Please use this identifier to cite or link to this item:
https://hdl.handle.net/10316/107387
Title: | A Comparative Study of Bio-Inspired Odour Source Localisation Strategies from the State-Action Perspective | Authors: | Macedo, João Marques, Lino Costa, Ernesto |
Keywords: | odour source localisation; mobile robot olfaction; bio-inspired strategies | Issue Date: | 14-May-2019 | Publisher: | MDPI | Project: | SFRH/BD/129673/2017 | Serial title, monograph or event: | Sensors (Switzerland) | Volume: | 19 | Issue: | 10 | Abstract: | Locating odour sources with robots is an interesting problem with many important real-world applications. In the past years, the robotics community has adapted several bio-inspired strategies to search for odour sources in a variety of environments. This work studies and compares some of the most common strategies from a behavioural perspective with the aim of knowing: (1) how different are the behaviours exhibited by the strategies for the same perceptual state; and (2) which are the most consensual actions for each perceptual state in each environment. The first step of this analysis consists of clustering the perceptual states, and building histograms of the actions taken for each cluster. In case of (1), a histogram is made for each strategy separately, whereas for (2), a single histogram containing the actions of all strategies is produced for each cluster of states. Finally, statistical hypotheses tests are used to find the statistically significant differences between the behaviours of the strategies in each state. The data used for performing this study was gathered from a purpose-built simulator which accurately simulates the real-world phenomena of odour dispersion and air flow, whilst being sufficiently fast to be employed in learning and evolutionary robotics experiments. This paper also proposes an xml-inspired structure for the generated datasets that are used to store the perceptual information of the robots over the course of the simulations. These datasets may be used in learning experiments to estimate the quality of a candidate solution or for measuring its novelty. | URI: | https://hdl.handle.net/10316/107387 | ISSN: | 1424-8220 | DOI: | 10.3390/s19102231 | Rights: | openAccess |
Appears in Collections: | I&D CISUC - Artigos em Revistas Internacionais I&D INESCC - Artigos em Revistas Internacionais |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
A-comparative-study-of-bioinspired-odour-source-localisation-strategies-from-the-stateaction-perspectiveSensors-Switzerland.pdf | 2.02 MB | Adobe PDF | View/Open |
SCOPUSTM
Citations
29
checked on Oct 14, 2024
WEB OF SCIENCETM
Citations
23
checked on Oct 2, 2024
Page view(s)
110
checked on Oct 15, 2024
Download(s)
25
checked on Oct 15, 2024
Google ScholarTM
Check
Altmetric
Altmetric
This item is licensed under a Creative Commons License