Linked Local Navigation for Visual Route Guidance

Abstract

Insects are able to navigate reliably between food and nest using only visual information. This behavior has inspired many models of visual landmark guidance, some of which have been tested on autonomous robots. The majority of these models work by comparing the agent's current view with a view of the world stored when the agent was at the goal. The region from which agents can successfully reach home is therefore limited to the goal's visual locale, that is, the area around the goal where the visual scene is not radically different to the goal position. Ants are known to navigate over large distances using visually guided routes consisting of a series of visual memories. Taking inspiration from such route navigation, we propose a framework for linking together local navigation methods. We implement this framework on a robotic platform and test it in a series of environments in which local navigation methods fail. Finally, we show that the framework is robust to environments of varying complexity.

Insect-Inspired Visual Navigation for Flying Robots

“…This work and others showed that, while snapshot models work in a variety of environments, these approaches are limited in that they generally allow for navigation only in the immediate vicinity of the goal [10][11][12][13]. We therefore developed a familiarity-based model of route navigation in which individual views are used as a visual compass to recall the direction the agent was facing at that point, rather than the direction to the location as in most s napshot models.…”

Snapshots in ants? New interpretations of paradigmatic experiments

“…Despite the simplicity of the idea, in practice it has proved difficult for snapshot-type models of navigation to be extended to the use of multiple discrete views in this way [for a discussion, see Smith et al (Smith et al, 2007)]. One reason is that because each view acts as an attractor to a discrete location in space, they need to be used independently.…”

Bio-Inspired Principles Applied to the Guidance, Navigation and Control of UAS

“…Traditionally, a visual route is composed of a sequence of discrete waypoints, representing visual locales and defined by either global (whole image, image histogram) [99][100][101][102][103][104] or local descriptors extracted from input images (geometric features, SIFT points, average landmark vectors, etc.) [105][106][107][108][109][110][111].…”