Occupancy Grid Mapping (Occupancy Grid Mapping)
Revision as of 10:25, 15 February 2023 by Admin (talk | contribs) (Created page with "{{DISPLAYTITLE:Occupancy Grid Mapping (Occupancy Grid Mapping)}} == Description == Assuming a robot's pose is known, generate a occupancy grid mapping of the area. 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 s...")
Description
Assuming a robot's pose is known, generate a occupancy grid mapping of the area. 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.
Parameters
No parameters found.
Table of Algorithms
| Name | Year | Time | Space | Approximation Factor | Model | Reference |
|---|---|---|---|---|---|---|
| Maximum a Posteriori Occupancy Mapping | 2004 | $O(n^{3})$ | Deterministic |