Experimental Comparison of Global Motion Planning Algorithms for Wheeled Mobile Robots
This provides a tool for practitioners and researchers to compare motion planning algorithms, but it is incremental as it focuses on benchmarking rather than new algorithms.
The authors tackled the problem of comparing motion planning algorithms for wheeled mobile robots by introducing a new open-source benchmark with real-world scenarios and metrics for efficiency and path quality, and used it to evaluate and recommend state-of-the-art planners.
Planning smooth and energy-efficient motions for wheeled mobile robots is a central task for applications ranging from autonomous driving to service and intralogistic robotics. Over the past decades, a wide variety of motion planners, steer functions and path-improvement techniques have been proposed for such non-holonomic systems. With the objective of comparing this large assortment of state-of-the-art motion-planning techniques, we introduce a novel open-source motion-planning benchmark for wheeled mobile robots, whose scenarios resemble real-world applications (such as navigating warehouses, moving in cluttered cities or parking), and propose metrics for planning efficiency and path quality. Our benchmark is easy to use and extend, and thus allows practitioners and researchers to evaluate new motion-planning algorithms, scenarios and metrics easily. We use our benchmark to highlight the strengths and weaknesses of several common state-of-the-art motion planners and provide recommendations on when they should be used.