3-D Motion Capture of an Unmodified Drone with Single-chip Millimeter Wave Radar

Peijun Zhao, Chris Xiaoxuan Lu, Bing Wang, Niki Trigoni, Andrew Markham

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Accurate motion capture of aerial robots in 3-D is a key enabler for autonomous operation in indoor environments such as warehouses or factories, as well as driving forward research in these areas. The most commonly used solutions at present are optical motion capture (e.g. VICON) and Ultra-wideband (UWB), but these are costly and cumbersome to deploy, due to their requirement of multiple cameras/sensors spaced around the tracking area. They also require the drone to be modified to carry an active or passive marker. In this work, we present an inexpensive system that can be rapidly installed, based on single-chip millimeter wave (mmWave) radar. Importantly, the drone does not need to be modified or equipped with any markers, as we exploit the Doppler signals from the rotating propellers. Furthermore, 3-D tracking is possible from a single point, greatly simplifying deployment. We develop a novel deep neural network and demonstrate decimeter level 3-D tracking at 10Hz, achieving better performance than classical baselines. Our hope is that this low-cost system will act to catalyse inexpensive drone research and increased autonomy.
Original languageEnglish
Title of host publication2021 IEEE International Conference on Robotics and Automation (ICRA)
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Number of pages7
Publication statusAccepted/In press - 28 Feb 2021
Event2021 IEEE International Conference on Robotics and Automation - Xi'an, China
Duration: 30 May 20215 Jun 2021
http://www.icra2021.org/

Conference

Conference2021 IEEE International Conference on Robotics and Automation
Abbreviated titleICRA 2021
CountryChina
CityXi'an
Period30/05/215/06/21
Internet address

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