Name
Abstract | ||
|---|---|---|
With the development of biped robots, systems became able to navigate in a 3 dimensional world, walking up and down stairs, or climbing over small obstacles. We present a method for obtaining a labeled 2.5D grid map of the robot's surroundings. Each cell is marked either as floor or obstacle and contains a value telling the height of the floor or obstacle. Such height maps are useful for path planning and collision avoidance. The method uses a novel combination of a 3D occupancy grid for robust sensor data interpretation and a 2.5D height map for fine resolution floor values. We evaluate our approach using stereo vision on the humanoid robot QRIO and show the advantages over previous methods. Experimental results from navigation runs on an obstacle course demonstrate the ability of the method to generate detailed maps for autonomous navigation. |
Year | DOI | Venue |
|---|---|---|
2005 | 10.1109/ROBOT.2005.1570257 | 2005 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION (ICRA), VOLS 1-4 |
Keywords | Field | DocType |
3D perception and navigation, obstacle avoidance, humanoid robot | Obstacle avoidance,Grid reference,Obstacle,Computer vision,Artificial intelligence,Engineering,Obstacle course,Mobile robot navigation,Robot,Occupancy grid mapping,Humanoid robot | Conference |
Volume | Issue | ISSN |
2005 | 1 | 1050-4729 |
Citations | PageRank | References |
24 | 1.59 | 13 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jens-Steffen Gutmann | 1 | 657 | 76.64 |
| Masaki Fukuchi | 2 | 194 | 13.20 |
| Masahiro Fujita | 3 | 549 | 115.60 |