A novel gait and foot slip detection algorithm for walking robots

Nori Okita, Henry Joseph Sommer, III

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


A novel gait and slip detection algorithm for walking robots using an inertial measurement unit was developed. An unscented Kalman filter was formulated with a simple dynamic model as a block on a slope without translations. Considerable prediction errors resulted when unmodeled dynamics (i.e., translation) occurred. These prediction errors were used in a binary Bayes filter to estimate the probability of gait and slip states. A proof of concept experiment was conducted with a monopedal walker under three floor conditions (nonslip, poly, and poly-oil) and three orientations (flat, uphill, and downhill). Realtime and offline detection at 100 Hz were successful. Continuous gait cycles were detected in proper order. Slip detection was successful except for very mild slips involving small jerk. The proposed algorithm provided a robust gait and slip detection method with a single set of parameters without knowledge of floor conditions and inclinations.

Original languageEnglish (US)
Title of host publicationIndustrial Applications; Modeling for Oil and Gas, Control and Validation, Estimation, and Control of Automotive Systems; Multi-Agent and Networked Systems; Control System Design; Physical Human-Robot Interaction; Rehabilitation Robotics; Sensing and Actuation for Control; Biomedical Systems; Time Delay Systems and Stability; Unmanned Ground and Surface Robotics; Vehicle Motion Controls; Vibration Analysis and Isolation; Vibration and Control for Energy Harvesting; Wind Energy
PublisherAmerican Society of Mechanical Engineers
ISBN (Electronic)9780791846209
StatePublished - Jan 1 2014
EventASME 2014 Dynamic Systems and Control Conference, DSCC 2014 - San Antonio, United States
Duration: Oct 22 2014Oct 24 2014

Publication series

NameASME 2014 Dynamic Systems and Control Conference, DSCC 2014


OtherASME 2014 Dynamic Systems and Control Conference, DSCC 2014
Country/TerritoryUnited States
CitySan Antonio

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Mechanical Engineering
  • Industrial and Manufacturing Engineering


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