ROBOG Autonomously Navigating Outdoor Robo-Guide

Autor:	Harish Yenala, Anil Kumar Vadathya, Irfan Feroz Gramoni Mohammed, Kranthi Kumar Rachavarapu, Chakravarthi Jada
Rok vydání:	2015
Předmět:	Identification (information) Artificial neural network business.industry Feature (computer vision) Computer science Node (networking) Locality Computer vision Image processing Artificial intelligence Image segmentation business Perceptron
Zdroj:	Swarm, Evolutionary, and Memetic Computing ISBN: 9783319202938 SEMCCO
DOI:	10.1007/978-3-319-20294-5_70
Popis:	ROBOG: The Robo-Guide is an autonomously navigating vehicle capable of learning the navigational directions of a locality by using Artificial Neural Networks. The main task of ROBOG is to guide people from one location to any other location in a trained region. The prime feature of ROBOG is its simplicity of implementation and working. The map information is learned by Artificial Neural Network using the proposed concept of branch and node. The Multi-Layered Perceptron is trained using the standard Error Back Propagation Algorithm. Road Detection & Tracking and Destination Identification are employed to achieve autonomous navigation. All the Image Processing techniques used are computationally inexpensive. The ROBOG is tested successfully in the outdoor environment for autonomous navigation and due to the simplicity in implementation it can be easily trained for any region.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::510ddf27ad1cb426e4ad2dbd7a0141d2 https://doi.org/10.1007/978-3-319-20294-5_70 Zobrazit plný text záznamu