A Dual-Mode Routing Algorithm for an Autonomous Roving Vehicle

Abstract

A dual-mode algorithm for routing an unmanned autonomous roving vehicle designed to explore the uncertain terrain of other planets is presented. The algorithm consists of a global mode, which uses dynamic programming and terrain information available from photo reconnaissance data to determine a nominal optimal path, and a local mode, which routes the vehicle around obstacles whose presence, location, and extent are not known in advance. Gaussian probability density functions are used to simulate terrain for examples that illustrate the performance of the algorithm.