Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/60103
Title: | Real-time fuzzy obstacle avoidance using directional visual perception | Authors: | Huang, QC Rad, AB Wong, YK |
Issue Date: | 2004 | Source: | Journal of Southwest Jiaotong University (西南交通大学学报. 英文版), Nov. 2004, v. 12, no. 2, p. 107-115 | Abstract: | This paper presents a novel vision-based obstacle avoidance approach for the Autonomous Mobile Robot (AMR) with a Pan-Tilt-Zoom (PTZ) camera as its only sensing modality. The approach combines the morphological closing operation based on Sobel Edge Detection Operation and the (μ-kσ) thresholding technique to detect obstacles to soften the various lighting and ground floor effects. Both the morphology method and thresholding technique are computationally simple. The processing speed of the algorithm is fast enough to avoid some active obstacles. In addition, this approach takes into account the history obstacle effects on the current state. Fuzzy logic is used to control the behaviors of AMR as it navigates in the environment. All behaviors run concurrently and generate motor response solely based on vision perception. A priority based on subsumption coordinator selects the most appropriate response to direct the AMR away from obstacles. Validation of the proposed approach is done on a Pioneer 1 mobile robot. | Keywords: | Fuzzy system Obstacle avoidance Edge detection Autonomous mobile robot |
Publisher: | Southwest Jiaotong University | Journal: | Journal of Southwest Jiaotong University (西南交通大学学报. 英文版) | ISSN: | 2095-087X | Rights: | © 2004 中国学术期刊电子杂志出版社。本内容的使用仅限于教育、科研之目的。 © 2004 China Academic Journal Electronic Publishing House. It is to be used strictly for educational and research purposes. |
Appears in Collections: | Journal/Magazine Article |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
r21548.pdf | 359.5 kB | Adobe PDF | View/Open | |
r21548.pdf | 359.5 kB | Adobe PDF | View/Open |
Page views
71
Last Week
1
1
Last month
Citations as of Sep 22, 2024
Downloads
65
Citations as of Sep 22, 2024
Google ScholarTM
Check
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.