Probabilistic motion planning of balloons in strong, uncertain wind fields

This paper introduces a new algorithm for probabilistic motion planning in arbitrary, uncertain vector fields, with emphasis on high-level planning for Montgolfieré balloons in the atmosphere of Titan. The goal of the algorithm is to determine what altitude-and what horizontal actuation, if any is available on the vehicle-to use to reach a goal location in the fastest expected time. The winds can vary greatly at different altitudes and are strong relative to any feasible horizontal actuation, so the incorporation of the winds is critical for guidance plans. This paper focuses on how to integrate the uncertainty of the wind field into the wind model and how to reach a goal location through the uncertain wind field, using a Markov decision process (MDP). The resulting probabilistic solutions enable more robust guidance plans and more thorough analysis of potential paths than existing methods.