Real-Time Implementation of Quadrotor UAV Control System Based on a Deep Reinforcement Learning Approach
Source abstract
Abstract
The popularity of quadrotor Unmanned Aerial Vehicles (UAVs) stems from their simple propulsion systems and structural design. However, their complex and nonlinear dynamic behavior presents a significant challenge for control,... | Find, read and cite all the research you need on Tech Science Press
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Advanced Sensor and Control Systems · Elevator Systems and Control · Advanced Algorithms and Applications
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
References (58)
Show source-provided references
1. A multi-lingual speech recognition-based framework to human-drone interaction10.3390/electronics11121829 ↗
2. Using chaotic maps for 3D boundary surveillance by quadrotor robot10.1016/j.asoc.2018.11.051 ↗
3. The design and experimental development of air scanning using a sniffer quadcopter10.3390/s19183849 ↗
4. Visual victim detection and quadrotor-swarm coordination control in search and rescue environment
5. Analysis of multiple antenna techniques for unmanned aerial vehicle (UAV) communication
6. Path planning and formation control for UAV-enabled mobile edge computing network10.3390/s22197243 ↗
7. Distributed dynamic event-triggered consensus control for multiagent systems with guaranteed l_2 performance and positive inter-event times10.1109/TASE.2022.3231845 ↗
8. Distributed obstacles avoidance for UAVs formation using consensus-based switching topology10.12785/ijcds/080208 ↗
9. Cooperative fault-tolerant output regulation of linear heterogeneous multiagent systems via an adaptive dynamic event-triggered mechanism10.1109/TCYB.2022.3204119 ↗
10. Quadrotor stabilization under time and space constraints using implicit PID controller10.1016/j.jfranklin.2022.01.002 ↗
11. Thusoo · 2023 · 227
12. Design and experimental comparison of PID, LQR and MPC stabilizing controllers for parrot mambo mini-drone10.3390/aerospace9060298 ↗
13. Sliding-mode control for flight stability of quadrotor drone using adaptive super-twisting reaching law10.3390/drones7080522 ↗
14. Fractional order sliding mode control of quadrotor based on fractional order model10.1109/ACCESS.2023.3296644 ↗
15. Modeling and backstepping-based nonlinear control strategy for a 6 DOF quadrotor helicopter10.1016/S1000-9361(08)60034-5 ↗
16. Adaptive finite-time backstepping control tracker for quadrotor UAV with model uncertainty and external disturbance10.1016/j.ast.2022.108088 ↗
17. Attitude control of a quadcopter using adaptive control technique
18. Robust adaptive quadrotor position tracking control for uncertain and fault conditions10.1177/09544100231181869 ↗
19. A robust h control for unmanned aerial vehicle against atmospheric turbulence
20. Alsaade · Adv. Space Res. · 2023 · 71 · 363110.1016/j.asr.2022.02.012 ↗
21. A comparative study for control of quadrotor UAVs10.3390/app13063464 ↗
22. Fopid control of quadrotor based on neural networks optimization and path planning through machine learning and PSO algorithm10.1007/s42405-022-00461-8 ↗
23. EKF-SLAM for quadcopter using differential flatness-based LQR control10.3390/electronics12051113 ↗
24. Data-enabled predictive control for quadcopters10.1002/rnc.5686 ↗
25. Data driven model-free adaptive control method for quadrotor formation trajectory tracking based on rise and ismc algorithm10.3390/s21041289 ↗
26. SE(3) koopman-MPC: Data-driven learning and control of quadrotor uavs10.1016/j.ifacol.2023.12.091 ↗
27. An experimental validation of reinforcement learning applied to the position control of UAVs
28. Robust quadrotor control through reinforcement learning with disturbance compensation10.3390/app11073257 ↗
29. Deep reinforcement learning for quadrotor path following with adaptive velocity10.1007/s10514-020-09951-8 ↗
30. Deterministic policy gradient with integral compensator for robust quadrotor control10.1109/TSMC.2018.2884725 ↗
31. Quadrotor path following and reactive obstacle avoidance with deep reinforcement learning
32. Reinforcement learning based linear quadratic regulator for the control of a quadcopter
33. R. Polvara et al., “Autonomous quadrotor landing using deep reinforcement learning,” 2017, arXiv:1709.03339. doi: 10.48550/arXiv.1709.03339.
34. Evaluation of reinforcement and deep learning algorithms in controlling unmanned aerial vehicles10.3390/app11167240 ↗
35. Low-level autonomous control and tracking of quadrotor using reinforcement learning10.1016/j.conengprac.2019.104222 ↗
36. Controlling tiltrotors unmanned aerial vehicles (UAVs) with deep reinforcement learning
37. Hybrid reinforcement learning control for a micro quadrotor flight10.1109/LCSYS.2020.3001663 ↗
38. Neural network based model predictive control for a quadrotor UAV10.3390/aerospace9080460 ↗
39. Low-level control of a quadrotor with deep model-based reinforcement learning10.1109/LRA.2019.2930489 ↗
40. Controller design for quadrotor UAVs using reinforcement learning
41. Control of a quadrotor with reinforcement learning10.1109/LRA.2017.2720851 ↗
42. Quadrotor motion control using deep reinforcement learning10.1139/juvs-2021-0010 ↗
43. Constrained reinforcement learning using distributional representation for trustworthy quadrotor UAV tracking control
44. UAV control method combining reptile meta-reinforcement learning and generative adversarial imitation learning10.3390/fi16030105 ↗
45. Performance-designated reinforcement learning enclosing control for UAVs with collision-free capability10.1109/TITS.2024.3384431 ↗
46. Improved DRL-based energy-efficient UAV control for maximum lifecycle10.1016/j.jfranklin.2024.106718 ↗
47. Deep-reinforcement-learning-based UAV autonomous navigation and collision avoidance in unknown environments10.1016/j.cja.2023.09.033 ↗
48. STIF: A spatial-temporal integrated framework for end-to-end micro-UAV trajectory tracking and prediction with 4-D MIMO radar10.1109/JIOT.2023.3244655 ↗
49. Multi-objective simulated annealing for hyperparameter optimization in convolutional neural networks10.7717/peerj-cs.338 ↗
50. Simplified swarm optimization for hyperparameters of convolutional neural networks10.1016/j.cie.2023.109076 ↗
51. An enhanced proximal policy optimization-based reinforcement learning method with random forest for hyperparameter optimization
52. M. Kiran and M. Ozyildirim, “Hyperparameter tuning for deep reinforcement learning applications,” 2022, arXiv:2201.11182.
53. Pathik · Soft Computing: Theories and Applications · 2020 · 515
54. Reinforcement learning based relay selection for underwater acoustic cooperative networks
55. Towards optimization of energy consumption of tello quad-rotor with MPC model implementation10.3390/en15239207 ↗
56. T. P. Lillicrap et al., “Continuous control with deep reinforcement learning,” 2015, arXiv:1509.02971.
57. Addressing function approximation error in actor-critic methods
58. Delahaye · Handbook of Metaheuristics · 2019 · 1