Time-Optimal Path Planning in a Constant Wind for Uncrewed Aerial Vehicles Using Dubins Set Classification

Time-optimal path planning in high winds for a turning-rate constrained Uncrewed Aerial Vehicle is a challenging problem to solve and is important for deployment and field operations. Previous works have used trochoidal path segments comprising straight and maximum-rate turn segments, as optimal extremal paths in uniform wind conditions. Current methods iterate over all candidate trochoidal trajectory types and select the one that is time-optimal; however, this exhaustive search can be computationally slow. In this letter, we introduce a method to decrease the computation time. This is achieved by reducing the number of candidate trochoidal trajectory types by framing the problem in the air-relative frame and bounding the solution within a subset of candidate trajectories. Our method reduces overall computation by 37.4% compared to pre-existing methods in Bang-Straight-Bang trajectories, freeing up computation for other onboard processes and can lead to significant total computational reductions when solving many trochoidal paths. When used within the framework of a global path planner, faster state expansions help find solutions faster or compute higher-quality paths.

I. Introduction

Deploying robotic platforms in the field often necessitates taking into account additional disturbances and challenges introduced by the environment. For example, the perception could be affected by changing lighting conditions, glare, and precipitation, while the path planning and controls are affected by disturbances and changing environmental factors such as wind [1]. Ignoring these factors in path planning can lead to less robust results, suboptimal paths, infeasible paths, or even the loss of the vehicle due to collisions.