907 resultados para Robot vision systems
Resumo:
We address robust stabilization problem for networked control systems with nonlinear uncertainties and packet losses by modelling such systems as a class of uncertain switched systems. Based on theories on switched Lyapunov functions, we derive the robustly stabilizing conditions for state feedback stabilization and design packet-loss dependent controllers by solving some matrix inequalities. A numerical example and some simulations are worked out to demonstrate the effectiveness of the proposed design method.
Resumo:
A range of influences, both technical and organisational, has encouraged the wide spread adoption of Enterprise Systems (ES). Nevertheless, there is a growing consensus that Enterprise Systems have in many cases failed to provide expected benefits. The increasing role of, and dependency on ES (and IT in general), and the ‘uncertainty’ of these large investments, have created a strong need to monitor and measure ES performance. This paper reports on a research project aimed at deriving an ‘Enterprise Systems benefits measurement instrument’. The research seeks to identify how Enterprise Systems benefits can be usefully measured, with a ‘balance’ between qualitative and quantitative factors.
Resumo:
A range of influences, both technical and organizational, has encouraged the widespread adoption of Enterprise Systems (ES). The integrated and process-oriented nature of Enterprise Systems has led organizations to use process modelling as a means of managing the complexity of these systems, and to aid in achieving business goals. Past research illustrates how process modelling is applied across different Enterprise Systems lifecycle phases. However, no empirical evidence exists to evaluate what factors are essential for a successful process modelling initiative, in general or in an ES context. This research-in-progress paper reports on an empirical investigation of the factors that influence process modelling success. It presents an a-priori process modelling critical-success-factors-model, describes its derivation, and concludes with an outlook to the next stages of the research.
Resumo:
Person tracking systems are dependent on being able to locate a person accurately across a series of frames. Optical flow can be used to segment a moving object from a scene, provided the expected velocity of the moving object is known; but successful detection also relies on being able segment the background. A problem with existing optical flow techniques is that they don’t discriminate the foreground from the background, and so often detect motion (and thus the object) in the background. To overcome this problem, we propose a new optical flow technique, that is based upon an adaptive background segmentation technique, which only determines optical flow in regions of motion. This technique has been developed with a view to being used in surveillance systems, and our testing shows that for this application it is more effective than other standard optical flow techniques.