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Meet up

Unmanned Aircraft System Concept Design and Formations of flying cameras to film a moving target

Monday, 9th November at CodeNode, London

This meetup is run by The London Big-O Meetup. Starts at 6:30 PM.

In this meetup we will have two talk on some very interesting recent developments in flying technologies.

Unmanned Aircraft System Concept Design

In this meetup we will have two talk on some very interesting recent developments in flying technologies.

This presentation will give an introduction to the Multi-Objective and Multi-Disciplinary Optimisation approaches involved in the conceptual design process of Unmanned Aircraft Systems (UAS), specifically focused towards fixed wing UAS. The design of UAS requires a multi-disciplinary approach that not only considers the aircraft itself, but also other major sub-systems such as the communication systems, payload systems, propulsion system, avionics architecture, and many others. Thus, to develop a well balanced design, key system elements must have the right proportions, allocation of attributes, and satisfy the operational needs. This presentation will define a systems engineering approach, with the inclusion of multi-objective optimisation algorithms, to define a well balanced system that accounts for performance metrics which defines the ‘goodness’ of a system. In addition, the presentation will also recommend some open source tools that can be used to develop a simulation framework to calculate the performance of a given UAS architecture.

Amrith Surendra

I recently joined Frazer-Nash consultancy as an engineer to provide technical consultancy support, in the form of software implementations of engineering models, to clients in the defence and energy sectors. Prior to joining Frazer-Nash I completed my postgraduate research studies in the computational engineering design department, at Southampton University. The research was focused towards the development of a new decision support system that aids system designers to identify optimal design solutions. This is achieved by combining methods and algorithms developed in the fields of, multi-objective optimization, decision theory, systems engineering, and graph theory.

Formations of flying cameras to film a moving target

Quadcopters are highly manoeuvrable and can provide an effective means for an agile positioning of sensors such as cameras (flying cameras). In this talk I will present how visual sensing can allow flying cameras to fly in formations without the need of external positioning systems such as GPS. I will address the problem of formations following a moving (ground) target, and explain a distributed decision-making process performed via sensing and sharing of information among neighbouring flying cameras. Given formations of up to 12 flying cameras, I will show how the target-following performance varies when the visual sensing is used as opposed to a GPS-only-based positioning.

Fabio Poiesi

Fabio Poiesi is a postdoc in the Centre for Intelligent Sensing at Queen Mary University of London. He received his PhD degree from the same university in March 2014, supervised by Prof. Andrea Cavallaro. He published in journals such as IEEE Trans. on Image Processing, IEEE Trans. on Circuits and Systems for Video Technology, Computer Vision and Image Understanding, and in conferences such as IROS, ICIP and AVSS.

Thanks to our sponsors

Attending Members

Overview

In this meetup we will have two talk on some very interesting recent developments in flying technologies.

Unmanned Aircraft System Concept Design

In this meetup we will have two talk on some very interesting recent developments in flying technologies.

This presentation will give an introduction to the Multi-Objective and Multi-Disciplinary Optimisation approaches involved in the conceptual design process of Unmanned Aircraft Systems (UAS), specifically focused towards fixed wing UAS. The design of UAS requires a multi-disciplinary approach that not only considers the aircraft itself, but also other major sub-systems such as the communication systems, payload systems, propulsion system, avionics architecture, and many others. Thus, to develop a well balanced design, key system elements must have the right proportions, allocation of attributes, and satisfy the operational needs. This presentation will define a systems engineering approach, with the inclusion of multi-objective optimisation algorithms, to define a well balanced system that accounts for performance metrics which defines the ‘goodness’ of a system. In addition, the presentation will also recommend some open source tools that can be used to develop a simulation framework to calculate the performance of a given UAS architecture.

Amrith Surendra

I recently joined Frazer-Nash consultancy as an engineer to provide technical consultancy support, in the form of software implementations of engineering models, to clients in the defence and energy sectors. Prior to joining Frazer-Nash I completed my postgraduate research studies in the computational engineering design department, at Southampton University. The research was focused towards the development of a new decision support system that aids system designers to identify optimal design solutions. This is achieved by combining methods and algorithms developed in the fields of, multi-objective optimization, decision theory, systems engineering, and graph theory.

Formations of flying cameras to film a moving target

Quadcopters are highly manoeuvrable and can provide an effective means for an agile positioning of sensors such as cameras (flying cameras). In this talk I will present how visual sensing can allow flying cameras to fly in formations without the need of external positioning systems such as GPS. I will address the problem of formations following a moving (ground) target, and explain a distributed decision-making process performed via sensing and sharing of information among neighbouring flying cameras. Given formations of up to 12 flying cameras, I will show how the target-following performance varies when the visual sensing is used as opposed to a GPS-only-based positioning.

Fabio Poiesi

Fabio Poiesi is a postdoc in the Centre for Intelligent Sensing at Queen Mary University of London. He received his PhD degree from the same university in March 2014, supervised by Prof. Andrea Cavallaro. He published in journals such as IEEE Trans. on Image Processing, IEEE Trans. on Circuits and Systems for Video Technology, Computer Vision and Image Understanding, and in conferences such as IROS, ICIP and AVSS.

Thanks to our sponsors

Who's coming?

Attending Members