A key challenge in enabling autonomous Unmanned Aerial Vehicles (UAVs) to operate in cluttered urban environments is to plan collision-free, smooth, dynamically feasible trajectories between two locations with the wind in realtime. This paper presents a novel path planning strategy using sampling-based planning that uses a two-point boundary value problem (BVP) to connect states in the presence of wind. Unlike most approaches that use a curvature discontinuous solution, the proposed BVP is formulated as a nonlinear constrained optimization problem with curvature and curvature-rate continuous profile to generate smoother trajectories. To achieve real-time performance, our method uses surrogate solutions from a precalculated library while solving the planning problem and then runs a repair routine to generate the final trajectory. To validate the feasibility of the offline-online strategy, simulation results on a 3D model of an actual city block with a realistic wind-field are presented. Results with a trochoid-based BVP solver are also presented for comparison. For the given simulation scenario, we could demonstrate a 93% success rate for the algorithm in finding a valid trajectory.
Overall Approach: Offline, we generate a trajectory library of precomputed wind-agnostic BVP solutions on a predefined grid. Online, we use the trajectory library to provide wind-aware surrogate solutions to perform real-time planning. Only the surrogate solutions that are part of the final path are repaired to provide smooth collision-free wind-aware path.