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Control of a compass gait walker based on energy regulation using ankle push-off and foot placement

Published online by Cambridge University Press:  01 April 2014

Pranav A. Bhounsule
Pranav A. Bhounsule*
Affiliation:
Disney Research Pittsburgh, Pittsburgh, PA 15213, USA
*
*Corresponding author. E-mail: [email protected]
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Summary

In this paper, we present a theoretical study on the control of a compass gait walker using energy regulation between steps. We use a return map to relate the mid-stance robot kinetic energy between steps with two control inputs, namely, foot placement and ankle push-off. We show that by regulating robot kinetic energy between steps using the two control inputs, we are able to (1) generate a wide range of walking speeds and stride lengths, including average human walking; (2) cancel the effect of external disturbance fully in a single step (dead-beat control); and (3) switch from one periodic gait to another in a single step. We hope that insights from this control methodology can help develop robust controllers for practical bipedal robots.

Keywords

BipedsLegged robotsMotion planningHumanoid robotsControl of robotic systems
Type
Articles
Information
Robotica , Volume 33 , Issue 6 , July 2015 , pp. 1314 - 1324
Copyright
Copyright © Cambridge University Press 2014 

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References

1. McGeer, T., “Passive dynamic walking” Int. J. Robot. Res. 9 (2), 62–82 (1990).Google Scholar
2. Garcia, M., Chatterjee, A., Ruina, A. and Coleman, M., “The simplest walking model: Stability, complexity, and scaling,” J. Biomech. Eng. 120 (2), 281–288 (1998).Google Scholar
3. Goswami, A., Thuilot, B. and Espiau, B., “A study of the passive gait of a compass-like biped robot symmetry and chaos,” Int. J. Robot. Res. 17 (12), 1282–1301 (1998).Google Scholar
4. Asano, F., Yamakita, M. and Furuta, K., “Virtual Passive Dynamic Walking and Energy-Based Control Laws” International Conference on Intelligent Robots and Systems, Takamatsu, Japan (Oct. 30–Nov. 5, 2000) pp. 1149–1154.Google Scholar
5. Goswami, A., Espiau, B. and Keramane, A., “Limit cycles in a passive compass gait biped and passivity-mimicking control laws,” Auton. Robots 4 (3), 273–286 (1997).Google Scholar
6. Spong, M. W., “Passivity Based Control of the Compass Gait Biped,” Proceedings of IFAC World Congress, Beijing, China (Jul. 5–9, 1999) pp. 19–24.Google Scholar
7. Byl, K. and Tedrake, R.. “Approximate Optimal Control of the Compass Gait on Rough Terrain,” International Conference on Robotics and Automation, Pasadena, California (May 19–23, 2008) pp. 1258–1263.Google Scholar
8. Pratt, J., Carff, J., Drakunov, S. and Goswami, A., “Capture Point: A Step Toward Humanoid Push Recovery,” International Conference on Humanoid Robots, Genova, Italy (Dec. 4–6, 2006) pp. 200–207.Google Scholar
9. Kajita, S. and Tani, K., “Experimental Study of Biped Dynamic Walking in the Linear Inverted Pendulum Mode,” In: International Conference on Robotics and Automation, Nagoya, Aichi, Japan (May 21–27, 1995) pp. 2885–2891.Google Scholar
10. Wight, D. L., Kubica, E. G. and Wang, D. W., “Introduction of the foot placement estimator: A dynamic measure of balance for bipedal robotics,” J. Comput. Nonlinear Dyn. 3 (1), 011 009–1:10 (2008).Google Scholar
11. Kuo, A. D., “Energetics of actively powered locomotion using the simplest walking model,” J. Biomech. Eng. 124 (1), 113–120 (2002).Google Scholar
12. Kuo, A. D., “A simple model of bipedal walking predicts the preferred speed–step length relationship,” J. Biomech. Eng. 123, 264–269 (2001).Google Scholar
13. Ruina, A., Bertram, J. E. and 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).Google Scholar
14. Kuo, A. D. and Donelan, J. M., “Dynamic principles of gait and their clinical implications,” Phys. Ther. 90 (2), 157–174 (2010).Google Scholar
15. Bhounsule, P. A., A Controller Design Framework for Bipedal Robots: Trajectory Optimization and Event-Based Stabilization Ph.D. Thesis, Cornell University, Ithaca, NY (2012).Google Scholar
16. Bhounsule, P. A., Cortell, J., Grewal, A., Hendriksen, B., Karrsen, J. G. D., Paul, C. and Ruina, A., “Low-bandwidth reflex-based control for lower power walking: 65 km on a single battery charge,” Int. J. Robot. Res. (in press).Google Scholar
17. Ruina, A., “Cornell ranger 2011, 4-legged bipedal robot. Available at: http://ruina.tam.cornell.edu/research/topics/locomotion_and_robotics/ranger/Ranger2011/ (2013, June), online. (Or Google search for Cornell ranger).Google Scholar
18. Ralston, H. J., “Energy–speed relation and optimal speed during level walking,” Int. Zeitschrift für angewandte Physiologie einschließlich Arbeitsphysiologie 17 (4), 277–283 (1958).Google Scholar
19. Alexander, R. and Maloiy, G. M. O., “Stride lengths and stride frequencies of primates,” J. Zoology 202 (4), 577–582 (1984).Google Scholar
20. Strogatz, S., Nonlinear Dynamics and Chaos: With Applications to Physics, Biology, Chemistry and Engineering (Perseus Books, New York, NY, 2001).Google Scholar
21. Antsaklis, P. J. and Michel, A. N., Linear Systems (Birkhauser, Boston, MA, 1997).Google Scholar
22. Carver, S. G., Cowan, N. J. and Guckenheimer, J. M., “Lateral stability of the spring-mass hopper suggests a two-step control strategy for running,” Chaos Interdiscip. J. Nonlinear Sci. 19 (2), 026106–026106 (2009).Google Scholar
23. Wu, A. and Geyer, H., “The 3-D spring–mass model reveals a time-based deadbeat control for highly robust running and steering in uncertain environments,” IEEE Trans. Robot. 99, 1–11 (2013).Google Scholar
24. Saglam, C. O. and Byl, K., “Switching Policies for Metastable Walking,” International Conference on Decisions and Control, Florence, Italy, (Dec. 10–13, 2013) pp. 977–983.Google Scholar
25. Srinivasan, M. and Ruina, A., “Computer optimization of a minimal biped model discovers walking and running,” Nature 439 (7072), 72–75 (2005).Google Scholar