Sensor fusion for precise autonomous vehicle navigation in outdoor semi-structured environments

Abstract
This paper presents a guidance system for au- tonomous vehicles navigation in semi-structured outdoor envi- ronments. It integrates redundant encoders data and absolute positioning data provided by landmarks and artificial beacons. Natural features are localized using a laser range sensor, and magnetic sensing rulers were developed to detect magnetic markers buried in the ground. In the first fusion stage, data from four wheel encoders and one steering encoder are fused by means of an EKF, providing robust odometric information, namely in face of undesirable effects of wheels slippage. Next, a second fusion stage is processed for integrating odometric and absolute positioning data. Simulation and real experiments using a four-wheels actuated electrical vehicle are presented. I. INTRODUCTION Odometry being essential for autonomous navigation, is not enough due to its relative and integrative nature. So, it is required to complement odometric data with absolute positioning. Due to systematic error problems, some effort has been dedicated in modelling the uncertainty propagation in order to get somehow a reliable odometry model (6). Data fusion of ABS sensors and GPS for outdoor localization, based on an Extended Kalman Filter (EKF) had been pre- sented by Bonnifait, et al. (2).

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