TY - GEN
T1 - Adaptive dynamic control of quadrupedal robotic gaits with artificial reaction networks
AU - Gerrard, Claire E.
AU - McCall, John
AU - Coghill, George M.
AU - Macleod, Christopher
PY - 2012
Y1 - 2012
N2 - The Artificial Reaction Network (ARN) is a bio-inspired connectionist paradigm based on the emerging field of Cellular Intelligence. It has properties in common with both AI and Systems Biology techniques including Artificial Neural Networks, Petri Nets, and S-Systems. In this paper, elements of temporal dynamics and pattern recognition are combined within a single ARN control system for a quadrupedal robot. The results show that the ARN has similar applicability to Artificial Neural Network models in robotic control tasks. In comparison to neural Central Pattern Generator models, the ARN can control gaits and offer reduced complexity. Furthermore, the results show that like spiky neural models, the ARN can combine pattern recognition and complex temporal control functionality in a single network.
AB - The Artificial Reaction Network (ARN) is a bio-inspired connectionist paradigm based on the emerging field of Cellular Intelligence. It has properties in common with both AI and Systems Biology techniques including Artificial Neural Networks, Petri Nets, and S-Systems. In this paper, elements of temporal dynamics and pattern recognition are combined within a single ARN control system for a quadrupedal robot. The results show that the ARN has similar applicability to Artificial Neural Network models in robotic control tasks. In comparison to neural Central Pattern Generator models, the ARN can control gaits and offer reduced complexity. Furthermore, the results show that like spiky neural models, the ARN can combine pattern recognition and complex temporal control functionality in a single network.
KW - Artificial Neural Networks
KW - Artificial Reaction Networks
KW - Biochemical Networks
KW - Cellular Intelligence
UR - https://www.scopus.com/pages/publications/84869077200
UR - https://www.scopus.com/pages/publications/84869077200#tab=citedBy
U2 - 10.1007/978-3-642-34475-6_34
DO - 10.1007/978-3-642-34475-6_34
M3 - Conference contribution
AN - SCOPUS:84869077200
SN - 9783642344749
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 280
EP - 287
BT - Neural Information Processing - 19th International Conference, ICONIP 2012, Proceedings
T2 - 19th International Conference on Neural Information Processing, ICONIP 2012
Y2 - 12 November 2012 through 15 November 2012
ER -