CGD: Constraint-Guided Diffusion Policies for UAV Trajectory Planning

arXiv:2405.01758v1 Announce Type: cross
Abstract: Traditional optimization-based planners, while effective, suffer from high computational costs, resulting in slow trajectory generation. A successful strategy to reduce computation time involves using Imitation Learning (IL) to develop fast neural network (NN) policies from those planners, which are treated as expert demonstrators. Although the resulting NN policies are effective at quickly generating trajectories similar to those from the expert, (1) their output does not explicitly account for dynamic feasibility, and (2) the policies do …

abstract arxiv computation computational costs cs.lg cs.ro cs.sy diffusion eess.sy expert imitation learning network neural network optimization planning policies reduce strategy trajectory type while