TY - GEN
T1 - Immune-Inspired Error Detection for Multiple Faulty Robots in Swarm Robotics
AU - Lau, Hui Keng
AU - Bate, Iain
AU - Timmis, Jon
N1 - Funding Information:
We acknowledge the Swedish Foundation for Strategic Research (SSF) SYNOPSIS Project and Artificial Intelligence Research Unit, Universiti Malaysia Sabah for supporting this work.
Publisher Copyright:
© 2013 Proceedings of the 12th European Conference on the Synthesis and Simulation of Living Systems: Advances in Artificial Life, ECAL 2013. All rights reserved.
PY - 2013
Y1 - 2013
N2 - Error detection and recovery are important issues in swarm robotics research, as they are a means by which fault tolerance can be achieved. Our previous work has looked at error detection for single failures in a swarm robotics scenario with the Receptor Density Algorithm. Three modes of failure to the wheels of individual robots was investigated and comparable performance to other statistical methods was achieved. In this paper, we investigate the potential of extending this approach to a robot swarm with multiple faulty robots. Two experiements have been conducted: A swarm of ten robots with 1 to 8 faulty robots, and a swarm of 10 to 20 robots with varying number of faulty robots. Results from the experiments showed that the proposed approach is able to detect errors in multiple faulty robots. The results also suggest the need to further investigate other aspects of the robot swarm that can potentially affect the performance of detection such as the communication range.
AB - Error detection and recovery are important issues in swarm robotics research, as they are a means by which fault tolerance can be achieved. Our previous work has looked at error detection for single failures in a swarm robotics scenario with the Receptor Density Algorithm. Three modes of failure to the wheels of individual robots was investigated and comparable performance to other statistical methods was achieved. In this paper, we investigate the potential of extending this approach to a robot swarm with multiple faulty robots. Two experiements have been conducted: A swarm of ten robots with 1 to 8 faulty robots, and a swarm of 10 to 20 robots with varying number of faulty robots. Results from the experiments showed that the proposed approach is able to detect errors in multiple faulty robots. The results also suggest the need to further investigate other aspects of the robot swarm that can potentially affect the performance of detection such as the communication range.
UR - http://www.scopus.com/inward/record.url?scp=84908531956&partnerID=8YFLogxK
U2 - 10.7551/978-0-262-31709-2-ch124
DO - 10.7551/978-0-262-31709-2-ch124
M3 - Conference Proceeding (Non-Journal item)
AN - SCOPUS:84908531956
T3 - Proceedings of the 12th European Conference on the Synthesis and Simulation of Living Systems: Advances in Artificial Life, ECAL 2013
SP - 846
EP - 853
BT - Proceedings of the 12th European Conference on the Synthesis and Simulation of Living Systems
PB - MIT Press Journals
T2 - 12th European Conference on the Synthesis and Simulation of Living Systems: Advances in Artificial Life, ECAL 2013
Y2 - 2 September 2013 through 6 September 2013
ER -