Name
Abstract | ||
|---|---|---|
Active map learning for autonomous robots exploring in unknown environments is an essential and vital issue for robot navigation. However, many factors limit a robot's ability to learn accurate map models in practice. To enhance its learning capability, this paper proposed a binocular vision system, developed using IP web cameras and MATLAB image processing toolbox. It integrates knowledge from computer vision and robot navigation. Through the binocular vision system, binocular images are captured and analysed so that feature objects or shapes are identified. Together with sonar readings, this information is used in collision avoidance and map building. It is shown that the capability of active map learning is effectively realised by adopting this binocular vision system. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1504/IJISTA.2011.038262 | IJISTA |
Keywords | Field | DocType |
binocular-vision-enhanced mobile robot navigation,active map,map building,autonomous robot,binocular image,active map learning,robot navigation,computer vision,ip web camera,accurate map model,binocular vision system,feature extraction,binocular vision,image processing,robot learning,mobile robots,obstacle avoidance,mobile robot navigation | Obstacle avoidance,Robot learning,Computer vision,Binocular vision,Artificial intelligence,Autonomous system (mathematics),Mobile robot navigation,Engineering,Robot,Robotics,Mobile robot | Journal |
Volume | Issue | Citations |
10 | 1 | 0 |
PageRank | References | Authors |
0.34 | 13 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| James N. K. Liu | 1 | 529 | 44.35 |
| Bernard C. S. Kan | 2 | 0 | 0.34 |