Eighteenth national conference on Artificial intelligence
Incremental heuristic search in AI
AI Magazine
AAMAS '06 Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems
Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems - Volume 1
Algorithm for computer control of a digital plotter
IBM Systems Journal
Global-referenced navigation grids for off-road vehicles and environments
Robotics and Autonomous Systems
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This paper presents a method for improving the runtime of an optimal heuristic path planner (A*) so that it can run repeatedly, in real-time, in a dynamic environment. This is necessary for mobile robots navigating in dynamic environments that have moving obstacles with associated costs, such as personal space around people or buffer zones around dangerous vehicles. Our approach is to modify the search space used by the A* algorithm, increasing the size of grid cells further from the robot. This approach relies on the notion that only the area closest to the robot needs to be searched carefully; areas further from the robot can be searched more coarsely. Because the planner is assumed to run repeatedly as the robot moves, the robot will always have a fine-grained path defined for its next action. We have experimentally verified in simulation that this algorithm can be run in real-time and produces paths that are comparable to full-resolution planning.