Hostname: page-component-7b7567c8c-7pwfn Total loading time: 0 Render date: 2026-11-15T00:48:27.826Z Has data issue: false hasContentIssue false

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
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
Rights & Permissions [Opens in a new window]

Summary

Core share and HTML view are not available for this content. However, as you have access to this content, a full PDF is available via the 'Save PDF' action button.

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.

Information

Type
Articles
Copyright
Copyright © Cambridge University Press 2018