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Planning smooth and energy-efficient motions for wheeled mobile robots is acentral task for applications ranging from autonomous driving to service andintralogistic robotics. Over the past decades, a wide variety of motionplanners, steer functions and path-improvement techniques have been proposedfor such non-holonomic systems. With the objective of comparing this largeassortment of state-of-the-art motion-planning techniques, we introduce a novelopen-source motion-planning benchmark for wheeled mobile robots, whosescenarios resemble real-world applications (such as navigating warehouses,moving in cluttered cities or parking), and propose metrics for planningefficiency and path quality. Our benchmark is easy to use and extend, and thusallows practitioners and researchers to evaluate new motion-planningalgorithms, scenarios and metrics easily. We use our benchmark to highlight thestrengths and weaknesses of several common state-of-the-art motion planners andprovide recommendations on when they should be used.

Experimental Comparison of Global Motion Planning Algorithms for Wheeled Mobile Robots