robot navigation control based on monocular images: an image processing algorithm for obstacle avoidance decisions

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ID: 222835
2012
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Abstract
This paper covers the use of monocular vision to control autonomous navigation for a robot in a dynamically changing environment. The solution focused on using colour segmentation against a selected floor plane to distinctly separate obstacles from traversable space: this is then supplemented with canny edge detection to separate similarly coloured boundaries to the floor plane. The resulting binary map (where white identifies an obstacle-free area and black identifies an obstacle) could then be processed by fuzzy logic or neural networks to control the robot’s next movements. Findings show that the algorithm performed strongly on solid coloured carpets, wooden, and concrete floors but had difficulty in separating colours in multicoloured floor types such as patterned carpets.
Reference Key
benn2012mathematicalrobot Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors ;William Benn;Stanislao Lauria
Journal journal of power sources
Year 2012
DOI
10.1155/2012/240476
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