TY - JOUR
T1 - Adaptive Online Fault Diagnosis in Autonomous Robot Swarms
AU - O'Keefe, James
AU - Tarapore, Danesh Sarosh
AU - Millard, Alan Gregory
AU - Timmis, Jonathan Ian
N1 - © 2018 O’Keeffe, Tarapore, Millard and Timmis
PY - 2018/11/30
Y1 - 2018/11/30
N2 - Previous work has shown that robot swarms are not always tolerant to the failure of individual robots, particularly those that have only partially failed and continue to contribute to collective behaviors. A case has been made for an active approach to fault tolerance in swarm robotic systems, whereby the swarm can identify and resolve faults that occur during operation. Existing approaches to active fault tolerance in swarms have so far omitted fault diagnosis, however we propose that diagnosis is a feature of active fault tolerance that is necessary if swarms are to obtain long-term autonomy. This paper presents a novel method for fault diagnosis that attempts to imitate some of the observed functions of natural immune system. The results of our simulated experiments show that our system is flexible, scalable, and improves swarm tolerance to various electro-mechanical faults in the cases examined
AB - Previous work has shown that robot swarms are not always tolerant to the failure of individual robots, particularly those that have only partially failed and continue to contribute to collective behaviors. A case has been made for an active approach to fault tolerance in swarm robotic systems, whereby the swarm can identify and resolve faults that occur during operation. Existing approaches to active fault tolerance in swarms have so far omitted fault diagnosis, however we propose that diagnosis is a feature of active fault tolerance that is necessary if swarms are to obtain long-term autonomy. This paper presents a novel method for fault diagnosis that attempts to imitate some of the observed functions of natural immune system. The results of our simulated experiments show that our system is flexible, scalable, and improves swarm tolerance to various electro-mechanical faults in the cases examined
U2 - 10.3389/frobt.2018.00131
DO - 10.3389/frobt.2018.00131
M3 - Article
SN - 2296-9144
VL - 5
JO - Frontiers in Robotics and AI
JF - Frontiers in Robotics and AI
M1 - 131
ER -