Reinforcement Learning with Gaussian Processes for Unmanned Aerial Vehicle Navigation

Reinforcement Learning with Gaussian Processes for Unmanned Aerial Vehicle Navigation

We study the problem of Reinforcement Learning (RL) for Unmanned Aerial Vehicle (UAV) navigation with the smallest number of real world samples possible. This work is motivated by applications of learning autonomous navigation for aerial robots in structural inspec- tion. A naive RL implementation s...

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Bibliographic Details
Main Author: Gondhalekar, Nahush Ramesh
Other Authors: Electrical and Computer Engineering
Format: Others
Published: Virginia Tech 2017
Subjects:
Reinforcement Learning
Gaussian Processes
Unmanned Aerial Vehicle Navigation
Online Access:http://hdl.handle.net/10919/78667

Internet

http://hdl.handle.net/10919/78667

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