Moth-Like Chemo-Source Localization and Classification on an Indoor Autonomous Robot

Abstract

Olfaction is a crucial sense for many living organisms. Many animals, especially insects, rely heavily on the olfactory sense for encoding and processing different chemical cues in order to perform several tasks such as foraging, predator avoidance, mate finding, communication etc.(22). Yet, olfaction has not been as widely studied as vision or the auditory system in insects. At the same time, robotic platforms capable of searching, locating and classifying odor sources in wind turbulence and in the presence of complex odors have diverse applications ranging from environmental monitoring (21), detection of explosives and other hazardous substances (19), land mine detection (2) to human search and rescue operations. The main challenge thereby is the stable and fast coding and decoding of odors and the localization of the sources (17). In our own recent work, we have proposed an insect-like mapless navigation mechanism which integrates surge-and-cast chemo search, path integration, wind detection and visual landmark navigation on an indoor mobile robot (28). Also, we have proposed a model based on insect navigation that is capable of navigating in highly dynamic environments and our model was compared directly to ant navigational data, with strikingly similar navigational behaviors (26). The problem of ambiguous information, particularly in the navigational context, is also addressed in our recent work (27). Beyond that, we have contributed significantly to modeling insect navigation and designing robotic systems such as: a model of the locust Lobula Giant Movement Detector (LGMD) tested on a high speed robot (29), moth-like odor localization for robots (30), control of an unmanned aerial vehicle using a neuronal model of a fly-locust brain (31; 32), moth-like optomotor anemotactic chemical search for robots (33), and a blimp flight control using a biologically inspired flight control system (34). Despite these advances, several biological systems with relatively simple nervous systems solve the odor localization and classification problem much more efficiently than their artificial counterparts: bees use odor to localize nests, ants use pheromone trails to organize foraging in swarms, lobsters use odor to locate food, the Escherichia bacteria use odors to locate nutrients, male moths use olfaction to locate female mates etc. The odor localization