Direct Learning of Home Vector Direction: Incited by Existing Insect-Inspired Approaches for Local Navigation and Wayfinding

Insects have long been recognized for their ability to navigate and return home using visual cues from their nest’s environment. However, the precise mechanism underlying this remarkable homing skill remains a subject of ongoing investigation. Drawing inspiration from the learning flights of honey bees and wasps, we propose a robot navigation...

Low-memory Visual Route Following for Micro Aerial Vehicles in Indoor Environments

This thesis presents a visual route following method that minimizes memory consumption to the point that even Micro Aerial Vehicles (MAV) equipped with only a simple microcontroller can traverse distances of a few hundred meters. Existing Simultaneous Localization and Mapping (SLAM) algorithms are too complex for use on a microcontroller....

Visual Homing for Micro Aerial Vehicles using Scene Familiarity

Autonomous navigation is a major challenge in the development of MAVs. When an algorithm has to be efficient, insect intelligence can be a source of inspiration. An elementary navigation task is homing, which means autonomously returning to the initial location. A promising approach makes use of visual familiarity of a route to determine...