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A Low Cost Omnidirectional Relative Localization Sensor for Swarm Applications
Luleå University of Technology.
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Embedded Internet Systems Lab.ORCID iD: 0000-0001-9586-0991
Monash Swarm Robotics Laboratory, Monash University.
Monash Swarm Robotics Laboratory, Monash University.
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2018 (English)In: IEEE 4th World Forum on Internet of Things, Institute of Electrical and Electronics Engineers (IEEE), 2018, p. 694-699Conference paper, Published paper (Refereed)
Abstract [en]

By enabling coordinated task execution and movement, robotic swarms can achieve efficient exploration of unknown environments. In this paper, we propose a relative localization sensor system using Ultra-wideband (UWB) radio technology for ranging. This system is light-weight and relatively indifferent to the types of surrounding environments. Infrastructure dependency such as the requirement of beacons at known locations is eliminated by making an array of sensors on a swarm agent. In this paper, a novel algorithm is implemented on hardware with limited resources and compared to a more traditional trilateration approach. Both utilize Particle Swarm Optimization (PSO) to be more robust against noise and to achieve similar accuracy. The experimental results show that the proposed algorithm runs up to ten times faster than the existing trilateration approach. The sensor array which forms the localization system weighs only 56g, and achieves around 0.5m RMSE with a 10Hz update rate. Experiments show that the accuracy can be further improved if the rotational bias observed in the UWB devices are compensated for.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2018. p. 694-699
National Category
Engineering and Technology Other Electrical Engineering, Electronic Engineering, Information Engineering
Research subject
Industrial Electronics
Identifiers
URN: urn:nbn:se:ltu:diva-67643DOI: 10.1109/WF-IoT.2018.8355093OAI: oai:DiVA.org:ltu-67643DiVA, id: diva2:1182585
Conference
2018 IEEE 4th World Forum on Internet of Things (WF-IoT), Singapore, 5-8 Feb. 2018
Projects
Productive4.0ArrowheadAvailable from: 2018-02-14 Created: 2018-02-14 Last updated: 2018-06-08Bibliographically approved

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Kohlbacher, AntonEliasson, Jens
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