Zyggie: A Wireless Body Area Network platform for indoor positioning and motion tracking

Abstract : Nowadays, there is a high demand for human and/or objects monitoring/localizing in the context of applications like Building Information Modeling (BIM), automated drone missions, contextual visits of museum or sports monitoring for instance. While for outdoor positioning accurate and robust solutions (i.e. GPS) exist for many years, indoor positioning is still very challenging. There is also a need of gesture/motion tracking systems that could replace video solutions. We propose in this paper a hardware/software platform named Zyggie that combines both Ultra Wide Band (UWB) technology and Received Signal Strength Indicator (RSSI) for low power accurate indoor positioning and Inertial Measurement Unit (IMU) utilization for motion tracking. Very few industrial/academic existing solutions can simultaneously perform indoor positioning and motion tracking and none of them can do both under low power, low cost and compacity constraints addressed by our platform. As Zyggie has the capability to estimate distances w.r.t other platforms in the environment and quaternions (which represents the attitude/orientation) users can test/enhance state of the art algorithms for positioning and motion tracking applications.
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Antoine Courtay, Mickaël Le Gentil, Olivier Berder, Arnaud Carer, Pascal Scalart, et al.. Zyggie: A Wireless Body Area Network platform for indoor positioning and motion tracking. ISCAS 2018 - IEEE International Symposium on Circuits and Systems, May 2018, Florence, Italy. pp.1-5, ⟨10.1109/ISCAS.2018.8351278⟩. ⟨hal-01804927⟩

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