On-line estimation of vehicle motion and power model parameters for skid-steer robot energy use prediction

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

20 Scopus citations


This paper presents a method of estimating skid-steer robot power usage using on-line estimation of terrain and kinematic parameters. For vehicles operating at low speeds on hard, flat surfaces, kinematic models utilizing the instantaneous centers of rotation (ICRs) of the tracks or wheels of a skidsteer vehicle have been shown to provide accurate motion and power use estimation. Previous work has relied on post-process optimization to learn necessary ICR location and terrain information for motion and power modeling. The work presented here utilizes an extended Kalman filter for learning ICR locations and the recursive least squares algorithm for learning terrain-related power model parameters. The algorithms have been implemented on a wheeled skid-steer vehicle, and field test results show good estimation of motion and power usage using no prior terrain information and only knowledge of vehicle geometry and mass distribution, intermittent GPS and heading, and odometry information from the slipping tires/treads.

Original languageEnglish (US)
Title of host publication2014 American Control Conference, ACC 2014
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages6
ISBN (Print)9781479932726
StatePublished - 2014
Event2014 American Control Conference, ACC 2014 - Portland, OR, United States
Duration: Jun 4 2014Jun 6 2014

Publication series

NameProceedings of the American Control Conference
ISSN (Print)0743-1619


Other2014 American Control Conference, ACC 2014
Country/TerritoryUnited States
CityPortland, OR

All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering


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