Discrete Optimization of Adaptive State Lattices for Iterative Motion Planning on Unmanned Ground Vehicles
Benned Hedegaard,Ethan Fahnestock,Jacob Arkin,Ashwin Menon,Thomas M. Howard,Benned Hedegaard,Ethan Fahnestock,Jacob Arkin,Ashwin Menon,Thomas M. Howard
Robust motion planners for unmanned ground vehicles must minimize risk while obeying vehicle mobility constraints. Algorithms such as the State Lattice (SL) utilize offline computation to generate expressive control sets which form recombinant search spaces, enabling the use of heuristic search to efficiently produce feasible motion plans online. The Adaptive State Lattice (ASL) demonstrated that ...
