The Visual Extraction of the Autonomous Lawnmower Navigation Route

Abstract:

This paper uses the more intuitive visual processing of the camera to extract navigation information instead of using the low-end information collection technology of the photoelectric sensor as the current autonomous lawnmower navigation sensor. Image grey processing, binary algorithm, the image smooth method, the image inflation, the improved Hough transform combining with VC++ are used to get the line in order to distinguish the done and undone lawn successfully and to obtain navigation path and navigation parameters. The improved grayscale algorithm and the Hough transform algorithm have reduced the amount of image data processing, solved the small angle lines problem, and improved the real-time of the robots. Meanwhile prove the impossibility of image sharpening and border detection on extracting lawn boundary. The feasibility of the lawn image processing has been proved by examples.

• Periodical: Applied Mechanics and Materials (Volumes 157-158)
• Pages: 1458-1464
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.157-158.1458
• Online since: February 2012
• Authors: Li Si Fu, Yong You Xing
• Keywords: Autonomous Lawnmower, Hough Transform (HT), Image Processing, Robot Navigation

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