6 papers
NavRL++: A System-Level Framework for Improving Sim-to-Real Transfer in Reinforcement Learning-Based Robot Navigation
Zhefan Xu, Hanyu Jin, Kenji Shimada
Recent years have witnessed significant progress in autonomous navigation using reinforcement learning. However, existing approaches largely emphasize reinforcement learning framew…
ASIP-Planner: Adaptive Planning for UAV Surface Inspection in Partially Known Indoor Environments
Hanyu Jin, Zhefan Xu, Haoyu Shen +3
Indoor infrastructure inspection, such as tunnels and industrial facilities, requires systematic surface coverage to ensure that all inspection targets are properly observed. Unman…
Adaptive Planning Framework for UAV-Based Surface Inspection in Partially Unknown Indoor Environments
Hanyu Jin, Zhefan Xu, Haoyu Shen +3
Inspecting indoor environments such as tunnels, industrial facilities, and construction sites is essential for infrastructure monitoring and maintenance. While manual inspection in…
Intent Prediction-Driven Model Predictive Control for UAV Planning and Navigation in Dynamic Environments
Zhefan Xu, Hanyu Jin, Xinming Han +2
Aerial robots can enhance construction site productivity by autonomously handling inspection and mapping tasks. However, ensuring safe navigation near human workers remains challen…
LV-DOT: LiDAR-visual dynamic obstacle detection and tracking for autonomous robot navigation
Zhefan Xu, Haoyu Shen, Xinming Han +3
Accurate perception of dynamic obstacles is essential for autonomous robot navigation in indoor environments. Although sophisticated 3D object detection and tracking methods have b…
NavRL: Learning Safe Flight in Dynamic Environments
Zhefan Xu, Xinming Han, Haoyu Shen +2
Safe flight in dynamic environments requires unmanned aerial vehicles (UAVs) to make effective decisions when navigating cluttered spaces with moving obstacles. Traditional approac…