Permissions [Opens in a new window]

Summary

A disturbance rejection controller is proposed based on the general dynamic model of 3D biped robots. For the first time, with this proposed approach, not only the Zero Moment Point (ZMP) location remains unchanged in presence of disturbances but also the longitudinal and lateral ground reaction forces and the vertical twist moment remain unchanged. This way, slipping as well as tipping is prevented by the controller. The swing phase of the robot's walking gait is considered. An integral sliding mode architecture is chosen for the disturbance rejection. The support forces and moments of the stance foot are the control outputs. The acceleration of the arm/body joints are chosen as the inputs. During the disturbance rejection, the leg joints remain at their desired trajectory. Since the leg joint trajectories are unaffected, the robot is still able to complete its step as planned, even when bounded disturbances are experienced. For simulations, the general method is applied to an 18-degree of freedom biped humanoid robot. Simulations show that the controller successfully mitigates bounded disturbances and maintains all of the support reactions extremely close to their desired values. Consequently, the shift in the position of the ZMP is negligible, and the robot foot does not slip.

Keywords

BipedsControl of robotic systemsHumanoid robotsMotion planningLegged robots
Type
Articles
Information
Robotica , Volume 33 , Issue 2 , February 2015 , pp. 264 - 281
Copyright
Copyright © Cambridge University Press 2014 

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.McGeer, T., “Passive dynamic walking,” Int. J. Robot. Res. 9 (2), 62–82 (1990).Google Scholar
2.Liu, Z., Zhang, A., Tian, Y., Zhang, P. and Gao, D., “Further Analysis of the Kneed Passive-Dynamic Biped Robot,” Proceedings of Chinese Control and Decision Conference (CCDC 2010), Xuzhou, China (2010) pp. 1777–1782.Google Scholar
3.Hitomi, K., Shibata, T., Nakamura, Y. and Ishii, S., “Reinforcement learning for quasi-passive dynamic walking of an unstable biped robot,” Robot. Auton. Syst. 54 (12), 982–988 (2006).Google Scholar
4.Vukobratovic, M. and Borovac, B., “Zero moment point – thirty five years of its life,” Int. J. Humanoid Robot 1 (1), 157–173 (2004).Google Scholar
5.Zhang, R., Vadakkepat, P. and Chew, C. M., “Motion Planning for Biped Robot Climbing Stairs,” Proceedings of FIRA Robot World Congress, Vienna, Austria (Oct. 1–3, 2003) pp. 1–6.Google Scholar
6.Hirai, K., Hirose, Y. H. M. and Takenaka, T., “The Development of Honda Humanoid Robot,” Proceedings of the IEEE International Conference on Robotics and Automation, vol. 2 (1998) pp. 1321–1326.Google Scholar
7.Prahlad, V., Dip, G. and Meng-Hwee, C., “Disturbance rejection by online ZMP compensation,” Robotica 26, 9–17 (2008).Google Scholar
8.Naksuk, N., Lee, C. S. G. and Rietdyk, S., “Whole-Body Human-to-Humanoid Motion Transfer,” Proceedings of the 5th IEEE-RAS International Conference on Humanoid Robots, Tsukuba, Japan, vol. 2005 (2005) pp. 104–109.Google Scholar
9.Sano, A. and Furusho, J., “Realization of Natural Dynamic Walking Using the Angular Momentum Information,” Proceedings of the IEEE International Conference on Robotics and Automation, vol. 3 (May 1990) pp. 1476–1481.Google Scholar
10.Okumura, Y., Tawara, T., Endo, K., Furuta, T. and Shimizu, M., “Real-Time ZMP Compensation for Biped Walking Robot Using Adaptive Inertia Force Control,” Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2003), Piscataway, NJ, vol. 1 (2003) pp. 335–339.Google Scholar
11.Park, I.-W., Kim, J.-Y. and Oh, J.-H., “Online walking pattern generation and its application to a biped humanoid robot – KHR-3 (HUBO),” Adv. Robot. 22 (2–3), 159–190 (2008).CrossRefGoogle Scholar
12.Lim, H. O., Kaneshima, Y. and Takanishi, A., “Online Walking Pattern Generation for Biped Humanoid Robot with Trunk,” Proceedings of IEEE International Conference on Robotics and Automation, vol. 3 (2002) pp. 3111–3116.Google Scholar
13.Yamaguchi, J., Soga, E., Setiawan, S. A., Aoyagi, D., Nagamatsu, A. and Takanishi, A., “Development of a bipedal humanoid robot presupposing various whole body motions,” Adv. Robot. 13 (3), 297–299 (1999).Google Scholar
14.Mitobe, K., Capi, G. and Nasu, Y., “Control of walking robots based on manipulation of the zero moment point,” Robotica 18 (6), 651–657 (2000).Google Scholar
15.Vermeulen, J., Verrelst, B., Lefeber, D., Kool, P. and Vanderborght, B., “A real-time joint trajectory planner for dynamic walking bipeds in the sagittal plane,” Robotica 23 (6), 669–680 (2005).Google Scholar
16.Park, J. H. and Chung, H., “ZMP Compensation by Online Trajectory Generation for Biped Robots,” Proceedings of IEEE International Conference on Robotics and Automation, vol. 4 (Oct. 10–15, 1999) pp. 960–965.Google Scholar
17.Sugihara, T., Nakamura, Y. and Inoue, H., “Realtime Humanoid Motion Generation Through ZMP Manipulation Based on Inverted Pendulum Control,” Proceedings of the IEEE International Conference on Robotics and Automation, Washington, DC, vol. 2 (2002) pp. 1404–1409.Google Scholar
18.Erbatur, K. and Kurt, O., “Humanoid Walking Robot Control with Natural ZMP References,” Proceedings of the Industrial Electronics Conference (IECON), Paris, France (2006) pp. 4100–4106.Google Scholar
19.Kajita, S., Kanehiro, F., Kaneko, K., Yokoi, K. and Hirukawa, H., “The 3D Linear Inverted Pendulum Mode: A Simple Modeling for a Biped Walking Pattern Generation,” Proceedings of the IEEE International Conference on Intelligent Robots and Systems, Maui, HI, vol. 1 (2001) pp. 239–240.Google Scholar
20.Lee, B.-J., Stonier, D., Kim, Y.-D., Yoo, J.-K. and Kim, J.-H., “Modifiable Walking Pattern Generation Using Real-Time ZMP Manipulation for Humanoid Robots,” Proceedings of the IEEE International Conference on Intelligent Robots and Systems, San Diego, CA (2007) pp. 4221–4226.Google Scholar
21.Hammam, G. B., Orin, D. and Dariush, B., “Whole-Body Humanoid Control from Upper-Body Task Specifications,” Proceedings of IEEE International Conference on Robotics and Automation (ICRA) (May 3–7, 2010) pp. 3398–3405.Google Scholar
22.Hofmann, A., Massaquoi, S., Popovic, M. and Herr, H., “A Sliding Controller for Bipedal Balancing Using Integrated Movement of Contact and Non-Contact Limbs,” Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Sendai, Japan, vol. 2 (2004) pp. 1952–1959.Google Scholar
23.Park, J., “Synthesis of natural arm swing motion in human bipedal walking,” J. Biomech. 41 (7), 1417–1426 (2008).Google Scholar
24.Zaoui, C., Bruneau, O., Ouezdou, F. and Maalej, A., “Simulations of the dynamic behavior of a bipedal robot with trunk and arms subjected to 3D external disturbances in a vertical posture, during walking and during object handling,” Multibody Syst. Dyn. 21 (3), 261–280 (2009).Google Scholar
25.Yin, C.-B., Zhou, Q.-M., Xu, H.-H. and Yang, M., “Stability maintenance of a humanoid robot under external disturbance,” Kongzhi yu Juece (Control Decis.) 21 (6), 619–624 (2006).Google Scholar
26.Erbatur, K., Seven, U., Taskiran, E., Koca, O., Yilmaz, M., Unel, M., Kiziltas, G., Sabanovic, A. and Onat, A., “SURALP: A New Full-Body Humanoid Robot Platform,” 2009 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2009), St. Louis, MO (2009) pp. 4949–4954.Google Scholar
27.Cao, W.-J. and Xu, J.-X., “Nonlinear integral-type sliding surface for both matched and unmatched uncertain systems,” IEEE Trans. Autom. Control 49 (8), 1355–1360 (2004).Google Scholar
28.Castanos, F. and Fridman, L., “Analysis and design of integral sliding manifolds for systems with unmatched perturbations,” IEEE Trans. Autom. Control 51 (5), 853–858 (2006).CrossRefGoogle Scholar
29.Slotine, J.-J. E. and Li, W., Applied Nonlinear Control (Prentice-Hall, Upper Saddle River, NJ, 1991), Ch. 9, pp. 397–402.Google Scholar
30.Nikkhah, M., Ashrafiuon, H. and Fahimi, F., “Robust control of underactuated bipeds using sliding modes,” Robotica 25 (3), 367–374 (2007).Google Scholar
31.Moosavian, S. A. A., Alghooneh, M. and Takhmar, A., “Cartesian approach for gait planning and control of biped robots on irregular surfaces,” Int. J. Humanoid Robot. 6 (4), 675–697 (2009).Google Scholar
32.Tu, K.-Y. and Liu, M.-S., “Planning of sagittal gait of biped robots based on minimum motion energy,” Int. J. Humanoid Robot. 7 (4), 635–667 (2010).CrossRefGoogle Scholar