UAV-based Odor Source Localization in Multi-Building Environments Using Simulated Annealing Algorithm

A single unmanned-aerial-vehicle (UAV) based odor source localization (OSL) method for outdoor multi-building environments was proposed. The simulated annealing (SA) algorithm was introduced in this problem in consideration of the difficulties of relatively large search space, turbulent airflow in the building environment, and local concentration extrema near the building walls. To avoid the effect of rotating UAV rotors on airflow, a tunable diode laser absorption spectroscopy (TDLAS) rather than the contact gas sensor was used to collect odor information remotely. Moreover, a three-mode (plume finding, tracking, and escaping local extremum) searching framework was designed in the SA-based OSL method to equip the UAV with abilities of traversing the searching area and escaping local extrema rapidly. Simulation results on a robot active olfaction simulator show that, the UAV could effectively escape the local extremum, track the plume and localize the odor source in the area of 30×30×10 m
³
with an average time of about 119 steps and an average error of 1.56 m.