3D Backscatter Localization for Fine-Grained Robotics

Authors: 

Zhihong Luo, Qiping Zhang, Yunfei Ma, Manish Singh, and Fadel Adib, MIT Media Lab

Abstract: 

This paper presents the design and implementation of TurboTrack, a 3D localization system for fine-grained robotic tasks. TurboTrack's unique capability is that it can localize backscatter nodes with sub-centimeter accuracy without any constraints on their locations or mobility. TurboTrack makes two key technical contributions. First, it presents a pipelined architecture that can extract a sensing bandwidth from every single backscatter packet that is three orders of magnitude larger than the backscatter communication bandwidth. Second, it introduces a Bayesian space-time super-resolution algorithm that combines time series of the sensed bandwidth across multiple antennas to enable accurate positioning. Our experiments show that TurboTrack simultaneously achieves a median accuracy of sub-centimeter in each of the x/y/z dimensions and a $99^{th}$ percentile latency less than 7.5 milliseconds in 3D localization. This enables TurboTrack's real-time prototype to achieve fine-grained positioning for agile robotic tasks, as we demonstrate in multiple collaborative applications with robotic arms and nanodrones including indoor tracking, packaging, assembly, and handover.

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BibTeX
@inproceedings {227645,
author = {Zhihong Luo and Qiping Zhang and Yunfei Ma and Manish Singh and Fadel Adib},
title = {3D Backscatter Localization for Fine-Grained Robotics},
booktitle = {16th {USENIX} Symposium on Networked Systems Design and Implementation ({NSDI} 19)},
year = {2019},
isbn = {978-1-931971-49-2},
address = {Boston, MA},
pages = {765--782},
url = {https://www.usenix.org/conference/nsdi19/presentation/luo},
publisher = {{USENIX} Association},
}