A Low-Cost, Practical Localization System for Agricultural Vehicles

Abstract

This paper addresses the refactoring of an agricultural vehicle localization system and its deployment and field-testing in apple orchards. The system enables affordable precision agriculture in tree fruit production by providing the vehicle’s position in the orchard without the use of expensive differential GPS. The localization methodology depends only on the wheel and steering encoders and the laser rangefinder already on the vehicle for row following, thus adding zero hardware cost to the overall setup. It employs an Extended Kalman Filter to integrate the information from the sensors, with the pose being predicted via encoder odometry and updated via point and line features detections. The objective of this paper is to describe the complete refactoring of the initial proof-of-concept localization system, with the goal of making it robust, modular and reusable. Field test results indicate that the final system has sufficient accuracy for deployment of autonomous vehicles in tree fruit orchards.