Mono-Camera Based Simultaneous Obstacle Recognition and Distance Estimation for Obstacle Avoidance of Power Transmission Lines Inspection Robot

Title
Mono-Camera Based Simultaneous Obstacle Recognition and Distance Estimation for Obstacle Avoidance of Power Transmission Lines Inspection Robot
Authors
김창환김동환유주한
Keywords
Obstacle Recognition; Object Recognition; Obstacle Avoidance; Distance Estimation
Issue Date
2017-09
Publisher
IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) 2017
Citation
-6907
Abstract
This paper presents a mono-camera based simultaneous obstacle recognition and distance estimation method for power transmission lines(PTLs) inspection robot to avoid obstacles on or around them. The proposed robot inspects the PTLs while moving along them between power transmission towers. For autonomous navigation, our robot recognizes obstacles and avoids a collision with them. In addition, it can stop at the ends of the PTLs by recognizing its structures, such as insulators, installed at the ends of them. In order to recognize obstacles or insulators efficiently, initially, a robust PTLs detection method based on vanishing point estimation is proposed since they are installed on or around the PTLs. Then, obstacle models with various scales are built, and multiple regions-of-interest(ROIs) according to the scales of the model are constructed along the detected PTLs. Finally, obstacles are recognized within the multiple ROIs. Because each ROI represents a corresponding scale of the obstacle model to be matched, the proposed approach can efficiently deal with scale changes and also estimate distance between the robot and the obstacle simultaneously with obstacle recognition. Experimental results not only show that the proposed method correctly recognizes obstacles but also that the distance between the robot and the obstacles is estimated efficiently.
URI
http://pubs.kist.re.kr/handle/201004/66877
Appears in Collections:
KIST Publication > Conference Paper
Files in This Item:
There are no files associated with this item.
Export
RIS (EndNote)
XLS (Excel)
XML


qrcode

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.

BROWSE