A study of nonlinear forward models for dynamic walking

Yangwei You, Chengxu Zhou, Zhibin Li, Nikos G. Tsagarakis

Research output: Chapter in Book/Report/Conference proceedingConference contribution


This paper offers a novel insight of using nonlinear models for the control to produce more robust and natural walking gaits for humanoid robots. The sagittal and lateral gait control needs to be treated differently, hence, we proposed two types of suitable nonlinear models, which allow forward simulations to look ahead, and thus, predict accurately the future trajectory/state at the end of the current step. Subsequently, by performing multiple forward simulations in a similar manner for the next step and using the gradient descent method, an appropriate foot placement can be found to achieve precise walking speed. By doing this two-step lookahead, all trajectories of the support and the swing leg can be generated. Our proposed controller can plan trajectories at the beginning of each step or actively re-plan according to task state errors. It is validated effectively in simulations performed in both ADAMS and Open Dynamic Engine. The robot can successfully traverse up/down a stair and recover from pushes with more natural looking gaits compared to the conventional bent-knee style. The reasonable computational time also indicates the feasibility of real-time implementation on real robots.
Original languageEnglish
Title of host publication2017 IEEE International Conference on Robotics and Automation (ICRA)
Place of PublicationSingapore, Singapore
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Number of pages6
ISBN (Electronic)978-1-5090-4633-1
ISBN (Print)978-1-5090-4634-8
Publication statusPublished - 24 Jul 2017
Event2017 IEEE International Conference on Robotics and Automation - Singapore, Singapore
Duration: 29 May 20173 Jun 2017


Conference2017 IEEE International Conference on Robotics and Automation
Abbreviated titleICRA 2017
Internet address


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