Name
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. |
Year | Venue | Field |
|---|---|---|
2019 | PROCEEDINGS OF THE 16TH USENIX SYMPOSIUM ON NETWORKED SYSTEMS DESIGN AND IMPLEMENTATION | Computer science,Backscatter,Real-time computing,Computational science,Artificial intelligence,Robotics |
DocType | Citations | PageRank |
Conference | 0 | 0.34 |
References | Authors | |
0 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Zhihong Luo | 1 | 15 | 2.37 |
| Qiping Zhang | 2 | 104 | 12.87 |
| Yunfei Ma | 3 | 100 | 6.55 |
| Singh, Manish | 4 | 13 | 2.12 |
| Fadel Adib | 5 | 853 | 37.98 |