Path following using visual odometry for Mars Rover in high-slip environments.

An architecture for autonomous operation of Mars rovers in high slip environments has been designed, implemented, and tested. This architecture 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, and a slop 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 determining (tracking into account estimate uncertainties) if and how much 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.