The Application of a Dendritic Cell Algorithm to a Robotic Classifier
Robert Oates, Julie Greensmith, Uwe Aickelin, Jonathan M Garibaldi, Graham Kendall
Artificial Immune Systems, Proceedings | Springer Verlag | Published : 2007
The dendritic cell algorithm is an immune-inspired technique for processing time-dependent data. Here we propose it as a possible solution for a robotic classification problem. The dendritic cell algorithm is implemented on a real robot and an investigation is performed into the effects of varying the migration threshold median for the cell population. The algorithm performs well on a classification task with very little tuning. Ways of extending the implementation to allow it to be used as a classifier within the field of robotic security are suggested.
Many thanks to William Wilson for his input to the software architecture and to Daniel Bardsley for his advice on image processing. The authors are very grateful to Mark Hammonds for generating the vector graphics for this paper.This work is financially supported by MobileRobots Inc.