2014 12th IEEE International Conference on Industrial Informatics (INDIN) 2014
DOI: 10.1109/indin.2014.6945533
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An RRT-based navigation approach for mobile robots and automated vehicles

Abstract: Abstract-Advances in autonomous navigation, safety, and natural-landmark based localization, are among the key objectives in the development of the next generation of autonomous vehicles, to be deployed in manufacturing and semi-structured environments. In this paper, autonomous navigation and collision detection will be focused, where it is proposed a novel navigation approach that incorporates a RRT-based dynamic path planning and a path-following controller. Safety issues are taken into account in the form … Show more

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Cited by 10 publications
(1 citation statement)
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“…As opposed to exhaustively creating a full-cost function, the idea of this technique is to firstly sample random points regardless of interfering obstacles, then connect only collision free points to construct a map. This technique is typically used for a robotic manipulator [122][123][124][125][126][127], however is still sometimes used for a mobile vehicle [128][129][130][131][132][133][134]. The problem with this technique is that post-processing to smooth the path is required in order for the path to be realistically traversable for the vehicle [135][136][137].…”
Section: Sampling-based Path Planningmentioning
confidence: 99%
“…As opposed to exhaustively creating a full-cost function, the idea of this technique is to firstly sample random points regardless of interfering obstacles, then connect only collision free points to construct a map. This technique is typically used for a robotic manipulator [122][123][124][125][126][127], however is still sometimes used for a mobile vehicle [128][129][130][131][132][133][134]. The problem with this technique is that post-processing to smooth the path is required in order for the path to be realistically traversable for the vehicle [135][136][137].…”
Section: Sampling-based Path Planningmentioning
confidence: 99%