scholarly journals Stable Filtering for Artificial Pheromone Potential Field Constructed By Mobile Robots and Passive RFID Tags

2011 ◽  
Vol 3 (5) ◽  
pp. 107-121
Author(s):  
Piljae Kim ◽  
Daisuke Kurabayashi
Keyword(s):  
Mobile Robots ◽  
Potential Field ◽  
Rfid Tags ◽  
Passive Rfid ◽  
Artificial Pheromone

Artificial potential field neuro-fuzzy controller for autonomous navigation of mobile robots

2020 ◽  
pp. 095965182097483
Author(s):  
Mahamat Loutfi Imrane ◽  
Achille Melingui ◽  
Joseph Jean Baptiste Mvogo Ahanda ◽  
Fredéric Biya Motto ◽  
Rochdi Merzouki
Keyword(s):  
Neural Networks ◽  
Fuzzy Logic ◽  
Mobile Robots ◽  
Potential Field ◽  
Autonomous Navigation ◽  
Fuzzy Logic Controller ◽  
Artificial Potential Field ◽  
Type Reduction ◽  
Interval Type

Some autonomous navigation methods, when implemented alone, can lead to poor performance, whereas their combinations, when well thought out, can yield exceptional performances. We have demonstrated this by combining the artificial potential field and fuzzy logic methods in the framework of mobile robots’ autonomous navigation. In this article, we investigate a possible combination of three methods widely used in the autonomous navigation of mobile robots, and whose individual implementation still does not yield the expected performances. These are as follows: the artificial potential field, which is quick and easy to implement but faces local minima and robustness problems. Fuzzy logic is robust but computationally intensive. Finally, neural networks have an exceptional generalization capacity, but face data collection problems for the learning base and robustness. This article aims to exploit the advantages offered by each of these approaches to design a robust, intelligent, and computationally efficient controller. The combination of the artificial potential field and interval type-2 fuzzy logic resulted in an interval type-2 fuzzy logic controller whose advantage over the classical interval type-2 fuzzy logic controller was the small size of the rule base. However, it kept all the classical interval type-2 fuzzy logic controller characteristics, with the major disadvantage that type-reduction remains the main cause of high computation time. In this article, the type-reduction process is replaced with two layers of neural networks. The resulting controller is an interval type-2 fuzzy neural network controller with the artificial potential field controller’s outputs as auxiliary inputs. The results obtained by performing a series of experiments on a mobile platform demonstrate the proposed navigation system’s efficiency.

Design and Implementation of a Real-Time Object Location System Based on Passive RFID Tags

2015 ◽  
Vol 15 (9) ◽  
pp. 5015-5023 ◽  
Author(s):  
Han-Yen Yu ◽  
Jiann-Jone Chen ◽  
Tien-Ruey Hsiang
Keyword(s):  
Real Time ◽  
Object Location ◽  
Rfid Tags ◽  
Location System ◽  
Design And Implementation ◽  
Passive Rfid

scholarly journals Motion Planning for a Chain of Mobile Robots Using A* and Potential Field

Robotics ◽  
2018 ◽  
Vol 7 (2) ◽  
pp. 20 ◽  
Author(s):  
A poorva ◽  
Rahul Gautam ◽  
Rahul Kala
Keyword(s):  
Motion Planning ◽  
Mobile Robots ◽  
Potential Field ◽  
A Chain

An Integrated a-IGZO UHF Energy Harvester for Passive RFID Tags

2014 ◽  
Vol 61 (9) ◽  
pp. 3289-3295 ◽  
Author(s):  
Adrian Chasin ◽  
Vladimir Volskiy ◽  
Michael Libois ◽  
Kris Myny ◽  
Manoj Nag ◽  
...  
Keyword(s):  
Energy Harvester ◽  
Rfid Tags ◽  
Passive Rfid
Sign in / Sign up

Export Citation Format

Share Document