Analysis of cooperative localisation performance under varying sensor qualities and communication rates
Autor: | Nick Sullivan, Steven Grainger, Benjamin S. Cazzolato |
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Rok vydání: | 2018 |
Předmět: |
0209 industrial biotechnology
Computer science General Mathematics 02 engineering and technology Computer Science Applications Power (physics) 020901 industrial engineering & automation Control and Systems Engineering Position (vector) 0202 electrical engineering electronic engineering information engineering Robot 020201 artificial intelligence & image processing Software Simulation |
Zdroj: | Robotics and Autonomous Systems. 110:73-84 |
ISSN: | 0921-8890 |
DOI: | 10.1016/j.robot.2018.09.010 |
Popis: | Cooperative Localisation (CL) is a robust technique used to improve localisation accuracy in multi-robot systems. However, there is a lack of research on how CL performs under different conditions. It is unclear when CL is worthwhile, and how CL performance is affected if the system changes. This information is particularly important for systems with robots that have limited power and processing, which cannot afford to constantly perform CL. This paper investigates CL under varying sensor qualities (position accuracy, yaw accuracy, sample rate), communication rates, and number of robots for both homogeneous and heterogeneous multi-robot systems. Trends are found in MATLAB simulations using the UTIAS dataset, and then validated on Kobuki robots using an OptiTrack-based system. We find that yaw accuracy has a substantial effect on performance, a communication rate that is too fast can be detrimental, and heterogeneous systems are greater candidates for cooperative localisation than homogeneous systems. |
Databáze: | OpenAIRE |
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