8 accepted papers
Implicit representations for LiDAR-based Simultaneous Localization and Mapping (SLAM) offer significant advantages in storage efficiency and expressive power over traditional explicit maps. However, a critical limitation for implicit SLAM is their deterministic nature, which prevents the quantificat…
In this letter, we propose a tiered systematic framework to enhance the overall efficiency and environmental coverage of autonomous exploration for Autonomous Ground Vehicle (AGV) in complex environments with narrow regions. At the local level, we introduce a novel Multi-cause Triggering Sensor Mode…
Autonomous driving is a high-performance, safety-critical task. Effectively controlling autonomous vehicles to enhance both performance and safety is crucial, especially in complex and dynamic environments. However, in real-time obstacle avoidance (OA) scenarios, the planning layer often fails due t
This paper presents a universal LiDAR point cloud global localization framework based on multi-sector overlapping loss to address the localization challenges caused by heterogeneous LiDAR point clouds with varying resolutions, scanning formats, and field of view differences. The proposed method firs
One-shot global localization is crucial in many robotic applications, providing significant advantages during initialization and relocalization processes. However, LiDAR-based one-shot global localization methods encounter challenges, including local feature matching errors, sensitivity to dynamic o
Path tracking control is a crucial technology for intelligent vehicles (IVs) to achieve accurate tracking. However, a single controller struggles to track precisely in complex environments due to respective advantages and applicable scenarios. To improve tracking performance for IVs, this letter pro
This paper presents a novel one-shot global localization algorithm based on semantic-guided triangle descriptors to address initialization and global localization challenges in GNSSdenied environments. By encoding semantic geometric information into triangle descriptors, the proposed approach achiev
In this letter, we propose a tiered systematic framework to enhance the overall efficiency and environmental coverage of autonomous exploration for Unmanned Ground Vehicle (UGV) in complex environments with narrow regions. At the local level, we introduce a novel Multi-cause Triggering Sensor Model