An Open-Source Platform for Human Pose Estimation and Tracking Using a Heterogeneous Multi-Sensor System.

Human pose estimation and tracking in real-time from multi-sensor systems is essential for many applications. Combining multiple heterogeneous sensors increases opportunities to improve human motion tracking. Using only a single sensor type, e.

Fusion of Multiple Lidars and Inertial Sensors for the Real-Time Pose Tracking of Human Motion.

Today, enhancement in sensing technology enables the use of multiple sensors to track human motion/activity precisely. Tracking human motion has various applications, such as fitness training, healthcare, rehabilitation, human-computer interaction, virtual reality, and activity recognition. Therefore, the fusion of multiple sensors creates new opportunities to develop and improve an existing system.

On-Site 4-in-1 Alignment: Visualization and Interactive CAD Model Retrofitting Using UAV, LiDAR's Point Cloud Data, and Video.

Acquisition of 3D point cloud data (PCD) using a laser scanner and aligning it with a video frame is a new approach that is efficient for retrofitting comprehensive objects in heavy pipeline industrial facilities. This work contributes a generic framework for interactive retrofitting in a virtual environment and an unmanned aerial vehicle (UAV)-based sensory setup design to acquire PCD. The framework adopts a 4-in-1 alignment using a point cloud registration algorithm for a pre-processed PCD alignment with the partial PCD, and frame-by-frame registration method for video alignment.

A LiDAR and IMU Integrated Indoor Navigation System for UAVs and Its Application in Real-Time Pipeline Classification.

Mapping the environment of a vehicle and localizing a vehicle within that unknown environment are complex issues. Although many approaches based on various types of sensory inputs and computational concepts have been successfully utilized for ground robot localization, there is difficulty in localizing an unmanned aerial vehicle (UAV) due to variation in altitude and motion dynamics. This paper proposes a robust and efficient indoor mapping and localization solution for a UAV integrated with low-cost Light Detection and Ranging (LiDAR) and Inertial Measurement Unit (IMU) sensors.