Continuous-time trajectory representation has gained significant popularity in recent years,
as it offers an elegant formulation that allows the fusion of a larger number of sensors and …

Accurate, efficient, and robust state estimation is more important than ever in robotics as the
variety of platforms and complexity of tasks continue to grow. Historically, discrete-time filters …

LiDAR-based SLAM is a core technology for autonomous vehicles and robots. Despite the
intense research activity in this field, each proposed system uses a particular sensor post …

Helmet-mounted wearable positioning systems are crucial for enhancing safety and
facilitating coordination in industrial, construction, and emergency rescue environments …

Multi-axle autonomous mobile robots (AMRs) are set to revolutionize the future of robotics in
logistics. As the backbone of next-generation solutions, these robots face a critical …

SLAM plays a crucial role in automation tasks, such as warehouse logistics, healthcare
robotics, and restaurant delivery. These scenes come with various challenges, including …

Autonomous navigation in challenging environments, especially in global navigation
satellite system (GNSS)-denied stacked cage farming houses (SCFHs), presents …

To address the challenges posed by the dynamic environment for Simultaneous
Localization and Mapping (SLAM), a detection-first tightly-coupled LiDAR-Visual-Inertial …

We propose the D epth-V isual-I nertial (DVI) mapping system: a robust multi-sensor fusion
framework for dense 3D mapping using time-of-flight cameras equipped with RGB and IMU …

Ultra-wideband (UWB) is gaining popularity with devices like AirTags for precise home item
localization but faces significant challenges when scaled to large environments like …