A software system for autonomous operation of a Mars rover is composed of several key algorithms that enable the rover to accurately follow a designated path, compensate for slippage of its wheels on terrain, and reach intended goals. The techniques implemented by the algorithms are visual odometry, full vehicle kinematics, a Kalman filter, and path following with slip compensation.
The visual-odometry algorithm tracks distinctive scene features in stereo imagery to estimate rover motion between successively acquired stereo image pairs, by use of a maximum-likelihood motion-estimation algorithm. The full-vehicle kinematics algorithm estimates motion, with a no-slip assumption, from measured wheel rates, steering angles, and angles of rockers and bogies in the rover suspension system. The Kalman filter merges data from an inertial measurement unit (IMU) and the visual-odometry algorithm. The merged estimate is then compared to the kinematic estimate to determine whether and how much slippage has occurred. The kinematic estimate is used to complement the Kalman-filter estimate if no statistically significant slippage has occurred. If slippage has occurred, then a slip vector is calculated by subtracting the current Kalman filter estimate from the kinematic estimate. This slip vector is then used, in conjunction with the inverse kinematics, to determine the wheel velocities and steering angles needed to compensate for slip and follow the desired path.
This work was done by Daniel Helmick, Yang Cheng, Daniel Clouse, Larry Matthies, and Stergios Roumeliotis of Caltech for NASA's Jet Propulsion Laboratory. For further information, access the Technical Support Package (TSP) free on-line at www.techbriefs.com/tsp under the Software category.
This software is available for commercial licensing. Please contact Karina Edmonds of the California Institute of Technology at (818) 393-2827. Refer to NPO-40703.
This Brief includes a Technical Support Package (TSP).
Path Following With Slip Compensation for a Mars Rover
(reference NPO-40703) is currently available for download from the TSP library.
Don't have an account?
Overview
The document titled "Path Following With Slip Compensation for a Mars Rover" presents a comprehensive overview of a system designed to enhance the navigation capabilities of Mars rovers in high-slip environments. Developed by NASA's Jet Propulsion Laboratory, the system aims to enable rovers to accurately follow designated paths while compensating for slippage, thereby ensuring they reach their intended goals regardless of the terrain.
The architecture of the system comprises several key components: visual odometry, full vehicle kinematics, a Kalman filter, and a slip compensation/path following algorithm. Visual odometry utilizes stereo imagery to estimate rover motion independently of terrain properties, while full vehicle kinematics relies on position sensor inputs from the rover's mobility system to assess motion. The Kalman filter merges estimates from visual odometry and the onboard Inertial Measurement Unit (IMU) to create a high-frequency motion estimate, which is crucial for real-time navigation.
The document details the process of comparing the motion estimates from the Kalman filter and the vehicle kinematics. If discrepancies indicate slippage, a "slip vector" is generated, which is then used in conjunction with a path-following algorithm to adjust the rover's velocity commands. This integrated approach allows the rover to navigate effectively, even in challenging conditions.
Two experimental tests were conducted using the Rocky 8 rover platform. The first test took place in the Jet Propulsion Laboratory's Marsyard, designed to simulate Martian terrain, while the second was conducted in Johnson Valley, California, featuring loose granular sand slopes. Both experiments collected ground truth data using a Leica Total Station, which provided precise position measurements to validate the rover's navigation performance.
The results from these experiments demonstrated the effectiveness of the integrated system in compensating for slip and maintaining accurate path following. The findings contribute to the ongoing development of autonomous navigation technologies for future Mars missions, enhancing the ability of rovers to traverse diverse and unpredictable landscapes.
Overall, this document encapsulates significant advancements in rover navigation technology, emphasizing the importance of robust systems that can adapt to varying environmental conditions on Mars, ultimately supporting the goals of exploration and scientific discovery.
