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Bench-MR : A Motion Planning Benchmark for Wheeled Mobile Robots

Heiden, Eric (författare)
Univ Southern Calif, Dept Comp Sci, Los Angeles, CA 90007 USA.
Palmieri, Luigi (författare)
Robert Bosch GmbH, Corp Res, D-70839 Stuttgart, Germany.
Bruns, Leonard (författare)
KTH,Robotik, perception och lärande, RPL
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Arras, Kai O. (författare)
Robert Bosch GmbH, Corp Res, D-70839 Stuttgart, Germany.
Sukhatme, Gaurav S. (författare)
Univ Southern Calif, Dept Comp Sci, Los Angeles, CA 90007 USA.
Koenig, Sven (författare)
Univ Southern Calif, Dept Comp Sci, Los Angeles, CA 90007 USA.
visa färre...
Univ Southern Calif, Dept Comp Sci, Los Angeles, CA 90007 USA Robert Bosch GmbH, Corp Res, D-70839 Stuttgart, Germany. (creator_code:org_t)
Institute of Electrical and Electronics Engineers (IEEE), 2021
2021
Engelska.
Ingår i: IEEE Robotics and Automation Letters. - : Institute of Electrical and Electronics Engineers (IEEE). - 2377-3766. ; 6:3, s. 4536-4543
  • Tidskriftsartikel (refereegranskat)
Abstract Ämnesord
Stäng  
  • Planning smooth and energy-efficient paths for wheeled mobile robots is a central task for applications ranging from autonomous driving to service and intralogistic robotics. Over the past decades, several sampling-based motion-planning algorithms, extend functions and post-smoothing algorithms have been introduced for such motion-planning systems. Choosing the best combination of components for an application is a tedious exercise, even for expert users. We therefore present 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. It aids practitioners and researchers in designing, testing, and evaluating motion-planning systems, and comparing them against the state of the art on complex navigation scenarios through many performance metrics. Through several experiments, we demonstrate how Bench-MR can be used to gain extensive insights from the benchmarking results it generates.

Ämnesord

TEKNIK OCH TEKNOLOGIER  -- Elektroteknik och elektronik -- Robotteknik och automation (hsv//swe)
ENGINEERING AND TECHNOLOGY  -- Electrical Engineering, Electronic Engineering, Information Engineering -- Robotics (hsv//eng)

Nyckelord

Planning
Benchmark testing
Mobile robots
Navigation
Robot kinematics
Open source software
Collision avoidance
Nonholonomic motion planning
wheeled robots
software tools for benchmarking and reproducibility

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