Vision-Based Autonomous Navigation with Evolutionary Learning

Journal
Advances in Computational Intelligence
Lecture Notes in Computer Science
ISSN
0302-9743
1611-3349
Date Issued
2020
Author(s)
Coronel, Sandra L.
Chávez Domínguez, Rodrigo
Type
text::conference output::conference proceedings::conference paper
DOI
URL
Abstract
In this paper, we propose a vision-based autonomous robotics navigation system, it uses a bio-inspired optical flow approach using the Hermite transform and a fuzzy logic controller, the input membership functions were tuned applying a distributed evolutionary learning based on social wound treatment inspired in the Megaponera analis ant. The proposed method was implemented in a virtual robotics system using the V-REP software and in communication con MATLAB. The results show that the optimization of the input fuzzy membership functions improves the navigation behavior against an empirical tuning of them. © 2020, Springer Nature Switzerland AG.