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Indoor localisation is a currently a key issue, from robotics to the Internet of Things. With hardware advancements making Ultra-Wideband devices more accurate and low powered (potentially even passive), this unlocks the potential of having such devices in common place around factories and homes, enabling an alternative method of navigation. Therefore, anchor calibration indoors becomes a key problem in order to implement these devices efficiently and effectively. In this paper, we study the possibility for sequentially gathering Ultra-Wideband Time-of-Arrival measurements and using previously studied robust solvers, merge solutions together in order to calculate anchor positions in 3D in real-time. Here it is assumed that there is no prior knowledge of the anchor positions. This is then validated using Ultra-Wideband Time-of-Arrival data gathered by a Bitcraze Crazyflie quadcopter in 2D motion, 3D motion and full flight.
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Batstone et al. (2017) studied this question.
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