TOWARDS ROBOT VISION MODULE DEVELOPMENT WITH EXPERIENTIAL ROBOT LEARNING
n this paper we present a thrust in three directions of visual development us- ing supervised and semi-supervised techniques.The first is an implementation of semi-supervised object detection and recognition using the principles of Soft At- tention and Generative Adversarial Networks.The second and the third are supervised networks that learn basic concepts of spatial locality and quantity respectively using Convolutional Neural Networks.The three thrusts to- gether are based on the approach of Experiential Robot Learning, introduced in previous publication.While the results are unripe for implementation, we believe they constitute a stepping stone towards autonomous development of robotic vi- sual modules.
3 thrusts serving as stepping stones for robot experiential learning of vision moduleInvestigates is performance of existing image classifiers and object detectors. 