Vision-based Navigation, Environmental Representations and Imaging Geometries

Abstract

We discuss the role of spatial representations and visual geometries in vision-based navigation. To a large extent, these choices determine the complexity and robustness of a given navigation strategy. For instance, navigation systems relying on a geometric representation of the environment, use most of the available computational resources for localization rather than for “progressing” towards the final destination. In most cases, however, the localization requirements can be alleviated and different (e.g. topological) representations used. In addition, these representations should be adapted to the robot’s perceptual capabilities.

Another aspect that strongly influences the success/complexity of a navigation system is the geometry of the visual system itself. Biological vision systems display alternative ocular geometries that proved successful in different (and yet demanding and challenging) navigation tasks. The compound eyes of insects or the human foveated retina are clear examples. Similarly, the choice of the particular geometry of the vision system and image sampling scheme, are important design options when building a navigation system.

We provide a number of examples in vision based navigation, where special spatial representations and visual geometries have been taken in consideration, resulting in added simplicity and robustness of the resulting system.