Robot navigation using a sparse distributed memory

Despite all the progress that has been made in Robotics and Artificial Intelligence, traditional approaches seem unsuitable to build truly intelligent robots, exhibiting human-like behaviours. Many authors agree that the source of intelligence is, to a great extent, the use of a huge memory, where s...

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Bibliographic Details
Published in:2008 IEEE International Conference on Robotics and Automation pp. 53 - 58
Main Authors: Mendes, M., Crisostomo, M., Coimbra, A.P.
Format: Conference Proceeding
Language:English
Published: IEEE 01.05.2008
Subjects:
Artificial intelligence
Brain modeling
Humanoid robots
Humans
Image retrieval
Intelligent robots
Navigation
Orbital robotics
Predictive models
robot navigation
Robotics and automation
sparse distributed memory
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ISBN:1424416469, 9781424416462
ISSN:1050-4729
Online Access:Get full text
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Summary:Despite all the progress that has been made in Robotics and Artificial Intelligence, traditional approaches seem unsuitable to build truly intelligent robots, exhibiting human-like behaviours. Many authors agree that the source of intelligence is, to a great extent, the use of a huge memory, where sequences of events that guide our later behaviour are stored. Inspired by that idea, our approach is to navigate a robot using sequences of images stored in a Sparse Distributed Memory-a kind of associative memory based on the properties of high dimensional binary spaces, which, in theory, exhibits some human-like behaviours. The robot showed good ability to correctly follow most of the sequences learnt, with small errors and good immunity to the kidnapped robot problem.
ISBN:1424416469
9781424416462
ISSN:1050-4729
DOI:10.1109/ROBOT.2008.4543186