TY - GEN
T1 - Path following Using visual odometry for a Mars rover in high-slip environments
AU - Helmick, Daniel M.
AU - Cheng, Yang
AU - Clouse, Daniel S.
AU - Matthies, Larry H.
AU - Roumeliotis, Stergios I.
N1 - Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.
PY - 2004
Y1 - 2004
N2 - A system for autonomous operation of Mars rovers in high slip environments has been designed, implemented, and tested. This system is composed of several key technologies that enable the rover to accurately follow a designated path, compensate for slippage, and reach intended goals independent of the terrain over which it is traversing (within the mechanical constraints of the mobility system). These technologies include: visual odometry, full vehicle kinematics, a Kalman filter pose estimator, and a slip compensation/path follower. Visual odometry tracks distinctive scene features in stereo imagery to estimate rover motion between successively acquired stereo image pairs using a maximum likelihood motion estimation algorithm. The full vehicle kinematics for a rocker-bogie suspension system estimates motion, with a no-slip assumption, by measuring wheel rates, and rocker, bogie, and steering angles. The Kalman filter merges data from an Inertial Measurement Unit (IMU) and visual odometry. This merged estimate is then compared to the kinematic estimate to determine (taking into account estimate uncertainties) if and how much slippage has occurred. If no statistically significant slippage has occurred then the kinematic estimate is used to complement the Kalman filter estimate. If slippage has occurred then a slip vector is calculated by differencing the current Kalman filter estimate from the kinematic estimate. This slip vector is then used, in conjunction with the inverse kinematics, to determine the necessary wheel velocities and steering angles to compensate for slip and follow the desired path.
AB - A system for autonomous operation of Mars rovers in high slip environments has been designed, implemented, and tested. This system is composed of several key technologies that enable the rover to accurately follow a designated path, compensate for slippage, and reach intended goals independent of the terrain over which it is traversing (within the mechanical constraints of the mobility system). These technologies include: visual odometry, full vehicle kinematics, a Kalman filter pose estimator, and a slip compensation/path follower. Visual odometry tracks distinctive scene features in stereo imagery to estimate rover motion between successively acquired stereo image pairs using a maximum likelihood motion estimation algorithm. The full vehicle kinematics for a rocker-bogie suspension system estimates motion, with a no-slip assumption, by measuring wheel rates, and rocker, bogie, and steering angles. The Kalman filter merges data from an Inertial Measurement Unit (IMU) and visual odometry. This merged estimate is then compared to the kinematic estimate to determine (taking into account estimate uncertainties) if and how much slippage has occurred. If no statistically significant slippage has occurred then the kinematic estimate is used to complement the Kalman filter estimate. If slippage has occurred then a slip vector is calculated by differencing the current Kalman filter estimate from the kinematic estimate. This slip vector is then used, in conjunction with the inverse kinematics, to determine the necessary wheel velocities and steering angles to compensate for slip and follow the desired path.
UR - https://www.scopus.com/pages/publications/11244262504
UR - https://www.scopus.com/pages/publications/11244262504#tab=citedBy
U2 - 10.1109/AERO.2004.1367679
DO - 10.1109/AERO.2004.1367679
M3 - Conference contribution
AN - SCOPUS:11244262504
SN - 0780381556
T3 - IEEE Aerospace Conference Proceedings
SP - 773
EP - 789
BT - 2004 IEEE Aerospace Conference Proceedings
PB - IEEE Computer Society
T2 - 2004 IEEE Aerospace Conference Proceedings
Y2 - 6 March 2004 through 13 March 2004
ER -