VISUALLY GUIDED MOVEMENTS - LEARNING WITH MODULAR NEURAL MAPS IN ROBOTICS

Robotics involves complex processing and requires modular controllers. For the connectionist approach, the adaptation of each module within the global system remains a major problem to be solved. This paper pro poses the idea that biological learning can take advantage of the stru ctures of the modules and the nature of modular decomposition. Therefo re, we address this problem starting with the architecture of the syst em. We illustrate this approach using a robotic application: the visua l servoing of the arm's end-effector. The on-line adaptation of a simp le controller permits excellent results. To process several variables, and to limit the size of the memory required, this controller is deco mposed into modules, in the image of sensorial or motor processing cen ters. The learning of the modules is realized on-line, a bidirectional architecture permits the adaptation of each module using a simple alg orithm. The results obtained with various modular arrangements, both d uring intensive computer simulations and on our robotic platform, conf irm the practical interest of this approach. (C) 1998 Elsevier Science Ltd. All rights reserved.