Paper Info
Title
Towards Environmentally Adaptive Odor Source Localization: Fuzzy Lévy Taxis Algorithm and Its Validation in Dynamic Odor Plumes
Abstract
In this paper, we propose a bio-inspired Fuzzy Lévy Taxis algorithm to solve the robotic odor source localization problem in dynamic odor plumes. According to the proposed algorithm, the robot is programmed to move for a length with a turning angle at each step until reaching the odor source. The movement length and the turning angle follow two specific probability distribution, of which the parameters are adaptive through a fuzzy logic system. The proposed algorithm was compared with the Adaptive Lévy Taxis algorithm in simulated pseudo-Gaussian plumes. Our proposed algorithm shows a higher success rate and efficiency. The algorithm has also been systematically evaluated in simulated filament-based odor plumes under various environmental conditions. The results revealed that the performance of the proposed algorithm is consistently good in various environmental conditions in terms of success rate, number of steps and distance overhead to find the odor source.
Year
DOI
Venue
2020
10.1109/ICARM49381.2020.9195363
2020 5th International Conference on Advanced Robotics and Mechatronics (ICARM)
Keywords
DocType
ISBN
probability distribution,fuzzy logic system,environmentally adaptive odor source localization,dynamic odor plumes,robotic odor source localization problem,bioinspired fuzzy Lévy Taxis algorithm,filament-based odor simulation,pseudoGaussian plume simulation,adaptive Lévy Taxis algorithm
Conference
978-1-7281-6480-9
Citations 
PageRank 
References 
0
0.34
4
Authors
2
Name
Order
Citations
PageRank
Xinxing Chen100.34
J. Huang24412.63