Cooperative UAV transport operations in GPS-denied environments pose significant challenges in localization, coordination, and payload stability. This paper introduces a vision-based Leader-Follower drone system using MAVROS and depth cameras for real-...

This paper presents a system that fuses radio tomography data with RGB camera information for enhanced multi-person detection and tracking in indoor environments. Experiments were conducted in an irregularly shaped room with four subjects. Due to its ...

Fusing the data of millimeter-wave Radar sensors and high-definition cameras has emerged as a viable approach to achieving precise 3D object detection for roadside traffic surveillance. For roadside perception systems, earlier studies have pointed out ...

Earphones, due to their deep integration into daily life, have been developed for unobtrusive and ubiquitous health monitoring. However, these advanced algorithms greatly rely on the high quality sensing data. However, the data collected with universal ...

M-MOVE-IT is an open-source framework that simplifies data acquisition, annotation, and AI training for wearable technology. It addresses the challenges of synchronizing video and IMU data, making it easier to develop AI models for healthcare, sports, ...

Masked Autoencoders (MAE) play a pivotal role in learning potent representations, delivering outstanding results across various 3D perception tasks essential for autonomous driving. In real-world driving scenarios, it’s commonplace to deploy ...${}^{\mathrm{}}$${}^{\mathrm{}}$

We propose AstroSLAM, a standalone vision-based solution for autonomous online navigation around an unknown celestial target small body. AstroSLAM is predicated on the formulation of the SLAM problem as an incrementally growing factor graph, facilitated ...

This paper addresses the lower limits of encoding and processing the information acquired through interactions between an internal system (robot algorithms or software) and an external system (robot body and its environment) in terms of action and ...

Underwater perception and 3D surface reconstruction are challenging problems with broad applications in construction, security, marine archaeology, and environmental monitoring. Treacherous operating conditions, fragile surroundings, and limited ...

For real-world applications, autonomous mobile robotic platforms must be capable of navigating safely in a multitude of different and dynamic environments with accurate and robust localization being a key prerequisite. To support further research in this ...

The colour‐enhanced point cloud map is increasingly being employed in fields such as robotics, 3D reconstruction and virtual reality. The authors propose ER‐Mapping (Extrinsic Robust coloured Mapping system using residual evaluation and ...

As a safety-critical application, Autonomous Driving (AD) has received growing attention from security researchers. AD heavily relies on sensors for perception. However, sensors themselves are susceptible to various threats since they are exposed to the ...

Modern cyber-physical systems integrate data from many sensors as a regular part of their operations. Over the years, researchers have proposed methods ranging from statistical approaches to neural networks to achieve this sensor fusion, along with high-...

The multifaceted nature of sensor data has long been a hurdle for those seeking to harness its full potential in the field of 3D object detection. Although the utilisation of point clouds as input has yielded exceptional results, the challenge ...

A voxel‐based single‐shot multi‐model network for 3D object detection is introduced, namely AVIFF. The authors made some new attempts in fusing features of point cloud and image by designing the adaptive feature fusion (AFF) module and dense fusion (DF) ...

Existing wireless-inertial fusion positioning mechanisms predominantly rely on empirical propagation models of wireless signals and are often fused by filtering algorithms such as the Kalman filter or particle filter. Despite their wide usage, ...

In most manufacturing processes, data related to a product are collected across several process steps. Ensuring good data quality is essential for subsequent process modeling, monitoring, and control. Although data for a given process might already be ...

People usually form a social structure (e.g., a leader-follower, companion, or independent group) for better interactions among them and thus share similar perceptions of visible scenes and invisible wireless signals encountered while moving. Many ...

In recent years, the deployment of unmanned vehicle delivery services has increased unprecedentedly, leading to a need for enhanced security due to the risk of leaving high-value packages to an unauthorized third party during pickup or delivery. ...

This study proposes an approach for emotion recognition in children with hearing impairments by utilizing physiological and facial cues and fusing them using machine learning techniques. The study is a part of a child-robot interaction project to ...

Mobile sensors have improved traffic prediction through transportation mode recognition. Researchers are interested in exploring mobile sensor-based recognition methods for transportation modes. The SHL Recognition Challenge is a prominent competition ...