Planning in Dynamic and Partially Unknown Environments

Motion planning in dynamic and partially unknown environments is a difficult problem requiring both perception control components. We propose solution to the component while cleanly abstracting perception. show that this clean abstraction can be used synthesize verifiably safe reference trajectories using combination of reachability analysis Mixed Integer Linear Programming. Experiments with prototype implementation algorithm promise as it has subsecond synthesis performance for nonlinear vehicle models scenarios hundred plus obstacles on standard hardware.