Title
Learning anticipation via spiking networks: application to navigation control.
Abstract
In this paper, we introduce a network of spiking neurons devoted to navigation control. Three different examples, dealing with stimuli of increasing complexity, are investigated. In the first one, obstacle avoidance in a simulated robot is achieved through a network of spiking neurons. In the second example, a second layer is designed aiming to provide the robot with a target approaching system, making it able to move towards visual targets. Finally, a network of spiking neurons for navigation based on visual cues is introduced. In all cases, the robot was assumed to rely on some a priori known responses to low-level sensors (i.e., to contact sensors in the case of obstacles, to proximity target sensors in the case of visual targets, or to the visual target for navigation with visual cues). Based on their knowledge, the robot has to learn the response to high-level stimuli (i.e., range finder sensors or visual input). The biologically plausible paradigm of spike-timing-dependent plasticity (STDP) is included in the network to make the system able to learn high-level responses that guide navigation through a simple unstructured environment. The learning procedure is based on classical conditioning.
Year
DOI
Venue
2009
10.1109/TNN.2008.2005134
IEEE Transactions on Neural Networks
Keywords
Field
DocType
spiking neuron,high-level stimulus,visual target,navigation control,visual cue,spiking network,target sensor,guide navigation,visual input,high-level response,simulated robot,visual cues,spike timing dependent plasticity,navigation,biosensors,classical conditioning,robot control,obstacle avoidance,circuits,control systems,mobile robots,learning artificial intelligence,neural nets
Obstacle avoidance,Sensory cue,Robot control,Computer vision,Computer science,Artificial intelligence,Mobile robot navigation,Robot,Artificial neural network,Mobile robot,Robotics
Journal
Volume
Issue
ISSN
20
2
1941-0093
Citations 
PageRank 
References 
27
1.16
21
Authors
4
Name
Order
Citations
PageRank
Paolo Arena126147.43
Luigi Fortuna2761128.37
Mattia Frasca331360.35
Luca Patané410417.31