3D LiDAR-based place recognition has been extensively researched in urban environments, yet it remains underexplored in agricultural settings. Unlike urban contexts, horticultural environments, ...

LiDAR odometry is the task of estimating the ego-motion of the sensor from sequential laser scans. This problem has been addressed by the community for more than two decades, and many effective ...

Robotics has evolved significantly from its industrial origins to encompass advanced autonomous mobile systems capable of operating in complex and unstructured environments. A key catalyst for this ...

This article presents an effective and reliable pose tracking solution, termed ERPoT, for mobile robots operating in large-scale outdoor and challenging indoor environments, underpinned by an ...

Explore the evolution of image annotation—from manual labeling to AI automation—powering innovations in healthcare, retail, ...

Occupancy prediction reconstructs 3D structures of surrounding environments. It provides detailed information for autonomous driving planning and navigation. However, most existing methods heavily ...

Obstacle detection plays a crucial role in unmanned vehicle path planning, demanding heavy computational resources for accurate detection, often challenging real-time requirements. In this study, we ...

Light Detection and Ranging (LiDAR) sensors play a critical role in enabling precise and reliable environmental perception for autonomous vehicles. However, handling the large amounts of data they ...

Bowman Consulting Group and Merrick & Company will conduct aerial lidar data collection for the USGS’s 3D Elevation Program.

Implementing LiDAR-based 3D object detection algorithms in practical autonomous driving situations presents a significant challenge. In current research algorithms, the inherent sparsity and ...