Multiresolution Constraint Modeling for Mobile Robot Planning

Abstract

All navigation systems for a mobile robot include a basic sense-plan-drive cycle for moving the robot about. The navigator must choose sensing points, plan paths between them, and oversee the execution of the robot's trajectory. Various constraints must be met in selecting potential sensing points, feasible trajectories, and safe configurations, all while taking positional unceitainty into account. We have developed a local planner that finds trajectories for a robot by modeling all of the constraints uniformly. At each step in the planning process, the system identifies and uses the most severe constraint to guide the search. A multi-resolution approximation to the constraint solution space is employed to reduce the number of search states, and thus the planning time. The system has been implemented and tested on real data. The results are presented.