Robot Error Detection Using an Artificial Immune System
EH '03 Proceedings of the 2003 NASA/DoD Conference on Evolvable Hardware
The application of a dendritic cell algorithm to a robotic classifier
ICARIS'07 Proceedings of the 6th international conference on Artificial immune systems
Immune-Inspired Adaptable Error Detection for Automated Teller Machines
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Self-organisation for survival in complex computer architectures
SOAR'09 Proceedings of the First international conference on Self-organizing architectures
Collective self-detection scheme for adaptive error detection in a foraging swarm of robots
ICARIS'11 Proceedings of the 10th international conference on Artificial immune systems
Fault detection in analog circuits using a fuzzy dendritic cell algorithm
ICARIS'11 Proceedings of the 10th international conference on Artificial immune systems
Adaptive data-driven error detection in swarm robotics with statistical classifiers
Robotics and Autonomous Systems
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The immune system is a key component in the maintenance of host homeostasis. Key actors in this process are cells known as dendritic cells (DCs). An Artificial Immune System based on DCs (known as the Dendritic Cell Algorithm: DCA) is well established in the literature and has been applied in a number of applications. Work in this paper is concerned with the development of an integrated homeostatic system for small, autonomous robotic systems, implemented on a resource limited micro-controller. As a first step, we have modified the DCA to operate in both simulated robotic units, and a resource constrained micro-controller that can operate in an on-line manner. Errors can be introduced into the robotic unit during operation, and these can be detected and then circumvented by the modified DCA.