Indoor 2D Positioning Method for Mobile Robots Based on the Fusion of RSSI and Magnetometer Fingerprints

As a fundamental issue in robotics academia and industry, indoor autonomous mobile robots (AMRs) have been extensively studied. For AMRs, it is crucial to obtain information about their working environment and themselves, which can be realized through sensors and the extraction of corresponding information from the measurements of these sensors. The application of sensing technologies can enable mobile robots to perform localization, mapping, target or obstacle recognition, and motion tasks, etc. This paper reviews sensing technologies for autonomous mobile robots in indoor scenes. The benefits and potential problems of using a single sensor in application are analyzed and compared, and the basic principles and popular algorithms used in processing these sensor data are introduced. In addition, some mainstream technologies of multi-sensor fusion are introduced. Finally, this paper discusses the future development trends in the sensing technology for autonomous mobile robots in indoor scenes, as well as the challenges in the practical application environments.

Section: Overview Of Multi-sensor Fusion Sensing Technologiesmentioning

confidence: 99%

A Review of Sensing Technologies for Indoor Autonomous Mobile Robots

Liu,

Wang,

Xie

et al. 2024

“…Such external estimators can serve as a reference for the internal estimators, as presented in this work. Fingerprinting-based indoor 2D positioning method is proposed in [ 3 ], which utilizes the fusion of RSSI and magnetometer measurements. Autonomous navigation in mining tunnels based on artificial passive landmarks is addressed in [ 4 ].…”

Section: Sensing For Localisationmentioning

confidence: 99%

Advanced Sensors Technologies Applied in Mobile Robot

Klančar

Seder

Blažič

2023

“…Indoor localization is a key focus of research in artificial intelligence (AI) and the Internet of Things (IoT) as 80% of people's daily lives are spent indoors. Several technologies have been developed to achieve accurate indoor localization, including Wi-Fi [1], Bluetooth (BLE), magnetic sensors [2], ultra-wideband (UWB) [3], and visible light communication [4]. While accurate two-dimensional indoor localization is achievable using these technologies, there is currently no robust and environment-independent method for measuring indoor height.…”

Section: Introductionmentioning

confidence: 99%

A Hybrid Indoor Altimetry Based on Barometer and UWB

Wang

Zhou

et al. 2023

Accurate altimetry is essential for location-based services in commercial and industrial applications. However, current altimetry methods only provide low-accuracy measurements, particularly in multistorey buildings with irregular structures, such as hollow areas found in various industrial and commercial sites. This paper innovatively proposes a tightly coupled indoor altimetry system that utilizes floor identification to improve height measurement accuracy. The system includes two optimized algorithms that improve floor identification accuracy through activity detection and address the problem of difficult convergence of z-axis coordinates due to indoor coplanarity by applying constraints to iterative least squares (ILS). Two experiments were conducted in a teaching building and a laboratory, including an irregular environment with a hollow area. The results show that our proposed method for identifying floors based on activity detection outperforms other methods. In dynamic experiments, our method effectively eliminates repeated transformations during the up- and downstairs process, and in static experiments, it minimizes the impact of barometric drift. Furthermore, our proposed altimetry method based on constrained ILS achieves significantly improved positioning accuracy compared to ILS, 1D-CNN, and WC. Specifically, in the teaching building, our method achieves improvements of 0.84 m, 0.288 m, and 0.248 m, respectively, while in the laboratory, the improvements are 2.607 m, 0.696 m, and 0.625 m.