PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Movement generation and control with generic neural microcircuits
Prashant Joshi and Wolfgang Maass
In: Biologically Inspired Approaches to Advanced Information Technology. First International Workshop, BioADIT 2004, Lausanne, Switzerland. Lecture Notes in Computer Science (3141). (2004) Springer Verlag , pp. 258-273.

Abstract

Simple linear readouts from generic neural microcircuit models can be trained to generate and control basic movements, e.g., reaching with an arm to various target points. After suitable training of these readouts on a small number of target points; reaching movements to nearby points can also be generated. Sensory or proprioceptive feedback turns out to improve the performance of the neural microcircuit model, if it arrives with a significant delay of 25 to 100 ms. Furthermore, additional feedbacks of “prediction of sensory variables” are shown to improve the performance significantly. Existing control methods in robotics that take the particular dynamics of sensors and actuators into account(“embodiment of robot control”) are taken one step further with this approach which provides methods for also using the “embodiment of computation”, i.e. the inherent dynamics and spatial structure of neural circuits, for the design of robot movement controllers.

EPrint Type:Book Section
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Learning/Statistics & Optimisation
ID Code:1287
Deposited By:Wolfgang Maass
Deposited On:28 November 2005