For robots to be successfully introduced in a wider range of real-world settings, they should be able to safely and reliably navigate rapidly changing environments. While roboticists and computer scientists have introduced a wide range of computational techniques for robot navigation over the past decades, many of them were found to perform poorly in environments that are dynamic, cluttered or characterized by narrow pathways.
A human-inspired pathfinding approach to improve robot navigation
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