Daniel Schrage

Wing Design as a Symphony of Geographically Dispersed, Multi-disciplinary, Undergraduate Students

Globalization, technology, and risk sharing business partnerships have changed the landscape of large scale systems integration. In today’s business environment, the traditional style of knowledge transfer presuppositions and foundations are inadequate for dissemination of process knowledge in a global multi-cultural environment. The following paper describes a research university – industry approach as well as knowledge transfer strategies for successfully implementing a “Multi-site, cloud based capstone design project” within a cross cultural peer-to-peer design-build-test environment. Within this environment students were exposed to the industry principles of collaborative digital design and manufacturing targeting complex cyber-mechanical systems. Proper software selection, especially to facilitate instantaneous file sharing, collaborative analysis, and face-to-face meetings proved critical to the students’ success. Given ever increasing computing power and proliferation and familiarity of the current generation with social networking applications and virtual design-build-test methodologies for design verification and quality assurance demonstrate a major advancement and departure from traditional aircraft design and manufacturing approaches.

Automatic Pixel Geo-Registration for Aerial Systems - An integrated approach

Geo-registration is the technique of mapping the pixel co-ordinates from images to geocoordinates. Generally, this is achieved by adjusting and aligning the input images with a standard reference image. Geo-registration helps aerial systems in target detection, target tracking as well as exploration. For aerial systems, the information from the cameras may be inaccurate as the parameters of registration between them may not be known precisely. So, simultaneously reflning the registration parameters and performing geo-registration is a huge challenge. In this paper, we propose a solution based on image segmentation and image registration in order to automatically perform pixel geo-registration. The solution is generic and can be applied to any form of image-based sensing across a variety of modalities. In our approach, images are flrst segmented using the active contour methodology and geometric partial difierential equations (PDEs) based on curve and surface evolution theory. Region-based active contours are the preferred model for registration applications as they are able to utilize more image data in the simultaneous registration and segmentation process. The features extracted after the segmentation are more robust to scene changes than the traditional pixel-to-pixel image registration techniques. Since segmentation may be aided by the solution of registration and vice-versa, it is natural to couple the problems and solve them jointly. Our focus has been to combine segmentation speciflcally with image registration in a joint, simultaneous framework where both problems are solved together with continuous and constant feedback rather than solving one problem in isolation and then using the results of the flrst solution to solve the second problem. We develop an integrated iterative approach to unify the techniques of image registration and image segmentation to provide a robust solution for pixel geo-registration. The geo-registration algorithm is currently being incorporated into a simulator framework with visualization for depicting the terrain using 3D graphics.

Obstacle Avoidance and Cloud Detection for Unmanned Aerial Systems

Unmanned Aerial Vehicles (UAVs) that operate in civil airspace and ∞y autonomously must have regard for the safety of other vehicles in space the UAV must be equipped with technology for obstacle detection and avoidance. One of the problems with UAVs is the detection and avoidance of clouds and other visual obstructions. In this paper, we propose a system for automated detection of cloud edges as well as the sky regions to maintain operation in visual meteorological conditions using image processing. The solution is based on partial difierential equations (PDE) for image processing. Anisotropic difiusion is a wellknown PDE-based technique and has been widely used in image processing for denoising and segmentation. Recently, new anisotropic difiusion techniques such as anti-geometric difiusion models have been developed which are used for adaptive thresholding and denoising. Using techniques for region merging along with anti-geometric difiusion, helps to separate the scene in a few number of signiflcant regions, thus providing an integrated system for segmentation. This technique works well when there is contrast between the cloud regions and the other areas. To improve the contrast, we propose a preprocessing step of normalizing the input color image where each pixel is treated as a vector. The normalized vector is then projected on the Blue channel. The results obtained by using the modifled scene are shown in the paper. An e‐cient real-time algorithm is being developed so that the algorithm may be used with video sequences. The incorporation of the technique in the UAV simulator tool that is being developed by the co-authors is currently being pursued. I. Introduction Safety is a major concern for Unmanned Aerial Systems (UAS) that operate in civil airspace. The UAS are expected to ∞y autonomously avoiding obstacles and ∞ying through challenging atmospheric conditions. It is desirable that the UAS be equipped with means to maintain operation in visual meteorological conditions while having regard for the safety of other vehicles. One of the major problems with UAS is the detection and avoidance of clouds and other visual obstructions. In this paper, we propose a system for automated detection of cloud edges using image processing. The solution is based on using geometric partial difierential

An IPPD Approach For Preliminary Design Of Two-Place Turbine Training Helicopter

This paper describes research done for a two-place turbine training helicopter to successfully enter today’s challenging market. It must ofier superior performance, handling qualities, and safety capability at a price competitive with that of the Robinson R-22, the current world sales leader in two-place piston training helicopters. In order to meet this formidable design challenge, the priority of this design efiort was focused on the simpliflcation of systems and subsystems for both the vehicle and the process by which it would be built. Therefore, an Integrated Product and Process Development (IPPD) methodology was used to drive the design solution - ultimately generating the Georgia Tech Rambler for the winning graduate entry in the 2006 American Helicopter Society (AHS) student design competition.