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Operations involving autonomous vehicles require knowledge of the surrounding environment including other moving vehicles. The use of vision has been regarded as an enabling technology that can provide such information. Several important applications that would benefit from this technology is autonomous aerial refueling (AAR) and target tracking. This paper considers a sensor fusion approach using traditional IMU/GPS sensors with vision to facilitate the state estimation problem of moving targets. The proposed method makes use of a moving monocular camera to estimate the relative position and orientation of targets within the image by exploiting a known reference motion. The vision state estimation problem is solved using an homography approach that employs images containing both the reference and target vehicles. A simulation involving an unmanned aerial vehicle (UAV) and two ground vehicles is documented in this paper to demonstrate the algorithm and its accuracy.

High speed machining of aluminum and magnesium helicopter gearcases was experimentally demonstrated to be five times more productive than contemporary conventional commercial practice for suitable operations. Appropriate techniques and performance characteristics are discussed for face milling, endmilling and planetary milling operations. Potential problem areas, such as surface characteristics and machine tool performance requirements are discussed.

In this paper, we introduce the use of ontologies to implement the information developed and organized by resource planning tools into standard project management documents covering integrated cost, resource modeling and analysis, and visualization. The basic upper ontology used for NASA Space Operations is explained and the results obtained are discussed. This ontology-centered approach is looking for tighter connections between software, hardware, and systems engineering.

Unmanned aerial vehicles (UAVs) stand to play a significant role in future sensing and information gathering missions. The scope of these mission scenarios is expanding to include those missions for which the sensor and carrier vehicle will be in close proximity to the surrounding environment, such as in urban operations. Several unique problems related to guidance, navigation and control are introduced that separate these tasks from the existing paradigm for information gathering missions at standoff range. This paper examines the challenges related to autonomous sensor planning missions in these close proximity environments and discusses solution strategies to achieve maximal sensing effectiveness. Specifically, results from vision-based navigation research are discussed and the concept of a geometric sensing effectiveness criterion is introduced and subsequently utilized for motion planning.

A stiffness requirement for high speed milling machines is determined by examining the stiffness of current generation high speed spindles. The desire for stability against chatter dictates that the stiffness of the machine structure and drives, when reflected to the tool tip exceed the spindle/tool holder/tool stiffness. The stiffness characteristics of a classical serial machine tool designed expressly for high speed milling are shown. Another potential design for high speed machining applications, the parallel kinematic or hexapod structure is also examined. It is found that hexapod structures exhibit lower structural stiffness than can be achieved in serial machines when using the same drive components. Furthermore, the stiffness of the hexapod structure varies widely across the workspace, leading to difficulties in control and limiting the achievable accuracy.

Precision glass molding process is an attractive approach to manufacture small precision optical lenses in large volume over traditional manufacturing techniques because of its advantages such as low cost, fast time to market and being environment friendly. In this paper, we present a physics-based computational tool that predicts the final geometry of the glass element after molding process using the finite element method. Deformations of both glass and molds are considered at three different stages: heating, molding, and cooling. A 2D axisymmetric finite element model is developed to model the glass molding process. The proposed modeling technique is more efficient than the all-in-one modeling technique. The molds are assumed to be rigid, except for thermal expansion, at all time and glass treated as a flexible body during the compression. Details on identifying material parameters, modeling assumptions, and simplifications are discussed.