Although recent (physical) robots have powerful sensors and actuators their abilities to show intelligent behavior is often limited. One key reason is the lack of an appropriate spatial representation. Spatial knowledge plays a crucial role in navigation, (self-and object-)localization, planning and
Spatial constraint propagation for identifying qualitative spatial structure
β Scribed by Takushi Sogo; Hiroshi Ishiguro; Toru Ishida
- Book ID
- 102661570
- Publisher
- John Wiley and Sons
- Year
- 2000
- Tongue
- English
- Weight
- 862 KB
- Volume
- 31
- Category
- Article
- ISSN
- 0882-1666
No coin nor oath required. For personal study only.
β¦ Synopsis
This paper proposes a method for reconstructing qualitative positions of landmarks by using geometrical constraints. The acquisition process iterates the following steps: (1) observing relations among landmarks and motion directions of moving objects, (2) classifying the landmarks into a pair of landmark sets which are classified with a straight line, (3) acquiring three-point constraints from the pair, and (4) propagating the constraints. We have applied this method to acquisition of qualitative positions of multiple vision sensors in a distributed vision system, and evaluated it with simulations.
π SIMILAR VOLUMES
Existing computational models of structure-from-motion are all based on a quantitative analysis of variations in optical flow or feature point correspondences within the interiors of single objects. We present an alternative approach effective for objects rotating in depth. The method involves a set