A Path Planning Scheme with Consideration of Absolute Localization Accuracyfor Exploration UAVs

Abstract

Exploration UAVs (Unmanned Aerial Vehicles) are required to fly autonomously, because GPS cannot be used on Mars. Hence, localization is one of the major topics to be developed. In general, visual odometry is available for relative position estimation. However, it is difficult to estimate absolute position. This paper deals with the path planning in consideration of the absolute localization. This paper uses Mutual Information for image matching, which is robust to scene changes. MCL (Monte Carlo Localization) is applied for the absolute localization. Then, this paper proposes a new RRT (Rapidly-exploring Random Tree) extension method to generate a path with a large effect of the absolute localization. The simulation results show that the proposed method reduces the uncertainty of the position and generates a path that can increase the probability of reaching the goal.