Qihan Qi

Constructing and Navigating Connected Air Roads: A Safety-Critical Reinforcement Learning Approach for Multi-UAV Systems

This paper presents an integrated control method in air road navigation for multi-UAV systems, combining an efficient reinforcement learning (RL) controller with a control barrier function (CBF)-based filter that guarantees flight safety. First, an air road construction method based on arbitrary qua…

Distributed Collision-Free Control of MASs by Combining Reinforcement Learning with Filtered Position Barrier Certificates and Applications (I)

A Safety-Adjusted Policy Optimization Algorithm and Application for Obstacle Avoidance in the Quadcopter

Ensuring the safety of various real-world applications based on reinforcement learning (RL), such as quadcopter control, robotic manipulators, and autonomous robots, remains a critical challenge, despite RL’s remarkable success in solving complex decision-making tasks. Existing on-policy Lagrangian

Multi-UAV-UGV Collision-Free Tracking Control via Control Barrier Function-Based Reinforcement Learning

This paper introduces a novel hierarchical control approach for feature matching, real-time tracking and inter-UAV collision avoidance in multiple unmanned aerial vehicle-unmanned ground vehicle (multi-UAV-UGV) collaborative tracking. Our approach divides into three layers: optimal feature matching,