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Dive into the research topics where Troy S. Bruggemann is active.

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Featured researches published by Troy S. Bruggemann.


Journal of Intelligent and Robotic Systems | 2013

A 3D Collision Avoidance Strategy for UAVs in a Non-Cooperative Environment

Xilin Yang; Luis Mejias Alvarez; Troy S. Bruggemann

This paper presents a feasible 3D collision avoidance approach for fixed-wing unmanned aerial vehicles (UAVs). The proposed strategy aims to achieve the desired relative bearing in the horizontal plane and relative elevation in the vertical plane so that the host aircraft is able to avoid collision with the intruder aircraft in 3D. The host aircraft will follow a desired trajectory in the collision avoidance course and resume the pre-arranged trajectory after collision is avoided. The approaching stopping condition is determined for the host aircraft to trigger an evasion maneuver to avoid collision in terms of measured heading. A switching controller is designed to achieve the spatial collision avoidance strategy. Simulation results demonstrate that the proposed approach can effectively avoid spatial collision, making it suitable for integration into flight control systems of UAVs.


Journal of Field Robotics | 2012

Toward automated power line corridor monitoring using advanced aircraft control and multisource feature fusion

Zhengrong Li; Troy S. Bruggemann; Jason J. Ford; Luis Mejias; Yuee Liu

The conventional manual power line corridor inspection processes that are used by most energy utilities are labor-intensive, time consuming and expensive. Remote sensing technologies represent an attractive and cost-effective alternative approach to these monitoring activities. This paper presents a comprehensive investigation into automated remote sensing based power line corridor monitoring, focusing on recent innovations in the area of increased automation of fixed-wing platforms for aerial data collection, and automated data processing for object recognition using a feature fusion process. Airborne automation is achieved by using a novel approach that provides improved lateral control for tracking corridors and automatic real-time dynamic turning for flying between corridor segments, we call this approach PTAGS. Improved object recognition is achieved by fusing information from multi-sensor (LiDAR and imagery) data and multiple visual feature descriptors (color and texture). The results from our experiments and field survey illustrate the effectiveness of the proposed aircraft control and feature fusion approaches.


IEEE Transactions on Control Systems and Technology | 2011

Control of Aircraft for Inspection of Linear Infrastructure

Troy S. Bruggemann; Jason J. Ford; Rodney A. Walker

Inspection aircraft equipped with cameras and other sensors are routinely used for asset location, inspection, monitoring, and hazard identification of oil-gas pipelines, roads, bridges, and power transmission grids. This paper is concerned with automated flight of fixed-wing inspection aircraft to track approximately linear infrastructure. We propose a guidance law approach that seeks to maintain aircraft trajectories with desirable position and orientation properties relative to the infrastructure under inspection. Furthermore, this paper also proposes the use of an adaptive maneuver selection approach, in which maneuver primitives are adaptively selected to improve the aircrafts attitude behavior. We employ an integrated design methodology particularly suited for an automated inspection aircraft. Simulation studies using full nonlinear semicoupled six degree-of-freedom equations of motion are used to illustrate the effectiveness of the proposed guidance and adaptive maneuver selection approaches in realistic flight conditions. Experimental flight test results are given to demonstrate the performance of the design.


australian control conference | 2013

Automated aerial inspection guidance with improved turn planning

Troy S. Bruggemann; Jason J. Ford

Aerial inspection of pipelines, powerlines, and other large linear infrastructure networks has emerged in a number of civilian remote sensing applications. Challenges relate to automating inspection flight for under-actuated aircraft with LiDAR/camera sensor constraints whilst subjected to wind disturbances. This paper presents new improved turn planning strategies with guidance suitable for automation of linear infrastructure inspection able to reduce inspection flight distance by including wind information. Simulation and experimental flight tests confirmed the flight distance saving, and the proposed guidance strategies exhibited good tracking performance in a range of wind conditions.


IEEE Transactions on Aerospace and Electronic Systems | 2011

GPS Fault Detection with IMU and Aircraft Dynamics

Troy S. Bruggemann; Duncan G. Greer; Rodney A. Walker


Australian Research Centre for Aerospace Automation; Science & Engineering Faculty | 2012

A spatial collision avoidance strategy for UAVs in a non-cooperative environment

Xilin Yang; Luis Mejias; Troy S. Bruggemann


Faculty of Built Environment and Engineering | 2009

Investigation of MEMS inertial sensors and aircraft dynamic models in global positioning system integrity monitoring for approaches with vertical guidance

Troy S. Bruggemann


Faculty of Built Environment and Engineering | 2006

Chip Scale Atomic Clocks: Benefits to Airborne GNSS Navigation Performance

Troy S. Bruggemann; Duncan G. Greer; Rodney A. Walker


AIAC15: 15th Australian International Aerospace Congress | 2013

Airborne collision scenario flight tests: impact of angle measurement errors on reactive vision-based avoidance control

Troy S. Bruggemann; Luis Mejias


Australian Research Centre for Aerospace Automation; Science & Engineering Faculty | 2015

Sensors for missions

Luis Mejias; John Lai; Troy S. Bruggemann

Collaboration


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Rodney A. Walker

Queensland University of Technology

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Jason J. Ford

Queensland University of Technology

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Duncan G. Greer

Queensland University of Technology

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Luis Mejias

Queensland University of Technology

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Jonathan Kok

Queensland University of Technology

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Duncan A. Campbell

Queensland University of Technology

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Luis F. Gonzalez

Queensland University of Technology

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Xilin Yang

Queensland University of Technology

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Yanming Feng

Queensland University of Technology

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Aaron Mcfadyen

Queensland University of Technology

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