Networking Issues for Small Unmanned Aircraft Systems
Journal of Intelligent and Robotic Systems
Evolutionary robotics approach to odor source localization
Neurocomputing
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Four chemical plume-tracking algorithms have been compared using a mobile robot. These algorithms are based upon hypotheses proposed to explain the plume-tracking behavior of flying insects. They all use information from a wind sensor and a single chemical sensor to determine how the agent should move to locate the source of the chemical plume. The performance of the robot using each of the algorithms was tested in a wind tunnel under a range of wind speeds (0.55, 0.95, and 1.4 m/s) using a model chemical (ionized air). The robot was capable of tracking the ion plume to its source effectively with each algorithm, having an overall success rate of over 85%. The simplest implemented algorithm, surge anemotaxis, was found to be the fastest. However, the shape of the tracking paths observed indicated that this simple algorithm may not explain the plume-tracking behavior of certain insects as well as the other algorithms tested. Further tests are required to see if the surge anemotaxis algorithm remains the most efficient under more realistic wind conditions.