Drift-free roll and pitch estimation for high-acceleration hopping

Justin K. Yim, Eric K. Wang, Ronald S. Fearing

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

Abstract

We develop a drift-free roll and pitch attitude estimation scheme for monopedal jumping robots. The estimator uses only onboard rate gyroscopes and encoders and does not rely on external sensing or processing. It is capable of recovering from attitude estimate disturbances and, together with onboard velocity estimation, enables fully autonomous stable hopping control. The estimator performs well on a small untethered robot capable of large jumps and extreme stance accelerations. We demonstrate that the robot can follow a rectangular path using onboard dead-reckoning with less than 2 meters of drift over 200 seconds and 300 jumps covering 60 m. We also demonstrate that the robot can operate untethered outdoors under human wireless joystick direction.

Original languageEnglish (US)
Title of host publication2019 International Conference on Robotics and Automation, ICRA 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages8986-8992
Number of pages7
ISBN (Electronic)9781538660263
DOIs
StatePublished - May 2019
Externally publishedYes
Event2019 International Conference on Robotics and Automation, ICRA 2019 - Montreal, Canada
Duration: May 20 2019May 24 2019

Publication series

NameProceedings - IEEE International Conference on Robotics and Automation
Volume2019-May
ISSN (Print)1050-4729

Conference

Conference2019 International Conference on Robotics and Automation, ICRA 2019
Country/TerritoryCanada
CityMontreal
Period5/20/195/24/19

ASJC Scopus subject areas

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

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