A Taxonomy and Evaluation of Dense Two-Frame Stereo Correspondence Algorithms
International Journal of Computer Vision
Calculating Dense Disparity Maps from Color Stereo Images, an Efficient Implementation
International Journal of Computer Vision
Stereo Vision-Based Navigation in Unknown Indoor Environment
ECCV '98 Proceedings of the 5th European Conference on Computer Vision-Volume I - Volume I
Introduction to Autonomous Mobile Robots
Introduction to Autonomous Mobile Robots
Adaptive Support-Weight Approach for Correspondence Search
IEEE Transactions on Pattern Analysis and Machine Intelligence
Fast correlation-based stereo matching with the reduction of systematic errors
Pattern Recognition Letters
Obstacle-Free Pathway Detection by Means of Depth Maps
Journal of Intelligent and Robotic Systems
Hi-index | 0.00 |
This work presents a vision-based obstacle avoidance algorithm for autonomous mobile robots. It provides an efficient solution that uses a minimum of sensors and avoids, as much as possible, computationally complex processes. The only sensor required is a stereo camera. The proposed algorithm consists of two building blocks. The first one is a stereo algorithm, able to provide reliable depth maps of the scenery in frame rates suitable for a robot to move autonomously. The second building block is a decision making algorithm that analyzes the depth maps and deduces the most appropriate direction for the robot to avoid any existing obstacles. The proposed methodology has been tested on sequences of self-captured outdoor images and its results have been evaluated. The performance of the algorithm is presented and discussed.