Authors:
Vanderlei Bonato
1
;
Adriano K. Sanches
2
;
M.M. Fernandes
3
;
João M. P. Cardoso
4
;
E. D. V. Simoes
2
and
Eduardo Marques
2
Affiliations:
1
University of São Paulo, Brazil
;
2
University of Sao Paulo, Brazil
;
3
University Metodista of Piracicaba - UNIMEP, Brazil
;
4
University of Algarve, Portugal
Keyword(s):
Robotics, FPGA, SoC, Vision System, Gesture Recognition, RAM-Based Neural Network.
Related
Ontology
Subjects/Areas/Topics:
Human-Robots Interfaces
;
Image Processing
;
Informatics in Control, Automation and Robotics
;
Robot Design, Development and Control
;
Robotics and Automation
;
Vehicle Control Applications
;
Vision, Recognition and Reconstruction
Abstract:
This paper presents a vision system to be embedded in a mobile robot, both of them implemented using reconfigurable computing technology. The vision system captures gestures by means of a digital color camera, and then performs some pre-processing steps in order to use the image as input to a RAM-based neural network. The set of recognized gestures can be dened using the system on-chip training capabilities. All the above functionality has been implemented in a single FPGA chip. Experimental results have shown the system to be robust, with enough performance to meet real-time constraints (30 fps), and also high efficiency in the recognition process (true recognition rate of 99.57%).