Name
Abstract | ||
|---|---|---|
This paper describes a three-dimensional terrain mapping and classification technique to allow the operation of mobile robots in outdoor environments using laser range finders. We propose the use of a multi-layer perceptron neural network to classify the terrain into navigable, partially navigable, and non-navigable. The maps generated by our approach can be used for path planning, navigation, and local obstacle avoidance. Experimental tests using an outdoor robot and a laser sensor demonstrate the accuracy of the presented methods. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1145/1644993.1645074 | ICHIT |
Keywords | Field | DocType |
three-dimensional terrain mapping,experimental test,mobile robot,local obstacle avoidance,laser range finder,outdoor environment,multi-layer perceptron neural network,path planning,classification technique,outdoor robot,mobile robots,three dimensional,multi layer perceptron,neural network,obstacle avoidance | Terrain mapping,Obstacle avoidance,Motion planning,Computer vision,Computer science,Terrain,Artificial intelligence,Robot,Artificial neural network,Perceptron,Mobile robot | Conference |
Citations | PageRank | References |
1 | 0.37 | 4 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Alberto Yukinobu Hata | 1 | 71 | 7.75 |
| Denis Fernando Wolf | 2 | 47 | 9.86 |
| Gustavo Pessin | 3 | 164 | 23.10 |
| Fernando Santos Osório | 4 | 114 | 19.08 |