ROBOG: Robo guide with simple learning strategy

Author

Harish, Y. ; Kumar, R. Kranthi ; Feroz, G. M. D. Irfan ; Jada, Chakravarthi ; Kumar, V. Anil ; Mesa, Mounika

Author_Institution

Rajiv Gandhi Univ. of Knowledge Technol., Basar, India

fYear

2014

fDate

Feb. 28 2014-March 2 2014

Firstpage

224

Lastpage

228

Abstract

This paper presents ROBOG; an experimental effort in building an autonomous robot that can learn the navigation system of a known terrain and use it for guiding. It is equipped with Artificial Neural Network for the task of Decision making. ROBOG was trained to learn the geographical structure of a floor in an academic block of RGUKT and is tested successfully to guide a person from anywhere to any specific classroom in the trained region. The training of ANN is done with Error Back Propagation algorithm and Particle Swarm Optimization. Results are provided showing the superiority of PSO over conventional EBP in training the ANN. It can easily be trained for other type of structures as well. Some outlook of future work and extensions are suggested.

Keywords

backpropagation; intelligent robots; mobile robots; neural nets; particle swarm optimisation; ANN training; RGUKT; ROBOG testing; ROBOG training; academic block; artificial neural network; autonomous robot learning strategy; decision making; error backpropagation algorithm; floor geographical structure learning; known terrain; mobile robot; navigation system; particle swarm optimization; robot guide; trained region; Artificial neural networks; Biological neural networks; Navigation; Robot sensing systems; Training; Artificial Neural Networks; Branch; Error Back Propagation Algorithm; Learning; Multi Layer Perceptron; Node; Particle Swarm Optimization; RoboGuide;

fLanguage

English

Publisher

ieee

Conference_Titel

Students' Technology Symposium (TechSym), 2014 IEEE

Conference_Location

Kharagpur

Print_ISBN

978-1-4799-2607-7

Type

conf

DOI

10.1109/TechSym.2014.6808051

Filename

6808051