Realization of a Real-Time Optimal Control Strategy to Stabilize a Falling Humanoid Robot with Hand Contact

Shihao Wang, Kris Hauser

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

Abstract

In this paper, we present a real-time falling robot stabilization system for a humanoid robot in which the robot can prevent falling using hand contact with walls and other surfaces in the environment. Instead of ignoring or avoiding interaction with environmental obstacles, our system uses obstacle geometry to determine a contact point that reduces impact and necessary friction. It uses a planar dynamic model that is appropriate for falling stabilization in the robot's sagittal plane and frontal plane. The hand contact is determined with an optimal control approach, and to make the algorithm run in realtime, a simplified three-link robot model and a pre-computed database of subproblems for the hand contact optimization are adopted. Moreover, if the robot is not leaning too far after stabilization, we employ a heuristic push-up strategy to recover the robot to a standing posture. System integration is performed on the Darwin-Mini robot and validation is conducted in several environments and falling scenarios.

Original languageEnglish (US)
Title of host publication2018 IEEE International Conference on Robotics and Automation, ICRA 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages3092-3098
Number of pages7
ISBN (Electronic)9781538630815
DOIs
StatePublished - Sep 10 2018
Externally publishedYes
Event2018 IEEE International Conference on Robotics and Automation, ICRA 2018 - Brisbane, Australia
Duration: May 21 2018May 25 2018

Publication series

NameProceedings - IEEE International Conference on Robotics and Automation
ISSN (Print)1050-4729

Conference

Conference2018 IEEE International Conference on Robotics and Automation, ICRA 2018
CountryAustralia
CityBrisbane
Period5/21/185/25/18

ASJC Scopus subject areas

  • Software
  • Control and Systems Engineering
  • Artificial Intelligence
  • Electrical and Electronic Engineering

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