Image Space Potential Fields: Constant Size Environment Representation for Vision-based Subsumption Control Architectures
This addresses the challenge of real-time, reliable navigation for robotics by providing a representation that supports strong run-time guarantees, though it appears incremental as it builds on subsumption control architectures.
The paper tackles the problem of vision-based navigation by introducing an environment representation with constant size and structural similarity to camera image space, enabling control algorithms to operate directly in sensor space without inaccurate projections.
This technical report presents an environment representation for use in vision-based navigation. The representation has two useful properties: 1) it has constant size, which can enable strong run-time guarantees to be made for control algorithms using it, and 2) it is structurally similar to a camera image space, which effectively allows control to operate in the sensor space rather than employing difficult, and often inaccurate, projections into a structurally different control space (e.g. Euclidean). The presented representation is intended to form the basis of a vision-based subsumption control architecture.