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Automatic calibration of a spiking head-direction network for representing robot orientation

Stratton, Peter, Milford, Michael, Wiles, Janet, & Wyeth, Gordon (2009) Automatic calibration of a spiking head-direction network for representing robot orientation. In Scheding, Steve (Ed.) Proceedings of Australasian Conference on Robotics and Automation 2009, Australian Robotics and Automation Association Inc, Sydney.

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Abstract

Calibration of movement tracking systems is a difficult problem faced by both animals and robots. The ability to continuously calibrate changing systems is essential for animals as they grow or are injured, and highly desirable for robot control or mapping systems due to the possibility of component wear, modification, damage and their deployment on varied robotic platforms. In this paper we use inspiration from the animal head direction tracking system to implement a self-calibrating, neurally-based robot orientation tracking system. Using real robot data we demonstrate how the system can remove tracking drift and learn to consistently track rotation over a large range of velocities. The neural tracking system provides the first steps towards a fully neural SLAM system with improved practical applicability through selftuning and adaptation.

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ID Code: 32856
Item Type: Conference Paper
Additional URLs:
ISBN: 9780980740400
Subjects: Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100) > Adaptive Agents and Intelligent Robotics (080101)
Australian and New Zealand Standard Research Classification > PSYCHOLOGY AND COGNITIVE SCIENCES (170000) > COGNITIVE SCIENCE (170200) > Neurocognitive Patterns and Neural Networks (170205)
Copyright Owner: Copyright 2009 [please consult the authors]
Deposited On: 24 Jun 2010 13:27
Last Modified: 01 Mar 2012 00:14

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