Indoor Positioning Systems (IPS) are essential for a wide range of applications, from robotics and drones to augmented reality. While traditional technologies like WiFi and Bluetooth often fall short in accuracy, VLP stands out as a promising alternative due to its high precision and low infrastructure costs. However, VLP systems have their own limitations, such as susceptibility to signal blockages and the impact of the receiver's changing inclination, which can degrade accuracy. These challenges are especially problematic in dynamic environments where the receiver's orientation fluctuates frequently. Given these issues, the need for a more robust, adaptive indoor navigation system has become more pressing than ever.
In a recent study (DOI: 10.1186/s43020-025-00158-9) published on March 3, 2025, in Satellite Navigation, researchers from Wuhan University and Shenzhen University unveiled their breakthrough: a tightly coupled VLP/INS integrated navigation system. This innovative system leverages graph optimization to estimate the receiver's inclination and detect signal blockages in real-time, while also estimating the positions of unknown LEDs, making it highly applicable for real-world scenarios where pre-mapping is not feasible.
The study's key innovation lies in the seamless integration of VLP and INS, combining their strengths to tackle the inherent limitations of each system. Through the use of graph optimization, the system efficiently handles varying inclinations of the PhotoDiode (PD) and detects light blockages during operation. A novel blockage detection technique ensures that only unimpeded RSS measurements are used, maintaining continuous navigation even in environments with frequent signal disruptions. Additionally, the system's ability to estimate the locations of unknown LEDs—such as in dynamically changing environments—further enhances its flexibility and accuracy. Experimental tests demonstrated the system's remarkable performance, with one group achieving an average positioning accuracy of 10 cm and a 100% blockage detection success rate. Another group achieved 11.5 cm accuracy, underscoring the system's real-world potential in demanding applications like mobile robotics and Unmanned Aerial Vehicles (UAVs).
"This tightly coupled VLP/INS system represents a significant leap forward in indoor navigation technology," said Dr. Yuan Zhuang, the corresponding author of the study. "By addressing the critical challenges of inclination changes and signal blockages, we've developed a solution that not only enhances accuracy but also ensures more reliable performance in dynamic, real-world environments."
The implications of this groundbreaking research are vast, particularly in fields that require high-precision indoor navigation. With its ability to adapt to dynamic inclinations and overcome signal blockages, the system is ideally suited for mobile robots, drones, and wearable devices. In industrial environments, it could significantly improve the efficiency of Automated Guided Vehicles (AGVs) and robotic arms, providing accurate and reliable positioning. Due to the miniaturization and low cost of PD and LED, it provides an alternative solution to Simultaneous Localization and Mapping (SLAM) in the field of robotics. As indoor localization demand continues to rise, this technology is poised to become a cornerstone of smart factories, smart homes, and other IoT-driven applications.
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References
DOI
10.1186/s43020-025-00158-9
Original Source URL
https://doi.org/10.1186/s43020-025-00158-9
Funding information
This work was supported in part by the National Key Research and Development Program of China (International Scientific and Technological Cooperation Program) under Grant 2022YFE0139300; in part by the National Natural Science Foundation of China under Grant 42374047; in part by the Guangdong Basic and Applied Basic Research Foundation under Grant 2022B1515120067; in part by the Key Research and Development Program of Hubei Province (International Scientific and Technological Cooperation Program) under Grant 2023EHA036; and in part by Wuhan AI Innovation Program under Grant 2023010402040011.
About Satellite Navigation
Satellite Navigation (E-ISSN: 2662-1363; ISSN: 2662-9291) is the official journal of Aerospace Information Research Institute, Chinese Academy of Sciences. The journal aims to report innovative ideas, new results or progress on the theoretical techniques and applications of satellite navigation. The journal welcomes original articles, reviews and commentaries.