利用无线电指纹同时定位和绘图

IF 1.6 4区 计算机科学 Q3 COMPUTER SCIENCE, INFORMATION SYSTEMS
Ran Liu, Billy Pik Lik Lau, Khairuldanial Ismail, Achala Chathuranga, Chau Yuen, Simon X. Yang, Yong Liang Guan, S. Mao, U-Xuan Tan
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引用次数: 0

摘要

同时定位和映射(SLAM)对于无人系统实现自我定位和导航至关重要。由于传感器的限制、环境的复杂性和计算资源,在大型环境中执行SLAM具有挑战性。我们提出了一种使用无线电指纹定位和映射自动驾驶汽车的新方法,例如无线保真度或长期进化无线电特征,这些特征在现有基础设施中广泛可用。特别地,我们提出了两种利用无线电指纹进行SLAM的解决方案。在第一个解决方案中,即Radio SLAM,输出是使用SLAM技术生成的无线电指纹图。在第二个解决方案中,即Radio+LiDAR SLAM,我们使用无线电指纹来辅助传统的基于LiDAR的SLAM,以提高准确性和速度,同时生成占用图。我们展示了我们的系统在三种不同环境中的有效性,即室外、室内建筑和半室内环境。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Exploiting Radio Fingerprints for Simultaneous Localization and Mapping
Simultaneous localization and mapping (SLAM) is paramount for unmanned systems to achieve self-localization and navigation. It is challenging to perform SLAM in large environments, due to sensor limitations, complexity of the environment, and computational resources. We propose a novel approach for localization and mapping of autonomous vehicles using radio fingerprints,for example wireless fidelity or long term evolution radio features, which are widely available in the existing infrastructure. In particular, we present two solutions to exploit the radio fingerprints for SLAM. In the first solution—namely Radio SLAM, the output is a radio fingerprint map generated using SLAM technique. In the second solution—namely Radio+LiDAR SLAM, we use radio fingerprint to assist conventional LiDAR-based SLAM to improve accuracy and speed, while generating the occupancy map. We demonstrate the effectiveness of our system in three different environments, namely outdoor, indoor building, and semi-indoor environment.
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来源期刊
IEEE Pervasive Computing
IEEE Pervasive Computing 工程技术-电信学
CiteScore
4.10
自引率
0.00%
发文量
47
审稿时长
>12 weeks
期刊介绍: IEEE Pervasive Computing explores the role of computing in the physical world–as characterized by visions such as the Internet of Things and Ubiquitous Computing. Designed for researchers, practitioners, and educators, this publication acts as a catalyst for realizing the ideas described by Mark Weiser in 1988. The essence of this vision is the creation of environments saturated with sensing, computing, and wireless communication that gracefully support the needs of individuals and society. Many key building blocks for this vision are now viable commercial technologies: wearable and handheld computers, wireless networking, location sensing, Internet of Things platforms, and so on. However, the vision continues to present deep challenges for experts in areas such as hardware design, sensor networks, mobile systems, human-computer interaction, industrial design, machine learning, data science, and societal issues including privacy and ethics. Through special issues, the magazine explores applications in areas such as assisted living, automotive systems, cognitive assistance, hardware innovations, ICT4D, manufacturing, retail, smart cities, and sustainability. In addition, the magazine accepts peer-reviewed papers of wide interest under a general call, and also features regular columns on hot topics and interviews with luminaries in the field.
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