20 resultados para Tracking performance
Resumo:
This paper presents a new strategy for controlling rigid-robot manipulators in the presence of parametric uncertainties or un-modelled dynamics. The strategy combines an adaptation law with a well known robust controller proposed by Spong, which is derived using Lyapunov's direct method. Although the tracking problem of manipulators has been successfully solved with different strategies, there are some conditions under which their efficiency is limited. Specifically, their performance decreases when unknown loading masses or model disturbances are introduced. The aim of this work is to show that the proposed strategy performs better than existing algorithms, as verified with real-time experimental results with a Puma-560 robot. (c) 2006 Elsevier Ltd. All rights reserved.
Resumo:
Radial basis functions can be combined into a network structure that has several advantages over conventional neural network solutions. However, to operate effectively the number and positions of the basis function centres must be carefully selected. Although no rigorous algorithm exists for this purpose, several heuristic methods have been suggested. In this paper a new method is proposed in which radial basis function centres are selected by the mean-tracking clustering algorithm. The mean-tracking algorithm is compared with k means clustering and it is shown that it achieves significantly better results in terms of radial basis function performance. As well as being computationally simpler, the mean-tracking algorithm in general selects better centre positions, thus providing the radial basis functions with better modelling accuracy
Resumo:
There is a rising demand for the quantitative performance evaluation of automated video surveillance. To advance research in this area, it is essential that comparisons in detection and tracking approaches may be drawn and improvements in existing methods can be measured. There are a number of challenges related to the proper evaluation of motion segmentation, tracking, event recognition, and other components of a video surveillance system that are unique to the video surveillance community. These include the volume of data that must be evaluated, the difficulty in obtaining ground truth data, the definition of appropriate metrics, and achieving meaningful comparison of diverse systems. This chapter provides descriptions of useful benchmark datasets and their availability to the computer vision community. It outlines some ground truth and evaluation techniques, and provides links to useful resources. It concludes by discussing the future direction for benchmark datasets and their associated processes.
Resumo:
Purpose – This paper seeks to make the case for new research into the perceived fairness and impact of executive pay. Design/methodology/approach – The paper reviews the literature regarding executive compensation and corporate performance and examines the evidence that a more egalitarian approach to pay could be justified in terms of long-term shareholder value. Findings – There would appear to be no evidence to suggest that the growing gap between the pay of executives and that of the average employee generates long-term enterprise value, and it may even be detrimental to firms, if not the liberal capitalist consensus on which the corporate licence to operate is based. Research limitations/implications – The paper outlines a new approach to tracking income differentials with corporate performance through the development of a corporate Gini coefficient “league table”. Social implications – The proposed research is expected to point towards better practice in executive remuneration, and support the growing momentum for a sustainable and enlightened approach to business, in which the key goal is long-term enterprise value based on a fair distribution of the rewards of business. Originality/value – In producing a deeper understanding of the impact of widening income differentials, the paper should be of interest to senior executives in publicly quoted companies as well as press commentators, government officials and academics.