Related papers: Distributed Quantum Magnetic Sensing for Infrastru…
This article aims to investigate how circuit-based hybrid Quantum Convolutional Neural Networks (QCNNs) can be successfully employed as image classifiers in the context of remote sensing. The hybrid QCNNs enrich the classical architecture…
Navigating and localizing in partially observable, stochastic environments with magnetic anomalies presents significant challenges, especially when balancing the accuracy of state estimation and the stability of localization. Traditional…
In recent years, there has been a sharp increase in Global Navigation Satellite Systems (GNSS) interference, which has proven to be problematic in GNSS-dependent civilian applications. Many currently deployed GNSS receivers lack the proper…
Accurate localization is crucial for water robotics, yet traditional onboard Global Navigation Satellite System (GNSS) approaches are difficult or ineffective due to signal reflection on the water's surface and its high cost of aquatic GNSS…
Robots often use feature-based image tracking to identify their position in their surrounding environment; however, feature-based image tracking is prone to errors in low-textured and poorly lit environments. Specifically, we investigate a…
The accuracy of global navigation satellite system (GNSS) receivers is significantly compromised by interference from jamming devices. Consequently, the detection of these jammers are crucial to mitigating such interference signals.…
Remarkable advances have been achieved in localization techniques in past decades, rendering it one of the most important technologies indispensable to our daily lives. In this paper, we investigate a novel localization approach for future…
Distributed quantum sensing can provide quantum-enhanced sensitivity beyond the shot-noise limit (SNL) for sensing spatially distributed parameters. To date, distributed quantum sensing experiments have been mostly accomplished in…
This paper presents a trustworthy framework for achieving accurate cooperative localization in multiple unmanned aerial vehicle (UAV) systems. The The Cramer-Rao Lower Bound (CRLB) for the three-dimensional (3D) cooperative localization…
Robust navigation in urban environments has received a considerable amount of both academic and commercial interest over recent years. This is primarily due to large commercial organizations such as Google and Uber stepping into the…
The planet Earth has hundreds of impact events, with some occurrences causing both in terms of human casualty as well as economic losses. Such attitudes of earth pushed the frontiers to develop innovative monitoring strategies for the earth…
Recent advancements in UAV technology have spurred interest in developing multi-UAV aerial surveying systems for use in confined environments where GNSS signals are blocked or jammed. This paper focuses airborne magnetic surveying…
Quantum computing promises to revolutionize machine learning, offering significant efficiency gains in tasks such as clustering and distance estimation. Additionally, it provides enhanced security through fundamental principles like the…
Satellite-based quantum communication is an invaluable resource for the realization of a quantum network at the global scale. In this regard, the use of satellites well beyond the low Earth orbits gives the advantage of long communication…
A crucial function for automated vehicle technologies is accurate localization. Lane-level accuracy is not readily available from low-cost Global Navigation Satellite System (GNSS) receivers because of factors such as multipath error and…
Magnetic Induction (MI) is an efficient wireless communication method to deploy operational internet of underground things (IOUT) for oil and gas reservoirs. The IOUT consists of underground things which are capable of sensing the…
While both outdoor and indoor localization methods are flourishing, how to properly marry them to offer pervasive localizability in urban areas remains open. Recently proposals on indoor-outdoor detection make the first step towards such an…
Planet-scale photo geolocalization is the complex task of estimating the location depicted in an image solely based on its visual content. Due to the success of convolutional neural networks (CNNs), current approaches achieve super-human…
Accurately estimating the positions of multi-agent systems in indoor environments is challenging due to the lack of Global Navigation Satelite System (GNSS) signals. Noisy measurements of position and orientation can cause the integrated…
Geomagnetic surveys provide insight into the subsurface for a range of applications, from fundamental understanding of geological processes, to mineral exploration and locating unexploded ordnance. A persistent challenge in performing such…