![]() A typical gas sensor is designed and integrated into an UAV to enable active detection of gas information (concentration and species at different locations) in the atmosphere and continuous target positioning. In this work, an unmanned aerial vehicle (UAV) equipped with gas sensor systems is designed and studied for target detection and positioning. The search and rescue will be very time-consuming and very costly. The wilderness search and rescue (WiSAR) for lost persons or objects in remote wilderness areas is very challenging as these areas are almost inaccessible and the targets are concealed by the surrounding environment. We make the dataset and the code publicly available to enable the community to develop, validate, and compare new approaches related to gas sensing in complex environments. Correspondingly, ground-level gas distributions were rarely useful for localizing the gas source and elevated measurements were much more informative. We found strongly time-varying and counter-intuitive gas distribution patterns that disprove some assumptions commonly held in the MRO field, such as that heavy gases disperse along ground level. We also studied which features of the MOX sensor signals are optimal for predicting the source location, considering different lengths of the measurement window. ![]() This paper presents ten different experiments performed with a 3D grid of 27 metal oxide semiconductor (MOX) sensors to visualize the temporal evolution of gas distribution produced by an evaporating ethanol source placed at different locations in an office room, including variations in height, release rate and air flow. With the ever-increasing trend towards gas-sensitive aerial robots, 3D measurements of gas dispersion become necessary to characterize the environment these platforms can explore. Previous ground truth measurements of gas dispersion have been mostly based on expensive tracer optical methods or 2D chemical sensor grids deployed only at ground level. empirical evidence) about how a gas disperses in an environment is one of the major hurdles in the field of mobile robotic olfaction (MRO), impairing our ability to develop efficient gas source localization strategies and to validate gas distribution maps produced by autonomous mobile robots. The difficulty to obtain ground truth (i.e. In the second part of the study, this algorithm was further optimised by an ‘along-wall’ obstacle avoidance method and finally a novel algorithm, named vallumtaxis, was proposed and shown to achieve higher efficiency. Sixteen different algorithms were tested and compared and the algorithm constituted by normal casting, surge anemotaxis and normal stepsize performed the best among all. This is the first time that the performance of different plume-tracing algorithms in wall plumes has been tested and assessed and included in the literature. In one scenario, a chemical source is located away from walls in a channel and in the other scenario, the chemical source is located near a wall. A plume-tracing algorithm can be divided into three stages for analysis: plume sensing (PS), plume tracking (PT) and source localisation (SL).¹ These algorithms, which had been previously presented and tested in either simulation framework in 2D scenarios or experiments, were tested and compared in two different 3D scenarios in this study. In the first part of this study, a comparison of performance of several widely used plume-tracing algorithms was conducted. ![]() Bio-inspired chemical plume-tracing methods have been applied in robots to detect chemical emissions and to localise the plume sources in both indoor and outdoor environments.
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