3D backscatter localization for fine-grained robotics

Zhihong Luo, Qiping Zhang, Yunfei Ma, Manish Singh, Fadel Adib

Abstract:

This paper presents the design, implementation, and evaluation 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
99th 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