期刊
IEEE TRANSACTIONS ON ROBOTICS
卷 35, 期 6, 页码 1516-1522出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TRO.2019.2929015
关键词
Robot sensing systems; Fault detection; Mobile robots; Task analysis; Reliability; Collective behavior; fault detection; multirobot systems; robot swarms
类别
资金
- Marie Curie Intra-European Fellowship [GiFteD-MrS/623620]
- Engineering and Physical Sciences Research Council (EPSRC) [EP/R030073/1, EP/K040820/1]
- EPSRC [EP/R030073/1, EP/K040820/1] Funding Source: UKRI
The ability to reliably detect faults is essential in many real-world tasks that robot swarms have the potential to perform. Most studies on fault detection in swarm robotics have been conducted exclusively in simulation, and they have focused on a single type of fault or a specific task. In a series of previous studies, we have developed a robust fault-detection approach in which robots in a swarm learn to distinguish between normal and faulty behaviors online. In this paper, we assess the performance of our fault-detection approach on a swarm of seven physical mobile robots. We experiment with three classic swarm robotics tasks and consider several types of faults in both sensors and actuators. Experimental results show that the robots are able to reliably detect the presence of hardware faults in one another even when the swarm behavior is changed during operation. This paper is thus an important step toward making robot swarms sufficiently reliable and dependable for real-world applications.
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