Measuring Accuracy Prediction-based Path Planning for UGVs with Visual Measurement Ability

Abstract

Distributed unmanned ground vehicles (UGVs) with visual measurement cameras provide more flexibility and extendibility to measuring technology in industrial applications. This paper proposes an accuracy prediction-based path planning method for visual measurement system based on UGVs. A task planning framework for the visual measurement system is designed, in which task assignment, measuring position planning, and path planning are integrated. An accuracy prediction model is established using the geometric principle in visual measurement. The optimal measuring positions and paths are obtained for the UGVs based on the accuracy prediction model and virtual potential field method. Simulations and experimental results validate the effectiveness of the proposed method.