Benchmarking Sampling-based Motion Planning Pipelines for Wheeled Mobile Robots

Eric Heiden, Luigi Palmieri, Leonard Bruns, Kai O. Arras, Gaurav S. Sukhatme, and Sven Koenig
Benchmarking Sampling-based Motion Planning Pipelines for Wheeled Mobile Robots
ICAPS 2021

Abstract

Sampling-based motion planning is a key tool for several  autonomous  systems  ranging  from  autonomous driving  to  service  and  intralogistic  robotics.  Over  the past decades, several algorithms, extend functions and post-smoothing  techniques  have  been  introduced  for such systems. Choosing the best combination of such components for an autonomous system’s application is a tedious exercise, even for expert users. With the aim of helping researchers and practitioners in efficiently solving this issue, we have recently presented Bench-MR, the  first  open-source  motion-planning  benchmarking framework  designed  for  sampling-based  motion  planning for nonholonomic, wheeled mobile robots. Unlike related software suites, Bench-MR is an easy-to-use and comprehensive benchmarking framework that provides a large variety of sampling-based motion-planning algorithms,  extend  functions,  collision  checkers,  post-smoothing algorithms and optimization criteria. In this workshop paper, we complement our previous publication, by providing several examples on how to use it, together with the details on the framework architecture and components.

@article{heidenPalmieriICAPS2021,
  author    = {Eric Heiden and
               Luigi Palmieri and
               Leonard Bruns and
               Kai Oliver Arras and
               Gaurav S. Sukhatme and
               Sven Koenig},
  title     = {Benchmarking Sampling-based Motion Planning Pipelines for Wheeled Mobile Robots},
  journal   = {PlanRob Workshop at ICAPS 2021},
  year      = {2021}
}