Constructing Floor Plan through Smoke Using Ultra Wideband Radar

Author:

Chen Weiyan1,Zhang Fusang2,Gu Tao3,Zhou Kexing4,Huo Zixuan4,Zhang Daqing5

Affiliation:

1. Key Laboratory of High Confidence Software Technologies (Ministry of Education), School of Electronics Engineering and Computer Science, Peking University, Beijing, P.R China

2. State Key Laboratory for Novel Software Technology, Nanjing University, Nanjing, P.R China; State Key Laboratory of Computer Sciences, Institute of Software, Chinese Academy of Sciences, Beijing, P.R China

3. Department of Computing, Macquarie University, Australia

4. School of Electronics Engineering and Computer Science, Peking University, Beijing, P.R China

5. Key Laboratory of High Confidence Software Technologies (Ministry of Education), School of Electronics Engineering and Computer Science, Peking University, Beijing, China, Département Réseaux et Services Multimédia Mobiles, Institut Polytechnique de Paris, Evry, France

Abstract

Floor plan construction has been one of the key techniques in many important applications such as indoor navigation, location-based services, and emergency rescue. Existing floor plan construction methods require expensive dedicated hardware (e.g., Lidar or depth camera), and may not work in low-visibility environments (e.g., smoke, fog or dust). In this paper, we develop a low-cost Ultra Wideband (UWB)-based system (named UWBMap) that is mounted on a mobile robot platform to construct floor plan through smoke. UWBMap leverages on low-cost and off-the-shelf UWB radar, and it is able to construct an indoor map with an accuracy comparable to Lidar (i.e., the state-of-the-art). The underpinning technique is to take advantage of the mobility of radar to form virtual antennas and gather spatial information of a target. UWBMap also eliminates both robot motion noise and environmental noise to enhance weak reflection from small objects for the robust construction process. In addition, we overcome the limited view of single radar by combining multi-view from multiple radars. Extensive experiments in different indoor environments show that UWBMap achieves a map construction with a median error of 11 cm and a 90-percentile error of 26 cm, and it operates effectively in indoor scenarios with glass wall and dense smoke.

Funder

EU Horizon 2020 research and innovation programme IDEA-FAST

EU CHIST-ERA RadioSense Project

PKU-NTU collaboration Project

PKU-Baidu Fund

Youth Innovation Promotion Association of the Chinese Academy of Sciences

National Natural Science Foundation of China A3 Foresight Program

National Natural Science Foundation of China

Publisher

Association for Computing Machinery (ACM)

Subject

Computer Networks and Communications,Hardware and Architecture,Human-Computer Interaction

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2. Hand Gesture Recognition Using an IR-UWB Radar with an Inception Module-Based Classifier

3. Remote Monitoring of Human Vital Signs Using mm-Wave FMCW Radar

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