Benchmarking Motion Planning Algorithms: An Extensible Infrastructure for Analysis and Visualization

Motion planning is a key problem in robotics that is concerned with finding a path that satisfies a goal specification subject to constraints. In its simplest form, the solution to this problem consists of finding a path connecting two states, and the only constraint is to avoid collisions. Even for...

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Bibliographic Details
Published inIEEE robotics & automation magazine Vol. 22; no. 3; pp. 96 - 102
Main Authors Moll, Mark, Sucan, Ioan A., Kavraki, Lydia E.
Format Journal Article
LanguageEnglish
Published New York IEEE 01.09.2015
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects
Algorithms
Asymptotic properties
Automation
Benchmark testing
Collision avoidance
Completeness
Measurement
Mobile robots
Motion planning
Optimization
Path planning
Robotics
Robots
Specifications
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Summary:Motion planning is a key problem in robotics that is concerned with finding a path that satisfies a goal specification subject to constraints. In its simplest form, the solution to this problem consists of finding a path connecting two states, and the only constraint is to avoid collisions. Even for this version of the motion planning problem, there is no efficient solution for the general case [1]. The addition of differential constraints on robot motion or more general goal specifications makes motion planning even harder. Given its complexity, most planning algorithms forego completeness and optimality for slightly weaker notions such as resolution completeness, probabilistic completeness [2], and asymptotic optimality.
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ISSN:1070-9932
1558-223X
DOI:10.1109/MRA.2015.2448276