A Novel Augmentative Backward Reward Function with Deep Reinforcement Learning for Autonomous UAV Navigation
The autonomous UAV (unmanned aerial vehicle) navigation has recently gained an increasing interest from both academic and industrial sectors due to its potential uses in various fields and especially, the need for social distancing during the pandemic. Many works have adopted a deep reinforcement le...
Main Authors: | Chansuparp, M. (Author), Jitkajornwanich, K. (Author) |
---|---|
Format: | Article |
Language: | English |
Published: |
Taylor and Francis Ltd.
2022
|
Subjects: | |
Online Access: | View Fulltext in Publisher |
Similar Items
-
Reinforcement Learning with Gaussian Processes for Unmanned Aerial Vehicle Navigation
by: Gondhalekar, Nahush Ramesh
Published: (2017) -
IADRL: Imitation Augmented Deep Reinforcement Learning Enabled UGV-UAV Coalition for Tasking in Complex Environments
by: Jian Zhang, et al.
Published: (2020-01-01) -
Deep Reinforcement Learning for End-to-End Local Motion Planning of Autonomous Aerial Robots in Unknown Outdoor Environments: Real-Time Flight Experiments
by: Oualid Doukhi, et al.
Published: (2021-04-01) -
A Reinforcement Learning Approach for Fair User Coverage Using UAV Mounted Base Stations Under Energy Constraints
by: Hasini Viranga Abeywickrama, et al.
Published: (2020-01-01) -
Machine Learning for Intelligent Control: Application of Reinforcement Learning Techniques to the Development of Flight Control Systems for Miniature UAV Rotorcraft
by: Hayes, Edwin Laurie
Published: (2013)