Odometry Correction Using Visual Slip Angle Estimation for Planetary Exploration Rovers

Abstract

This paper introduces a novel method for slip angle estimation based on visually observing the traces produced by the wheels of a robot on soft, deformable terrain. The proposed algorithm uses a robust Hough transform enhanced by fuzzy reasoning to estimate the angle of inclination of the wheel trace with respect to the vehicle reference frame. Any deviation of the wheel track from the planned path of the robot suggests occurrence of sideslip that can be detected and, more interestingly, measured. In turn, the knowledge of the slip angle allows encoder readings affected by wheel slip to be adjusted and the accuracy of the position estimation system to be improved, based on an integrated longitudinal and lateral wheel-terrain slip model. The description of the visual algorithm and the odometry correction method is presented, and a comprehensive set of experimental results is included to validate this approach.

Improving Robot Mobility by Combining Downward-Looking and Frontal Cameras

“…This lens creates a telecentric optical system that provides a constant image scale factor regardless of the distance between the lens and the ground. In [19] a novel method for sideslip estimation is proposed. In particular, it is based on using a rearward-facing camera to measure the pose of the trace that is produced by the wheels, and detects whether the robot follows the desired path or deviates from it because of slippage.…”

Tyre pressure monitoring using a dynamical model-based estimator

“…Using state observers, key vehicle parameters can be estimated, including tyre cornering stiffness, [17] vehicle slip angle, [18] understeer gradient, yaw moment of inertia, roll stiffness, and roll damping coefficient. [19] Least-squares and total least-squares methods have also been used to measure cornering stiffness and weight distribution.…”

Methods for Wheel Slip and Sinkage Estimation in Mobile Robots

“…A novel approach for slip angle estimation of mobile robots travelling on loose terrain was presented in (Reina et al, 2010). It uses a rearward-facing video camera to measure the pose of the trace that is produced by the wheels, and detect whether the robot follows the desired path or deviates from it because of slippage.…”

“…11(b)), attesting to the feasibility of this approach. In order to allow useful dead-reckoning even in presence of lateral drift, a method for slippage compensated odometry was presented by Reina et al, 2010 using an integrated longitudinal and lateral friction model. This approach was proved to be effective in correcting odometry errors caused by wheel slippage, during traverse of sandy slopes.…”

“…Giulio Reina (2010). Methods for Wheel Slip and Sinkage Estimation in Mobile Robots, Robot Localization and Map Building, Hanafiah Yussof (Ed.…”