Research on UAV trajectory planning methods in indoor environments

In order to address the difficulty of considering dynamic constraints during trajectory search for indoor inspection UAVs, an improved dynamically feasible algorithm is proposed, and trajectory optimization is further incorporated to generate smooth curves. Dynamic constraints, including velocity and acceleration, are embedded into the BIT* framework to avoid generating infeasible segments and to improve both efficiency and feasibility. To address the nonsmooth nature of the searched paths, a spline-based trajectory optimization method is further applied, transforming discrete paths into smooth trajectories that satisfy higher-order continuity constraints. The proposed approach is validated in a simulation environment. Results demonstrate that feasible and smooth trajectories are obtained, enhancing controllability and stability in narrow spaces, and providing an efficient and reliable solution for autonomous indoor inspection flights.