Related papers: Precise Indoor Positioning Based on UWB and Deep L…
We present DeepPerimeter, a deep learning based pipeline for inferring a full indoor perimeter (i.e. exterior boundary map) from a sequence of posed RGB images. Our method relies on robust deep methods for depth estimation and wall…
Localization of robots is vital for navigation and path planning, such as in cases where a map of the environment is needed. Ultra-Wideband (UWB) for indoor location systems has been gaining popularity over the years with the introduction…
User equipment (UE) positioning accuracy is of paramount importance in current and future communications standard. However, traditional methods tend to perform poorly in non line of sight (NLoS) scenarios. As a result, deep learning is a…
While fingerprinting localization is favored for its effectiveness, it is hindered by high data acquisition costs and the inaccuracy of static database-based estimates. Addressing these issues, this letter presents an innovative indoor…
Localization plays a critical role in the field of distributed swarm robotics. Previous work has highlighted the potential of relative localization for position tracking in multi-robot systems. Ultra-wideband (UWB) technology provides a…
Accurate localization in indoor environments is a challenge due to the Non Line of Sight (NLoS) nature of the signaling. In this paper, we explore the use of AI/ML techniques for positioning accuracy enhancement in Indoor Factory (InF)…
Recognizing user location with WiFi fingerprints is a popular approach for accurate indoor positioning problems. In this work, our goal is to interpret WiFi fingerprints into actual user locations. However, WiFi fingerprint data can be very…
High-precision positioning is vital for cellular networks to support innovative applications such as extended reality, unmanned aerial vehicles (UAVs), and industrial Internet of Things (IoT) systems. Existing positioning algorithms using…
High accuracy localisation technologies exist but are prohibitively expensive to deploy for large indoor spaces such as warehouses, factories, and supermarkets to track assets and people. However, these technologies can be used to lend…
As commercial interest in proximity services increased, the development of various wireless localization techniques was promoted. In line with this trend, Ultra-wideband (UWB) is emerging as a promising solution that can realize proximity…
Recent advancements in Internet of Things (IoTs) have brought about a surge of interest in indoor positioning for the purpose of providing reliable, accurate, and energy-efficient indoor navigation/localization systems. Ultra Wide Band…
Indoor localization plays a vital role in the era of the IoT and robotics, with WiFi technology being a prominent choice due to its ubiquity. We present a method for creating WiFi fingerprinting datasets to enhance indoor localization…
Deep learning has been widely adopted for channel state information (CSI)-fingerprinting indoor localization systems. These systems usually consist of two main parts, i.e., a positioning network that learns the mapping from high-dimensional…
Precise indoor positioning systems (IPSs) are key to perform a set of tasks more efficiently during aircraft production, operation and maintenance. For instance, IPSs can overcome the tedious task of configuring (wireless) sensor nodes in…
This paper presents a novel indoor positioning method designed for residential apartments. The proposed method makes use of cellular signals emitting from a serving eNodeB which eliminates the need for specialized positioning…
There has been an increasing tendency to move from outdoor to indoor lifestyle in modern cities. The emergence of big shopping malls, indoor sports complexes, factories, and warehouses is accelerating this tendency. In such an environment,…
Precise indoor localization is an increasingly demanding requirement for various emerging applications, like Virtual/Augmented reality and personalized advertising. Current indoor environments are equipped with pluralities of WiFi access…
With robots increasingly integrating into human environments, understanding and predicting human motion is essential for safe and efficient interactions. Modern human motion and activity prediction approaches require high quality and…
Rodents have long been established as the premier model for behavioral studies, traditionally raised and maintained in conventional cage environments. However, these settings often limit rodents' ability to exhibit their full range of…
Indoor localization has been a hot area of research over the past two decades. Since its advent, it has been steadily utilizing the emerging technologies to improve accuracy, and machine learning has been at the heart of that. Machine…