Abstract-This paper introduces a novel method for wheel-slippage detection and correction based on motor current measurements. Our proposed method estimates wheel slippage from motor current measurements, and adjusts encoder readings affected by wheel slippage accordingly. The correction of wheel slippage based on motor currents works only in the direction of motion, but not laterally, and it requires some knowledge of the terrain. However, this knowledge does not have to be provided ahead of time by human operators. Rather, we propose three tuning techniques for determining relevant terrain parameters automatically, in real time, and during motion over unknown terrain. Two of the tuning techniques require position ground truth (i.e., GPS) to be available either continuously or sporadically. The third technique does not require any position ground truth, but is less accurate than the two other methods. A comprehensive set of experimental results have been included to validate this approach.
Abstract-Research at the University of Michigan's Mobile Robotics Lab aims at the development of an accurate proprioceptive (i.e., without external references) position estimation (PPE) system for planetary rovers. Much like other PPE systems, ours uses an inertial measurement unit (IMU) comprising three fiber-optic gyroscopes and a two-axes accelerometer, as well as odometry based on wheel encoders.Our PPE system, however, is unique in that it does not use the conventional Kalman Filter approach for fusing data from the different sensor modalities. Rather, our system combines data based on expert rules that implement our in-depth understanding of each sensor modality's behavior under different driving and environmental conditions. Since our system also uses Fuzzy Logic operations in conjunction with the Expert Rules for finer gradation, we call it Fuzzy Logic Expert navigation (FLEXnav) PPE system. The paper presents detailed experimental results obtained with our FLEXnav system integrated with our planetary rover clone "Fluffy" and operating in a Mars-like environment. In addition, we compare the results of our FLEXnav system with results obtained from a conventional Kalman Filter. The paper also introduces new methods for wheel slippage detection and correction, along with comprehensive experimental results.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.