Hostname: page-component-cd9895bd7-gxg78 Total loading time: 0 Render date: 2024-12-27T00:28:20.543Z Has data issue: false hasContentIssue false
  • English
  • Français

Heel-strike and toe-off motions optimization for humanoid robots equipped with active toe joints

Published online by Cambridge University Press:  08 March 2018

Majid Sadedel ,
Aghil Yousefi-Koma ,
Majid Khadiv  and
Faezeh Iranmanesh
Majid Sadedel
Affiliation:
Center of Advanced Systems and Technologies (CAST), School of Mechanical Engineering, College of Engineering, University of Tehran, Tehran, Iran
Aghil Yousefi-Koma*
Affiliation:
Center of Advanced Systems and Technologies (CAST), School of Mechanical Engineering, College of Engineering, University of Tehran, Tehran, Iran
Majid Khadiv
Affiliation:
Center of Excellence in Robotics and Control, Advanced Robotics & Automated Systems (ARAS) Lab, Department of Mechanical Engineering, K. N. Toosi University of Technology, Tehran, Iran
Faezeh Iranmanesh
Affiliation:
Center of Advanced Systems and Technologies (CAST), School of Mechanical Engineering, College of Engineering, University of Tehran, Tehran, Iran
*
*Corresponding author. E-mail: aykoma@ut.ac.ir
Get access Rights & Permissions [Opens in a new window]

Summary

In this paper, a walking pattern optimization procedure is implemented to yield the optimal heel-strike and toe-off motions for different goal functions. To this end, first, a full dynamic model of a humanoid robot equipped with active toe joints is developed. This model consists of two parts: multi-body dynamics of the robot which is obtained by Lagrange and Kane methods and power transmission dynamic model which is developed using system identification approach. Then, a gait planning routine is presented and consistent parameters are specified. Several simulations and experimental tests are carried out on SURENA III humanoid robot which is designed and fabricated at the Center of Advanced Systems and Technologies located in the University of Tehran. Afterward, a genetic algorithm optimization is adopted to compute the optimal walking patterns for five different goal functions including energy consumption, stability margin, joint velocity, joint torque and required friction coefficient. Also, several parametric analyses are performed to characterize the effects of heel-strike and toe-off angle and toe link mass and length on these five goal functions. Finally, it is concluded that walking pattern without heel-strike and toe-off motions requires less friction coefficient than the pattern with heel-strike and toe-off motions. Also, heavier toe link lowers tip-over instability and slippage occurrence possibility, but requires more energy consumption and joint torque.

Keywords

Active toe jointGait optimizationHeel-strike motionToe-off motionGenetic algorithm
Type
Articles
Information
Robotica , Volume 36 , Issue 6 , June 2018 , pp. 925 - 944
Copyright
Copyright © Cambridge University Press 2018 

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. Tlalolini, D., Chevallereau, C. and Aoustin, Y., “Comparison of different gaits with rotation of the feet for a planar biped,” Robot. Auton. Sys. 57, 371–383 (2009).CrossRefGoogle Scholar
2. Tlalolini, D., Chevallereau, C. and Aoustin, Y., “Human-like walking: Optimal motion of a bipedal robot with toe-rotation motion,” IEEE/ASME Trans. Mechatronics 16, 310–320 (2011).Google Scholar
3. Choi, J. and Grizzle, J., “Planar Bipedal Walking with Foot Rotation,” Proceedings of the 2005 American Control Conference, (IEEE, 2005), pp. 4909–4916.Google Scholar
4. Nishiwaki, K., Kagami, S., Kuniyoshi, Y., Inaba, M. and Inoue, H., “Toe Joints That Enhance Bipedal and Fullbody Motion of Humanoid Robots,” Proceedings of the ICRA'02, IEEE International Conference on Robotics and Automation, (IEEE, 2002), pp. 3105–3110.Google Scholar
5. Buschmann, T., Lohmeier, S. and Ulbrich, H., “Humanoid robot lola: Design and walking control,” Physiology-Paris 103, 141–148 (2009).Google Scholar
6. Tajima, R., Honda, D. and Suga, K., “Fast Running Experiments Involving a Humanoid Robot,” IEEE International Conference on Robotics and Automation, ICRA'09 (IEEE, 2009), pp. 1571–1576.Google Scholar
7. Miura, K., Morisawa, M., Kanehiro, F., Kajita, S., Kaneko, K. and Yokoi, K., “Human-Like Walking with Toe Supporting for Humanoids,” IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), (IEEE, 2011), pp. 4428–4435.CrossRefGoogle Scholar
8. Ogura, Y., Shimomura, K., Kondo, A., Morishima, A., Okubo, T., Momoki, S., Lim, H. and Takanishi, A., “Human-Like Walking with Knee Stretched, Heel-Contact and Toe-Off Motion by a Humanoid Robot,” IEEE/RSJ International Conference on Intelligent Robots and Systems (IEEE, 2006), pp. 3976–3981.Google Scholar
9. Doubliez, P., Bruneau, O. and Ouezdou, F., “Force control of the redundant leg of a biped robot to produce large inertial effects for crossing obstacles,” Int. J. Humanoid Robot. 9, 125–130 (2012).CrossRefGoogle Scholar
10. Ki, A., Cheol, L. and Jo, G., “Development of a Biped Robot with Toes to Improve Gait Pattern,” IEEE/ASME International Conference on Advanced Intelligent Mechatronics, (IEEE, 2003), pp. 729–734.Google Scholar
11. Wang, L., Yu, Z., Meng, Q. and Zhang, Z., “Influence Analysis of Toe-Joint on Biped Gaits,” IEEE International Conference on Mechatronics and Automation, (IEEE, 2006), pp. 1631–1635.Google Scholar
12. Kouchaki, E. and Sadigh, M. J., “Effect of Toe-Joint Bending on Biped Gait Performance,” IEEE International Conference on Robotics and Biomimetics (ROBIO), (IEEE, 2010), pp. 697–702.Google Scholar
13. Handharu, N., Yoon, J. and Kim, G., “Gait Pattern Generation with Knee Stretch Motion for Biped Robot Using Toe and Heel Joints,” 8th IEEE-RAS International Conference on Humanoids, (IEEE, 2008), pp. 265–270.CrossRefGoogle Scholar
14. Sadigh, M. J., Kouchaki, E. and Wu, C., “Effects of constraints on standing balance of a biped with toe-joints,” Int. J. Humanoid Robot. 09, 125–136 (2012).Google Scholar
15. Sellaouti, R., Stasse, O., Kajita, S., Yokoi, K. and Kheddar, A., “Faster and Smoother Walking of Humanoid Hrp-2 with Passive Toe Joints,” IEEE/RSJ International Conference on Intelligent Robots and Systems, (IEEE, 2006), pp. 4909–4914.Google Scholar
16. Kajita, S., Kaneko, K., Morisawa, M., Nakaoka, S. and Hirukawa, H., “Zmp-Based Biped Running Enhanced by Toe Springs,” IEEE International Conference on Robotics and Automation, (IEEE, 2007), pp. 3963–3969.CrossRefGoogle Scholar
17. Kumar, R., Handharu, N., Jungwon, Y. and Gap-soon, K., “Hybrid Toe and Heel Joints for Biped/Humanoid Robots for Natural Gait,” Proceeding of the ICCAS'07, International Conference on Control, Automation and Systems, (ICCAS, 2007), pp. 2687–2692.Google Scholar
18. Channon, P., Hopkins, S. and Pham, D., “Derivation of optimal walking motions for a bipedal walking robot,” Robotica 10, 165–172 (1992).Google Scholar
19. Chevallereau, C. and Aoustin, Y., “Optimal reference trajectories for walking and running of a biped robot,” Robotica 19, 557–569 (2001).Google Scholar
20. Dau, V., Chew, C. and Poo, A., “Achieving energy-efficient bipedal walking trajectory through ga-based optimization of key parameters,” Int. J. Humanoid Robot. 6, 609–629 (2009).Google Scholar
21. Capi, G., Nasu, Y., Barolli, L., Mitobe, K. and Takeda, K., “Application of genetic algorithms for biped robot gait synthesis optimization during walking and going up-stairs,” Adv. Robot. 15, 675–694 (2001).Google Scholar
22. Park, J. and Choi, M., “Generation of an optimal gait trajectory for biped robots using a genetic algorithm,” JSME Int. J. Ser. C Mech. Syst. Mach. Elements Manuf. 47, 715–721 (2004).Google Scholar
23. Rostami, M. and Bessonnet, G., “Sagittal gait of a biped robot during the single support phase. Part 2: Optimal motion,” Robotica 19, 241–253 (2001).Google Scholar
24. Bessonnet, G., Seguin, P. and Sardain, P., “A parametric optimization approach to walking pattern synthesis,” The Int. J. Robot. Res. 24, 523–536 (2005).Google Scholar
25. Kwon, O. and Park, J., “Asymmetric trajectory generation and impedance control for running of biped robots,” Auton. Robots 26, 47–78 (2009).Google Scholar
26. Aoi, S. and Tsuchiya, K., “Generation of bipedal walking through Interactions among the robot dynamics, the oscillator dynamics, and the environment: Stability characteristics of a five-link planar biped robot,” Auton. Robots 30, 123–141 (2011).Google Scholar
27. Aoi, S. and Tsuchiya, K., “Locomotion control of a biped robot using nonlinear oscillators,” Auton. Robots 19, 219–232 (2005).Google Scholar
28. Sadedel, M., Yousefi-Koma, A. and Khadiv, M., “Offline Path Planning, Dynamic Modeling and Gait Optimization of a 2d Humanoid Robot,” 2nd RSI/ISM International Conference on Robotics and Mechatronics (ICRoM), (IEEE, 2014), pp. 131–136.Google Scholar
29. Khadiv, M., Moosavian, S. A. and Sadedel, M., “Dynamics Modeling of Fully-Actuated Humanoids with General Robot-Environment Interaction,” 2nd RSI/ISM International Conference on Robotics and Mechatronics (ICRoM), (IEEE, 2014), pp. 233–238.CrossRefGoogle Scholar
30. Ugurlu, B., Saglia, J., Tsagarakis, N. and Caldwell, D., “Yaw moment compensation for bipedal robots via intrinsic angular momentum constraint,” Int. J. Humanoid Robot. 9, 1250033 (2012).CrossRefGoogle Scholar
31. Carbone, G., Ogura, Y., Lim, H., Takanishi, A. and Ceccarelli, M., “Dynamic simulation and experiments for the design of a new 7-dofs biped walking leg module,” Robotica 22, 41–50 (2004).Google Scholar
32. Wang, T., Chevallereau, C. and Rengifo, C., “Walking and steering control for a 3d biped robot considering ground contact and stability,” Robot. Auton. Syst. 60, 962–977 (2012).Google Scholar
33. Aoustin, Y. and Formalskii, A., “3d walking biped: Optimal swing of the arms,” Multibody Syst. Dyn. 32, 55–66 (2014).Google Scholar
34. Kajita, S. and Tani, K., “Study of Dynamic Biped Locomotion on Rugged Terrain-Derivation and Application of the Linear Inverted Pendulum Mode,” Proceedings of the 1991 IEEE International Conference on Robotics and Automation, (IEEE, 1991), pp. 1405–1411.Google Scholar
35. Kajita, S., Kanehiro, F., Kaneko, K., Fujiwara, K., Harada, K., Yokoi, K. and Hirukawa, H., “Biped Walking Pattern Generation by Using Preview Control of Zero-Moment Point,” Proceedings of the ICRA'03. IEEE International Conference on Robotics and Automation, (IEEE, 2003), pp. 1620–1626.Google Scholar
36. Park, J. and Kim, K., “Biped Robot Walking Using Gravity-Compensated Inverted Pendulum Mode and Computed Torque Control,” Proceedings. 1998 IEEE International Conference on Robotics and Automation, (IEEE, 1998), pp. 3528–3533.Google Scholar
37. Sato, T., Sakaino, S. and Ohnishi, K., “Real-time walking trajectory generation method with three-mass models at constant body height for three-dimensional biped robots,” IEEE Trans. Ind. Electron. 58, 376–383 (2011).Google Scholar
38. Huang, Q., Yokoi, K., Kajita, S., Kaneko, K., Arai, H., Koyachi, N. and Tanie, K., “Planning walking patterns for a biped robot,” IEEE Trans. Robot. Autom. 17, 280–289 (2001).Google Scholar
39. Baruh, H., Analytical Dynamics (WCB/McGraw-Hill, Boston, 1999).Google Scholar
40. Vukobratović, M. and Borovac, B., “Zero-moment point-thirty five years of its life,” Int. J. Humanoid Robot. 1, 157–173 (2004).Google Scholar
41. Grcar, J., “How ordinary elimination became gaussian elimination,” Historia Math. 38, 163–218 (2011).Google Scholar
42. Ben, A. and Greville, T., Generalized Inverses: Theory and Applications, vol. 15 (Springer Science & Business Media, 2003).Google Scholar
43. Taghirad, H. and Belanger, P., “Modeling and parameter identification of harmonic drive systems,” J. Dyn. Syst. Meas. Control, Trans.-Am. Soc. Mech. Eng. 120, 439–444 (1998).CrossRefGoogle Scholar
44. Nunez, J., Briseno, A., Rodriguez, D., Ibarra, J. and Rodriguez, V., “Explicit Analytic Solution for Inverse Kinematics of Bioloid Humanoid Robot,” Robotics Symposium and Latin American Robotics Symposium (SBR-LARS), (IEEE, 2012), pp. 33–38.Google Scholar
45. Huang, Q. and Nakamura, Y., “Sensory reflex control for humanoid walking,” IEEE Trans. Robot. 21, 977–984 (2005).Google Scholar
46. Hsu, W., Wang, T., Lu, H. and Lu, T., “Anticipatory changes in control of swing foot and lower limb joints when walking onto a moving surface traveling at constant speed,” Gait and Posture 41, 185–191 (2015).Google Scholar
47. Cham, R. and Redfern, M., “Changes in gait when anticipating slippery floors,” Gait and Posture 15, 159–171 (2002).Google Scholar