Name
Abstract | ||
|---|---|---|
An approach to robot perception and world modeling that uses a probabilistic tesselated representation of spatial information called the occupancy grid is reviewed. The occupancy grid is a multidimensional random field that maintains stochastic estimates of the occupancy state of the cells in a spatial lattice. To construct a sensor-derived map of the robot's world, the cell state estimates are obtained by interpreting the incoming range readings using probabilistic sensor models. Bayesian estimation procedures allow the incremental updating of the occupancy grid, using readings taken from several sensors over multiple points of view. The use of occupancy grids from mapping and for navigation is examined. Operations on occupancy grids and extensions of the occupancy grid framework are briefly considered.<> |
Year | DOI | Venue |
|---|---|---|
1989 | 10.1109/2.30720 | IEEE Computer |
Keywords | DocType | Volume |
Bayes methods,computerised navigation,mobile robots,Bayesian estimation,cell state estimates,mobile robot perception,multidimensional random field,multiple points of view,navigation,occupancy grid,path planning,probabilistic sensor models,probabilistic tesselated representation,range readings,sensor integration,sensor-derived map,single scanline stereo,sonar based mapping,spatial information,spatial lattice,world modeling | Journal | 22 |
Issue | ISSN | Citations |
6 | 0018-9162 | 656 |
PageRank | References | Authors |
64.00 | 2 | 1 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Alberto Elfes | 1 | 1470 | 416.36 |