Autonomous flying of drone based on ppo reinforcement learning algorithm

被引:5
|
作者
Park S.G. [1 ]
Kim D.H. [2 ]
机构
[1] Dept. of Mechanical Design and Robot Engineering, Seoul National University of Science and Technology
[2] Dept. of Mechanical System Design Engineering, Seoul National University of Science and Technology
来源
Kim, Dong Hwan (dhkim@seoultech.ac.kr) | 1600年 / Institute of Control, Robotics and Systems卷 / 26期
关键词
Autonomous drone; PPO(Proximal Policy Optimization); Reinforcement learning; Simulator;
D O I
10.5302/J.ICROS.2020.20.0125
中图分类号
学科分类号
摘要
In this study, the performance of autonomous flight was analyzed by introducing the PPO method as reinforcement learning for autonomous flight of drones. A simulator based on the dynamics of a drone was produced, and the performance of autonomous flight was confirmed when reinforcement learning was applied to a drone using this simulator. After that, the possibility of autonomous flight was confirmed by applying the PPO algorithm to the actual drone. Also, a lightweight embedded PC was attached to the drone to perform independent calculations to simultaneously construct obstacle avoidance and path planning. Copyright© ICROS 2020.
引用
收藏
页码:955 / 963
页数:8
相关论文
共 50 条
  • [41] Review of vision-based reinforcement learning for drone navigation
    Aburaya, Anas
    Selamat, Hazlina
    Muslim, Mohd Taufiq
    INTERNATIONAL JOURNAL OF INTELLIGENT ROBOTICS AND APPLICATIONS, 2024, 8 (04) : 974 - 992
  • [42] Vision Based Drone Obstacle Avoidance by Deep Reinforcement Learning
    Xue, Zhihan
    Gonsalves, Tad
    AI, 2021, 2 (03) : 366 - 380
  • [43] Reinforcement Learning Based Truck-and-Drone Coordinated Delivery
    Wu G.
    Fan M.
    Shi J.
    Feng Y.
    IEEE Transactions on Artificial Intelligence, 2023, 4 (04): : 754 - 763
  • [44] Autonomous Autorotation of an Unmanned Helicopter Using a Reinforcement Learning Algorithm
    Lee, Dong Jin
    Bang, Hyochoong
    JOURNAL OF AEROSPACE INFORMATION SYSTEMS, 2013, 10 (02): : 98 - 104
  • [45] Deep-Sarsa: A reinforcement learning algorithm for autonomous navigation
    Andrecut, M
    Ali, MK
    INTERNATIONAL JOURNAL OF MODERN PHYSICS C, 2001, 12 (10): : 1513 - 1523
  • [46] Deep Reinforcement Learning Based on Curriculum Learning for Drone Swarm Area Defense
    Sun, Miaoping
    Yang, Zequan
    Dai, Xunhua
    Nian, Xiaohong
    Wang, Haibo
    Xiong, Hongyun
    PROCEEDINGS OF 2022 INTERNATIONAL CONFERENCE ON AUTONOMOUS UNMANNED SYSTEMS, ICAUS 2022, 2023, 1010 : 1119 - 1128
  • [47] Drone Altitude Control with Reinforcement Learning
    Fu, Xilin
    Tay, Eng Hock Francis
    Hu, Junru
    Zhang, Yingnan
    Ding, Yi
    PROCEEDINGS OF 2022 INTERNATIONAL CONFERENCE ON AUTONOMOUS UNMANNED SYSTEMS, ICAUS 2022, 2023, 1010 : 590 - 594
  • [48] Drone Deep Reinforcement Learning: A Review
    Azar, Ahmad Taher
    Koubaa, Anis
    Ali Mohamed, Nada
    Ibrahim, Habiba A.
    Ibrahim, Zahra Fathy
    Kazim, Muhammad
    Ammar, Adel
    Benjdira, Bilel
    Khamis, Alaa M.
    Hameed, Ibrahim A.
    Casalino, Gabriella
    ELECTRONICS, 2021, 10 (09)
  • [49] Deep Reinforcement Learning for Drone Delivery
    Munoz, Guillem
    Barrado, Cristina
    Cetin, Ender
    Salami, Esther
    DRONES, 2019, 3 (03) : 1 - 19
  • [50] Learning fast in autonomous drone racing
    De Wagter, C.
    Paredes-Valles, F.
    Sheth, N.
    de Croon, G.
    NATURE MACHINE INTELLIGENCE, 2021, 3 (10) : 923 - 923