Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6867041 | Robotics and Autonomous Systems | 2018 | 25 Pages |
Abstract
Sampling-based, search-based, and optimization-based motion planners are just some of the different approaches developed for motion planning problems. Given the wide variety of application tackled by autonomous mobile manipulators, the question “which planner to choose” may be tough. In this paper, we review the state of the art of the most common approaches, and present a set of benchmarks with the aim to provide not only a theoretical review but also a qualitative/quantitative comparison of the algorithms. Our purpose is to provide an insight and analyze their performance with respect to different metrics. The results are based on an Underwater Vehicle Manipulator System UVMS, although they can be extended to terrestrial and aerial robots as well. The paper uses these results to formalize a set of guidelines for the selection process of the most appropriate approach, for a given problem/requirements.
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Dina Youakim, Pere Ridao,