A fuzzy temporal rule-based velocity controller for mobile robotics

Authors:
M. Mucientes;R. Iglesias;C. V. Regueiro;A. Bugarín;S. Barro
Affiliations:
Department of Electronics and Computer Science, University of Santiago de Compostela, 15782 Santiago de Compostela, Spain;Department of Electronics and Computer Science, University of Santiago de Compostela, 15782 Santiago de Compostela, Spain;Department of Electronics and Systems, University of A Coruña, 15071 A Coruña, Spain;Department of Electronics and Computer Science, University of Santiago de Compostela, 15782 Santiago de Compostela, Spain;Department of Electronics and Computer Science, University of Santiago de Compostela, 15782 Santiago de Compostela, Spain
Venue:
Fuzzy Sets and Systems - Special issue: Fuzzy set techniques for intelligent robotic systems
Year:
2003

Citing 6
Cited 4

Representation and use of imprecise temporal knowledge in dynamic systems

Fuzzy Sets and Systems
Attention to time in fuzzy logic

Fuzzy Sets and Systems
Dynamical fuzzy reasoning and its application to system modeling

Fuzzy Sets and Systems
Self-organizing maps

Self-organizing maps
Supervised Reinforcement Learning: Application to a Wall Following Behaviour in a Mobile Robot

IEA/AIE '98 Proceedings of the 11th International Conference on Industrial and Engineering Applications of Artificial In telligence and Expert Systems: Tasks and Methods in Applied Artificial Intelligence
Fuzzy temporal rules: a rule-based approach for fuzzy temporal knowledge representation and reasoning

Technologies for constructing intelligent systems

Fuzzy constraint satisfaction approach for landmark recognition in mobile robotics

AI Communications
Design of a fuzzy controller in mobile robotics using genetic algorithms

Applied Soft Computing
A case study for learning behaviors in mobile robotics by evolutionary fuzzy systems

Expert Systems with Applications: An International Journal
People detection through quantified fuzzy temporal rules

Pattern Recognition

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper describes a velocity controller implemented on a Nomad 200 mobile robot. The controller has been developed for wall-following behaviour, and its design is modularized into two blocks: angular and linear velocity control. A simple design and implementation was made for the former, with the aim of focusing the design efforts on the linear velocity control block, in order to remark the usefulness of this task. The latter has been implemented using an explicit model for knowledge representation and reasoning called fuzzy temporal rules (FTRs). This model enables to explicitly incorporate time as a variable, due to which the evolution of variables in a temporal reference can be described. Using this mechanism we obtain linear velocity values that are adapted to each different circumstance, and thus a higher average velocity as well as smoother and more robust behaviours are achieved.