Path following Using visual odometry for a Mars rover in high-slip environments

Daniel M. Helmick, Yang Cheng, Daniel S. Clouse, Larry H. Matthies, Stergios Roumeliotis

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

76 Citations (Scopus)

Abstract

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.

Original languageEnglish (US)
Title of host publication2004 IEEE Aerospace Conference Proceedings
Pages772-788
Number of pages17
DOIs
StatePublished - Dec 1 2004
Event2004 IEEE Aerospace Conference Proceedings - Big Sky, MT, United States
Duration: Mar 6 2004Mar 13 2004

Publication series

NameIEEE Aerospace Conference Proceedings
Volume2
ISSN (Print)1095-323X

Other

Other2004 IEEE Aerospace Conference Proceedings
CountryUnited States
CityBig Sky, MT
Period3/6/043/13/04

Fingerprint

mars
Mars
Kinematics
slip
Kalman filters
kinematics
Kalman filter
estimates
Wheels
Inverse kinematics
Units of measurement
wheels
stereo image
Motion estimation
Maximum likelihood
vehicles
inverse kinematics
imagery
estimators
complement

Cite this

Helmick, D. M., Cheng, Y., Clouse, D. S., Matthies, L. H., & Roumeliotis, S. (2004). Path following Using visual odometry for a Mars rover in high-slip environments. In 2004 IEEE Aerospace Conference Proceedings (pp. 772-788). (IEEE Aerospace Conference Proceedings; Vol. 2). https://doi.org/10.1109/AERO.2004.1367679

Path following Using visual odometry for a Mars rover in high-slip environments. / Helmick, Daniel M.; Cheng, Yang; Clouse, Daniel S.; Matthies, Larry H.; Roumeliotis, Stergios.

2004 IEEE Aerospace Conference Proceedings. 2004. p. 772-788 (IEEE Aerospace Conference Proceedings; Vol. 2).

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

Helmick, DM, Cheng, Y, Clouse, DS, Matthies, LH & Roumeliotis, S 2004, Path following Using visual odometry for a Mars rover in high-slip environments. in 2004 IEEE Aerospace Conference Proceedings. IEEE Aerospace Conference Proceedings, vol. 2, pp. 772-788, 2004 IEEE Aerospace Conference Proceedings, Big Sky, MT, United States, 3/6/04. https://doi.org/10.1109/AERO.2004.1367679
Helmick DM, Cheng Y, Clouse DS, Matthies LH, Roumeliotis S. Path following Using visual odometry for a Mars rover in high-slip environments. In 2004 IEEE Aerospace Conference Proceedings. 2004. p. 772-788. (IEEE Aerospace Conference Proceedings). https://doi.org/10.1109/AERO.2004.1367679
Helmick, Daniel M. ; Cheng, Yang ; Clouse, Daniel S. ; Matthies, Larry H. ; Roumeliotis, Stergios. / Path following Using visual odometry for a Mars rover in high-slip environments. 2004 IEEE Aerospace Conference Proceedings. 2004. pp. 772-788 (IEEE Aerospace Conference Proceedings).
@inproceedings{42c41c1f04d5474ebb169d9265f04a9a,
title = "Path following Using visual odometry for a Mars rover in high-slip environments",
abstract = "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.",
author = "Helmick, {Daniel M.} and Yang Cheng and Clouse, {Daniel S.} and Matthies, {Larry H.} and Stergios Roumeliotis",
year = "2004",
month = "12",
day = "1",
doi = "10.1109/AERO.2004.1367679",
language = "English (US)",
isbn = "0780381556",
series = "IEEE Aerospace Conference Proceedings",
pages = "772--788",
booktitle = "2004 IEEE Aerospace Conference Proceedings",

}

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

PY - 2004/12/1

Y1 - 2004/12/1

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 - http://www.scopus.com/inward/record.url?scp=11244262504&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=11244262504&partnerID=8YFLogxK

U2 - 10.1109/AERO.2004.1367679

DO - 10.1109/AERO.2004.1367679

M3 - Conference contribution

SN - 0780381556

T3 - IEEE Aerospace Conference Proceedings

SP - 772

EP - 788

BT - 2004 IEEE Aerospace Conference Proceedings

ER -