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Dive into the research topics where Gregg Buskey is active.

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Featured researches published by Gregg Buskey.


intelligent robots and systems | 2003

A tale of two helicopters

Srikanth Saripalli; Jonathan M. Roberts; Peter Corke; Gregg Buskey; Gaurav S. Sukhatme

This paper discusses similarities and differences in autonomous helicopters developed at USC and CSIRO. The most significant differences are in the accuracy and sample rate of the sensor systems used for control. The USC vehicle, like a number of others, makes use of a sensor suite that costs an order of magnitude more than the vehicle. The CSIRO system, by contrast, utilizes low-cost inertial, magnetic, vision and GPS to achieve the same ends. We describe the architecture of both autonomous helicopters, discuss the design issues and present comparative results.


international conference on robotics and automation | 2004

Low-cost vision-based AUV guidance system for reef navigation

Matthew Dunbabin; Peter Corke; Gregg Buskey

Ensuring the long term viability of reef environments requires essential monitoring of many aspects of these ecosystems. However, the sheer size of these unstructured environments (for example Australias Great Barrier Reef) pose a number of challenges for current monitoring platforms which are typically remote operated and required significant resources and infrastructure. Therefore, a primary objective of the CSIRO robotic reef monitoring project is to develop and deploy a large number of AUV teams to perform broadscale reef surveying. In order to achieve this, the platforms must be cheap, even possibly disposable. This work presents the results of a preliminary investigation into the performance of a low-cost sensor suite and associated processing techniques for vision and inertial-based navigation within a highly unstructured reef environment.


Institute for Future Environments; Science & Engineering Faculty | 2003

Experiments in learning helicopter control from a pilot

Gregg Buskey; Jonathan M. Roberts; Gordon Wyeth

This paper details the development of a machine learning system which uses the helicopter state and the actions of an instructing pilot to synthesise helicopter control modules online. Aggressive destabilisation/restabilisation sequences are used for training, such that a wide state space envelope is covered during training. The performance of heading, roll, pitch, height and lateral velocity control learning is presented using our Xcell 60 experimental platform. The helicopter is demonstrated to be stabilised on all axes using the “learning from a pilot” technique. To our knowledge, this is the first time a “learning from a pilot” technique has been successfully applied to all axes.


Faculty of Built Environment and Engineering | 2004

Low-Cost vision-based AUV guidance system for reef navigation

Matthew Dunbabin; Peter Corke; Gregg Buskey


Computing & Control Engineering Journal | 2004

Helicopter automation a using a low-cost sensing system

Gregg Buskey; J. Roberts; P. I. Corke; G. F. Wyeth


Science & Engineering Faculty | 2001

Autonomous helicopter hover using an artificial neural network

Gregg Buskey; Gordon Wyeth; Jonathan M. Roberts


ACRA 2000 | 2000

Flight control using an artificial neural network

Gordon Wyeth; Gregg Buskey; Jonathan M. Roberts


international conference on robotics and automation | 2002

Online learning of autonomous helicopter control

Gregg Buskey; Jonathan M. Roberts; Gordon Wyeth


international conference on robotics and automation | 2003

A helicopter named Dolly: Behavioural cloning for autonomous helicopter control

Gregg Buskey; Jonathan M. Roberts; Gordon Wyeth


international conference on robotics and automation | 2003

Helicopter automation using a low-cost sensing system

Gregg Buskey; Jonathan M. Roberts; Peter Corke; Gordon Wyeth

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Jonathan M. Roberts

Queensland University of Technology

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Gordon Wyeth

Queensland University of Technology

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Peter Corke

Queensland University of Technology

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Matthew Dunbabin

Queensland University of Technology

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Gaurav S. Sukhatme

University of Southern California

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Peter Ridley

Queensland University of Technology

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