  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.
