TY - GEN
T1 - The use of unicycle robot control strategies for skid-steer robots through the ICR kinematic mapping
AU - Pentzer, Jesse
AU - Brennan, Sean
AU - Reichard, Karl
N1 - Publisher Copyright:
© 2014 IEEE.
PY - 2014/10/31
Y1 - 2014/10/31
N2 - While decades of work and hundreds of research papers exist on unicycle robot control, the control of skid-steer robots is not yet as standardized due to the complexity of wheel slipping behavior. This work presents a method of utilizing the track or wheel Instantaneous Centers of Rotation (ICRs) on a skid-steer vehicle to map skid-steer dynamics to an equivalent time-varying model of unicycle dynamics. This allows for the direct implementation of existing unicycle, or Hilare type, robot trajectory controllers. Knowledge of ICR locations enables the calculation of required track or wheel speeds to create desired vehicle movement, similar to the kinematic relations resulting from the no-slip assumption of a unicycle robot. The algorithm requires no prior knowledge of vehicle dimensions or terrain parameters because ICR locations are estimated during robot operation using an extended Kalman filter (EKF). Simulation and experimental results for a wheeled skid-steer vehicle show good trajectory tracking performance.
AB - While decades of work and hundreds of research papers exist on unicycle robot control, the control of skid-steer robots is not yet as standardized due to the complexity of wheel slipping behavior. This work presents a method of utilizing the track or wheel Instantaneous Centers of Rotation (ICRs) on a skid-steer vehicle to map skid-steer dynamics to an equivalent time-varying model of unicycle dynamics. This allows for the direct implementation of existing unicycle, or Hilare type, robot trajectory controllers. Knowledge of ICR locations enables the calculation of required track or wheel speeds to create desired vehicle movement, similar to the kinematic relations resulting from the no-slip assumption of a unicycle robot. The algorithm requires no prior knowledge of vehicle dimensions or terrain parameters because ICR locations are estimated during robot operation using an extended Kalman filter (EKF). Simulation and experimental results for a wheeled skid-steer vehicle show good trajectory tracking performance.
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U2 - 10.1109/IROS.2014.6943006
DO - 10.1109/IROS.2014.6943006
M3 - Conference contribution
AN - SCOPUS:84911476719
T3 - IEEE International Conference on Intelligent Robots and Systems
SP - 3201
EP - 3206
BT - IROS 2014 Conference Digest - IEEE/RSJ International Conference on Intelligent Robots and Systems
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2014
Y2 - 14 September 2014 through 18 September 2014
ER -