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Yang M, Sun X, Jia F, Rushworth A, Dong X, Zhang S, Fang Z, Yang G, Liu B. Sensors and Sensor Fusion Methodologies for Indoor Odometry: A Review. Polymers (Basel) 2022; 14:polym14102019. [PMID: 35631899 PMCID: PMC9143447 DOI: 10.3390/polym14102019] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2022] [Revised: 05/05/2022] [Accepted: 05/11/2022] [Indexed: 02/04/2023] Open
Abstract
Although Global Navigation Satellite Systems (GNSSs) generally provide adequate accuracy for outdoor localization, this is not the case for indoor environments, due to signal obstruction. Therefore, a self-contained localization scheme is beneficial under such circumstances. Modern sensors and algorithms endow moving robots with the capability to perceive their environment, and enable the deployment of novel localization schemes, such as odometry, or Simultaneous Localization and Mapping (SLAM). The former focuses on incremental localization, while the latter stores an interpretable map of the environment concurrently. In this context, this paper conducts a comprehensive review of sensor modalities, including Inertial Measurement Units (IMUs), Light Detection and Ranging (LiDAR), radio detection and ranging (radar), and cameras, as well as applications of polymers in these sensors, for indoor odometry. Furthermore, analysis and discussion of the algorithms and the fusion frameworks for pose estimation and odometry with these sensors are performed. Therefore, this paper straightens the pathway of indoor odometry from principle to application. Finally, some future prospects are discussed.
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Affiliation(s)
- Mengshen Yang
- Department of Mechanical, Materials and Manufacturing Engineering, The Faculty of Science and Engineering, University of Nottingham Ningbo China, Ningbo 315100, China; (M.Y.); (F.J.); (B.L.)
- Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo 315201, China;
- Zhejiang Key Laboratory of Robotics and Intelligent Manufacturing Equipment Technology, Ningbo 315201, China
| | - Xu Sun
- Department of Mechanical, Materials and Manufacturing Engineering, The Faculty of Science and Engineering, University of Nottingham Ningbo China, Ningbo 315100, China; (M.Y.); (F.J.); (B.L.)
- Nottingham Ningbo China Beacons of Excellence Research and Innovation Institute, University of Nottingham Ningbo China, Ningbo 315100, China
- Correspondence: (X.S.); (A.R.); (G.Y.)
| | - Fuhua Jia
- Department of Mechanical, Materials and Manufacturing Engineering, The Faculty of Science and Engineering, University of Nottingham Ningbo China, Ningbo 315100, China; (M.Y.); (F.J.); (B.L.)
| | - Adam Rushworth
- Department of Mechanical, Materials and Manufacturing Engineering, The Faculty of Science and Engineering, University of Nottingham Ningbo China, Ningbo 315100, China; (M.Y.); (F.J.); (B.L.)
- Correspondence: (X.S.); (A.R.); (G.Y.)
| | - Xin Dong
- Department of Mechanical, Materials and Manufacturing Engineering, University of Nottingham, Nottingham NG7 2RD, UK;
| | - Sheng Zhang
- Ningbo Research Institute, Zhejiang University, Ningbo 315100, China;
| | - Zaojun Fang
- Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo 315201, China;
- Zhejiang Key Laboratory of Robotics and Intelligent Manufacturing Equipment Technology, Ningbo 315201, China
| | - Guilin Yang
- Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo 315201, China;
- Zhejiang Key Laboratory of Robotics and Intelligent Manufacturing Equipment Technology, Ningbo 315201, China
- Correspondence: (X.S.); (A.R.); (G.Y.)
| | - Bingjian Liu
- Department of Mechanical, Materials and Manufacturing Engineering, The Faculty of Science and Engineering, University of Nottingham Ningbo China, Ningbo 315100, China; (M.Y.); (F.J.); (B.L.)
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