机器人2025，Vol.47Issue(3)：305-314,10.DOI:10.13973/j.cnki.robot.240329
基于深度强化学习的四旋翼无人机双向推力控制
Bidirectional Thrust Control of a Quadrotor with Deep Reinforcement Learning
摘要
Abstract
Current control technologies for quadrotors mainly adopt the approach of utilizing positive thrust from the motor,limiting the application potential of bidirectional motors.To improve the maneuverability of quadrotors,expand their action space,and achieve agile flight and rapid control,a bidirectional thrust control method for quadrotors based on deep reinforcement learning is proposed.This method combines deep reinforcement learning with bidirectional thrust control for quadrotors for the first time.Based on the dynamic model of quadrotors with bidirectional thrust,a neural network controller based on deep reinforcement learning is designed to control the expected low-level thrust of 4 motors,realizing rapid hovering under extreme conditions.In addition,simulations of quadrotor stable hovering control under extreme conditions,such as large attitudes,high speeds,and high angular speeds,are conducted.The experimental results show that,compared to existing controllers using positive thrust,the proposed bidirectional thrust controller performs smoother actions,with smaller state fluctuations,shorter control times,and stronger robustness,effectively improving the control performance of the quadrotor.关键词
四旋翼无人机/深度强化学习/神经网络控制器/双向推力/底层控制Key words
quadrotor/deep reinforcement learning/neural network controller/bidirectional thrust/low level control引用本文复制引用
李晓信,刘志宏,王冠政,王祥科..基于深度强化学习的四旋翼无人机双向推力控制[J].机器人,2025,47(3):305-314,10.基金项目
国家自然科学基金(U23B2032). （U23B2032）
