No abstract

The ability to quickly fabricate sensorcraft, or other small unmanned aircraft, via additive manufacturing techniques opens a range of new possibilities for the design and optimization of these vehicles. In this paper we propose a design loop that makes use of surrogate modeling and additive manufacturing to reduce the design and optimization time of scientific sensorcraft. Additive manufacturing reduces the time and effort required to fabricate a complete aircraft, allowing design iterations to be quickly manufactured and flight tested. Co-Kriging surrogate models allow data collected from test flights to correct Kriging models trained with numerically simulated data. The resulting model provides physically accurate and computationally cheap aircraft performance predictions. A global optimizer is used to search this model to find an optimal design for a bespoke aircraft. This paper presents the design loop and the progress made in implementing this design loop. Results are shown from Kriging models trained using numerically simulated data.Progress towards extracting aerodynamic data from flight testing small unmanned aircraft is also documented.

The ability to quickly fabricate small unmanned aircraft (sUAS) through additive manufacturing (AM) methods opens a range of new possibilities for the design and optimization of these vehicles. In this paper we propose a design loop that makes use of surrogate modeling and AM to reduce the design and optimization time of scientific sUAS. AM reduces the time and e↵ort required to fabricate a complete aircraft, allowing for rapid design iterations and flight testing. Co-Kriging surrogate models allow data collected from test flights to correct Kriging models trained with numerically simulated data. The resulting model provides physically accurate and computationally cheap aircraft performance predictions.A global optimizer is used to search this model to find an optimal design for a bespoke aircraft. This paper presents the design loop and a case study which demonstrates its application.

This paper describes the current development of a novel 4D scanner, which can fully sample three dimensional motion at 12.5Hz. The scanner a variant on structured light produces a series of position lines every 4Oms, from each video frame. The reconstruction of the range information uses a colour coded pattern, which is analyzed by a flexible and robust pattern matching algorithm.