This work presents a 3D scanner able to reconstruct a complete object without occlusions, including its surface appearance. The technique presents a number of differences in relation to current scanners: it does not require mechanical handling like robot arms or spinning plates, it is free of occlusions since the scanned part is not resting on any surface and, unlike stereo-based methods, the object does not need to have visual singularities on its surface. This system, among other applications, allows its integration in production lines that require the inspection of a large volume of parts or products, especially if there is an important variability of the objects to be inspected, since there is no mechanical manipulation. The scanner consists of a variable number of industrial quality cameras conveniently distributed so that they can capture all the surfaces of the object without any blind spot. The object is dropped through the common visual field of all the cameras, so no surface or tool occludes the views that are captured simultaneously when the part is in the center of the visible volume. A carving procedure that uses the silhouettes segmented from each image gives rise to a volumetric representation and, by means of isosurface generation techniques, to a 3D model. These techniques have certain limitations on the reconstruction of object regions with particular geometric configurations. Estimating the inherent maximum error in each area is important to bound the precision of the reconstruction. A number of experiments are presented reporting the differences between ideal and reconstructed objects in the system.
This paper introduces improvements in partitioning schemes for multiprocessor real-time systems which allow higher processor utilization and enhanced schedulability by using exact feasibility tests to evaluate the schedulability limit of a processor. The paper analyzes how to combine these tests with existing bin-packing algorithms for processor allocation and provides new variants which are exhaustively evaluated using two assumptions: variable and fixed number of processors. The problem of evaluating this algorithms is complex, since metrics are usually based on comparing the performance of a given algorithm to an optimal one, but determining optimals is often NP-hard on multiprocessors. This problem has been overcome by defining lower or upper bounds on the performance of an optimal algorithm and then defining metrics with respect this bounds. The evaluation has shown that the algorithms exhibit extremely good behaviors and they can be considered very close to the maximum achievable utilization. It is also shown that dynamic priority policies produces significantly better results than fixed priorities policies when task sets require high processor utilizations.
Abstract. Time-triggered and concurrent priority-based scheduling are the two major approaches in use for real-time and embedded systems. Both approaches have their own advantages and drawbacks. On the one hand, priority-based systems facilitate separation of concerns between functional and timing requirements by relying on an underlying realtime operating system that takes all scheduling decisions at run time. But this is at the cost of indeterminism in the exact timing pattern of execution of activities, namely variable release jitter. On the other hand, time-triggered schedules are more intricate to design since all scheduling decisions must be taken beforehand in the design phase, but their advantage is determinism and more chances for minimisation of release jitter. In this paper we propose a software architecture that enables the combined and controlled execution of time-triggered plans and priorityscheduled tasks. We also describe the implementation of an Ada library supporting it. Our aim is to take advantage of the best of both approaches by providing jitter-controlled execution of time-triggered tasks (e.g., control tasks), coexisting with a set of priority-scheduled tasks, with less demanding jitter requirements.
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