Locating odour sources with mobile robots is a difficult task that can be applied to locating the sources of pollutants, concealed explosives or victims in disaster scenarios. The existing approaches for locating odour sources can be divided between those that simply seek to reach the chemical source, and those that use gas dispersion models to estimate its location. One of the most popular source estimation approaches is Infotaxis, which has been shown to have great sensitivity to the parameters of its gas distribution model.
In this paper, we compare two evolutionary approaches for automatically selecting the values for these parameters along with a Genetic Programming approach for evolving human-readable source-seeking strategies. The comparisons are carried out in three simulated environments with different chemical plumes and the results show that the parameters that best fit the environment do not always lead to the highest performance. Also, depending on the scenario, the tree-based search strategies are able to perform equivalently to Infotaxis, at a lesser computational cost.
Assessing Infotaxis Sensitivity to Model Quality Through Evolutionary Computation
Lect. Notes in Networks, Syst.
Iberian Robotics conference ; 2023 ; Coimbra, Portugal November 22, 2023 - November 24, 2023
2024-04-27
14 pages
Article/Chapter (Book)
Electronic Resource
English
An New Evolutionary Computation Method
British Library Conference Proceedings | 1997
|A new evolutionary computation method
IEEE | 1997
|