Learn to navigate through deep neural networks
Autonomous navigation is a crucial prerequisite for mobile robots to perform various tasks while it remains a great challenge due to its inherent complexity. This thesis deals with the autonomous navigation problem using deep neural networks. It presents four main parts, i.e., an imitation learning...
Main Author: | Wu, Keyu |
---|---|
Other Authors: | Wang Han |
Format: | Thesis-Doctor of Philosophy |
Language: | English |
Published: |
Nanyang Technological University
2020
|
Subjects: | |
Online Access: | https://hdl.handle.net/10356/139680 |
Similar Items
-
iTD3-CLN: learn to navigate in dynamic scene through Deep Reinforcement Learning
by: Jiang, Haoge, et al.
Published: (2022) -
Learn to steer through deep reinforcement learning
by: Wu, Keyu, et al.
Published: (2019) -
BND*-DDQN: learn to steer autonomously through deep reinforcement learning
by: Wu, Keyu, et al.
Published: (2022) -
Depth-based obstacle avoidance through deep reinforcement learning
by: Wu, Keyu, et al.
Published: (2020) -
Deep learning neural network for image processing
by: Ma, Xueqing
Published: (2020)