Environment mapping for mobile robots navigation using hierarchical neural network and omnivision
MetadataShow full item record
Autonomous robots must be able to learn and maintain models of their environments. In this context, the present work considers techniques for the classification and extraction of features from images in joined with artificial neural networks in order to use them in the system of mapping and localization of the mobile robot of Laboratory of Automation and Evolutive Computer (LACE). To do this, the robot uses a sensorial system composed for ultrasound sensors and a catadioptric vision system formed by a camera and a conical mirror. The mapping system is composed by three modules. Two of them will be presented in this paper: the classifier and the characterizer module. The first module uses a hierarchical neural network to do the classification; the second uses techiniques of extraction of attributes of images and recognition of invariant patterns extracted from the places images set. The neural network of the classifier module is structured in two layers, reason and intuition, and is trained to classify each place explored for the robot amongst four predefine classes. The final result of the exploration is the construction of a topological map of the explored environment. Results gotten through the simulation of the both modules of the mapping system will be presented in this paper. © 2008 IEEE.
How to cite this document
Showing items related by title, author, creator and subject.
Godoy, Eduardo Paciência ; Tangerino, Giovana Tangerino; Tabile, Rubens André; Inamasu, Ricardo Yassushi; Porto, Arthur José Vieira (Journal of Control Science and Engineering, 2012) [Artigo]A current trend in the agricultural area is the development of mobile robots and autonomous vehicles for precision agriculture (PA). One of the major challenges in the design of these robots is the development of the ...
A proposed neural control for the trajectory tracking of a nonholonomic mobile robot with disturbances Martins, Nardênio A.; De Alencar, Maycol; Lombardi, Warody C.; Bertol, Douglas W.; De Pieri, Edson R.; Filho, Humberto F. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2012) [Trabalho apresentado em evento]In this paper, a trajectory tracking control problem for a nonholonomic mobile robot by the integration of a kinematic neural controller (KNC) and a torque neural controller (TNC) is proposed, where both the kinematic and ...
Lulio, Luciano C.; Tronco, Mario L.; Porto, Arthur J. V. (Proceedings of IEEE International Symposium on Computational Intelligence in Robotics and Automation, CIRA, 2009) [Trabalho apresentado em evento]This project aims to apply image processing techniques in computer vision featuring an omnidirectional vision system to agricultural mobile robots (AMR) used for trajectory navigation problems, as well as localization ...