Humanitarian Demining Using an Insect Based Chemical Unmanned Aerial Vehicle

Abstract

Humanitarian Demining: Innovative Solutions and the Challenges of Technology 192 on vision, biologically constrained neuronal models of the fly visual system suffice for course stabilization and altitude control of a blimp-based UAV. Then, we augment this system with a collision avoidance model based on the Lobula Giant Movement Detector neuron of the Locust. A number of chemical search experiments are described with a mobile robot in a controlled wind tunnel environment. In these experiments, a number of chemical mapping strategies and behaviorally and biologically constrained models derived from the moth are tested and their performance is assessed. Finally, some of these solutions are evaluated in outdoor chemical detection, mapping and localization tasks using a cUAV. We show that our insect based approach that combines detailed biologically constrained models of the fly, locust and moth provides for a robust system and can constitute a viable approach towards the detection and localization of explosives and therefore be used for humanitarian demining. Moreover, our insect based cUAV demonstrates that the detailed understanding of biological solutions to real-world problems can provide for novel and robust artificial systems.