Path Planning for Improved Visibility Using a Probabilistic Road Map

This paper focuses on the challenges of vision-based motion planning for industrial manipulators. Our approach is aimed at planning paths that are within the sensing and actuation limits of industrial hardware and software. Building on recent advances in path planning, our planner augments probabili...

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Bibliographic Details
Published in:IEEE transactions on robotics 2010-02, Vol.26 (1), p.195-200
Main Authors: Baumann, M., Leonard, S., Croft, E.A., Little, J.J.
Format: Article
Language:English
Subjects:
Applied sciences
Artificial intelligence
Assembly systems
Cameras
Communication system control
Computer industry
Computer programs
Computer science
control theory
systems
Computer vision
Control systems
Control theory. Systems
Exact sciences and technology
Hardware
Manipulators
Modelling and identification
Motion control
Path planning
path planning for industrial manipulators
Pattern recognition. Digital image processing. Computational geometry
Probabilistic methods
Probability theory
Roads
Robot arms
Robotics
Robots
sensor positioning
Tracking control systems
Vision systems
Visual servoing
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Summary:This paper focuses on the challenges of vision-based motion planning for industrial manipulators. Our approach is aimed at planning paths that are within the sensing and actuation limits of industrial hardware and software. Building on recent advances in path planning, our planner augments probabilistic road maps with vision-based constraints. The resulting planner finds collision-free paths that simultaneously avoid occlusions of an image target and keep the target within the field of view of the camera. The planner can be applied to eye-in-hand visual-target-tracking tasks for manipulators that use point-to-point commands with interpolated joint motion.
ISSN:1552-3098
1941-0468
DOI:10.1109/TRO.2009.2035745