Author

Garratt, Matthew Adam

Date
Description
This thesis makes a number of new contributions to control and sensing for unmanned vehicles. I begin by developing a non-linear simulation of a small unmanned helicopter and then proceed to develop new algorithms for control and sensing using the simulation. The work is field-tested in successful flight trials of biologically inspired vision and neural network control for an unstable rotorcraft. The techniques are more robust and more easily implemented on a small flying vehicle than previously attempted methods. ¶ ...
GUID
oai:openresearch-repository.anu.edu.au:1885/49285
Identifier
oai:openresearch-repository.anu.edu.au:1885/49285
Identifiers
b23509600
http://hdl.handle.net/1885/49285
10.25911/5d7a2c48c1521
https://openresearch-repository.anu.edu.au/bitstream/1885/49285/6/01front.pdf.jpg
https://openresearch-repository.anu.edu.au/bitstream/1885/49285/7/02whole.pdf.jpg
Publication Date
Titles
Biologically Inspired Vision and Control for an Autonomous Flying Vehicle