JOURNAL ARTICLE

A stereo vision-based obstacle detecting method for mobile robot navigation

Yong C. ChoHyung S. Cho

Year: 1994 Journal:   Robotica Vol: 12 (3)Pages: 203-216   Publisher: Cambridge University Press

Abstract

SUMMARY This paper presents a computationally simple stereo vision method for detecting useful features of obstacles on the ground relevant to a mobile robot's navigation in an indoor environment. Enhanced time efficiency and reliability is achieved by introducing a geometrical image transformation and a frame-wise iterative edge image comparison scheme. The image transformation used in this paper relates each constant disparity value to an oblique plane at an elevation from the floor. The stereo correspondence method is devised by implementing a frame-wise AND operation based upon edge orientation and a subsequent pixel wise intensity correlation checking. This method is efficient in terms of computation time and capable of identifying isodisparity points, so that the height information of all the obstacle points above the floor can be determined. The obtained disparities are recorded on a local map to give complete obstacle features for mobile robot's path planning. Through a series of experiments performed under various environmental conditions, it is found that the proposed method can effectively be applied for locating obstacles of various heights in indoor navigation of mobile robots.

Keywords:
Computer vision Artificial intelligence Computer science Mobile robot Obstacle Transformation (genetics) Frame (networking) Stereopsis Robot Mobile robot navigation Enhanced Data Rates for GSM Evolution Orientation (vector space) Obstacle avoidance Mathematics Geography Robot control

Metrics

17
Cited By
7.79
FWCI (Field Weighted Citation Impact)
29
Refs
0.98
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Robotics and Sensor-Based Localization
Physical Sciences →  Engineering →  Aerospace Engineering
Advanced Vision and Imaging
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Robotic Path Planning Algorithms
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
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