CONTROLAB: integration of intelligent systems for speech recognition, image processing, and trajectory control with obstacle avoidance aiming at robotics applications
E.P.L. Aude, J.T.C. Silveira, Fabrício Alves Barbosa da Silva, Mario F. Martins, Henrique Serdeira, Emerson P. Lopes · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1997
CONTROLAB is an environment which integrates intelligent systems and control algorithms aiming at applications in the area of robotics. Within CONTROLAB, two neural network architectures based on the backpropagation and the recursive models are proposed for the implementation of a robust speaker-independent word recognition system. The robustness of the system using the backpropagation network has been largely verified through use by children and adults in totally uncontrolled environments such as large public halls for the exhibition of new technology products. Experimental results with the recursive network show that it is able to overcome the backpropagation network major drawback, the frequent generation of false alarms. In addition, within CONTROLAB, the trajectory to be followed by a robot arm under self-tuning control is determined by a system which uses either VGRAPH or PFIELD algorithms to avoid obstacles detected by the computer vision system. The performance of the second algorithm is greatly improved when it is applied under the control of a rule-based system. An application in which a SCARA robot arm is commanded by voice to pick up a specific tool placed on a table among other tools and obstacles is currently running. This application is used to evaluate the performance of each sub-system within CONTROLAB.