Sciweavers

NN
2008
Springer

Event detection and localization for small mobile robots using reservoir computing

13 years 10 months ago
Event detection and localization for small mobile robots using reservoir computing
Reservoir Computing (RC) techniques use a fixed (usually randomly created) recurrent neural network, or more generally any dynamic system, which operates at the edge of stability, where only a linear static readout output layer is trained by standard linear regression methods. In this work, RC is used for detecting complex events in autonomous robot navigation. This can be extended to robot localization tasks which are solely based on a few low-range, high-noise sensory data. The robot thus builds an implicit map of the environment (after learning) that is used for efficient localization by simply processing the stream of distance sensors. These techniques are demonstrated in both a simple simulation environment and in the physically realistic Webots simulation of the commercially available e-puck robot, using several complex and even dynamic environments. Key words: Reservoir Computing, Robot localization, Event detection
Eric A. Antonelo, Benjamin Schrauwen, Dirk Strooba
Added 14 Dec 2010
Updated 14 Dec 2010
Type Journal
Year 2008
Where NN
Authors Eric A. Antonelo, Benjamin Schrauwen, Dirk Stroobandt
Comments (0)