Multilateral Mission Planning in a Time-Varying Vector Field with Dynamic Constraints

Abstract

Navigating in a vector field is a challenging problem for many autonomous vehicles. This article focuses on a High-Altitude Pseudo-Satellite (HAPS) operating in a wind field with wind magnitude comparable to its airspeed. In addition to navigating from a start to a goal point, the HAPS is expected to carry out patrolling missions spanning long hours/ days, within which the physical environment (e.g. wind field, weather-critical no-go areas, fly zones etc.) vary, resulting in either an improvement or a deterioration of mission fulfillment. A time-dependent hybrid mission planning framework is proposed in this work which consists firstly of a hierarchical strategic planner that produces very quickly multiple sequences of tasks (or rather plans) that are ranked with roughly estimated objective or penalty values, and secondly of a tactical planner that refines the values of each premature plan to help the operator assess the plans better. The framework was implemented on the long-term offline planner for HAPS in patrolling missions. Test results using an independent six degrees-of-freedoms HAPS simulator and historical weather data are provided and analyzed.