Planning smooth and energy-efficient motions for wheeled mobile robots is a\ncentral task for applications ranging from autonomous driving to service and\nintralogistic robotics. Over the past decades, a wide variety of motion\nplanners, steer functions and path-improvement techniques have been proposed\nfor such non-holonomic systems. With the objective of comparing this large\nassortment of state-of-the-art motion-planning techniques, we introduce a novel\nopen-source motion-planning benchmark for wheeled mobile robots, whose\nscenarios resemble real-world applications (such as navigating warehouses,\nmoving in cluttered cities or parking), and propose metrics for planning\nefficiency and path quality. Our benchmark is easy to use and extend, and thus\nallows practitioners and researchers to evaluate new motion-planning\nalgorithms, scenarios and metrics easily. We use our benchmark to highlight the\nstrengths and weaknesses of several common state-of-the-art motion planners and\nprovide recommendations on when they should be used.\n