In this paper we present a system which utilizes vision and touch for object apprehension. We define apprehension as the determination of the properties of an object and the relationships among these properties. This ...
详细信息
In this paper we present a system which utilizes vision and touch for object apprehension. We define apprehension as the determination of the properties of an object and the relationships among these properties. This is in contrast to recognition, which goes a step further in the determination process by attaching a label to the object as a whole. Vision is used to to obtain initial information about the object, including position, two dimensional segmentation, and three dimensional edge analysis. This data is then used to guide an active tactile system in its exploration of the object. The visual and tactile data are combined into a spatial polyhedral representation designed to allow further exploration of the object, as well as high level reasoning about the object and its components.
CAPTAIN is a collection of visual-interactive, digital-computer programs for time-series analysis and stochastic model building based around a central Instrumental Variable-Approximate Maximum Likelihood (iv-AML) para...
详细信息
CAPTAIN is a collection of visual-interactive, digital-computer programs for time-series analysis and stochastic model building based around a central Instrumental Variable-Approximate Maximum Likelihood (iv-AML) parameter estimation algorithm. In addition to preliminary model identification, parameter estimation and model validation, CAPTAIN has a forecasting option which is of particular importance when dealing with economic and industrial time-series. One important advantage of this approach to stochastic model building over other approaches based on block data processing is the recursive nature of the iv-AML procedure which provides additional information to the user and allows for the estimation of time-variable parameters. After providing a brief outline of the analytical procedures used in the constituent programs, the paper concentrates on a description of the program organization and operating system. Finally, several practical examples are discussed, including the analysis of discrete data obtained from a gas furnace, distillation columns and the U. K. economy.
CAPTAIN is a collection of visual-interactive, digital-computer programs for time-series analysis and stochastic model building based around a central Instrumental Variable-Approximate Maximum Likelihood (iv-AML) para...
详细信息
CAPTAIN is a collection of visual-interactive, digital-computer programs for time-series analysis and stochastic model building based around a central Instrumental Variable-Approximate Maximum Likelihood (iv-AML) parameter estimation algorithm. In addition to preliminary model identification, parameter estimation and model validation, CAPTAIN has a forecasting option which is of particular importance when dealing with economic and industrial time-series. One important advantage of this approach to stochastic model building over other approaches based on block data processing is the recursive nature of the iv-AML procedure which provides additional information to the user and allows for the estimation of time-variable parameters. After providing a brief outline of the analytical procedures used in the constituent programs, the paper concentrates on a description of the program organization and operating system. Finally, several practical examples are discussed, including the analysis of discrete data obtained from a gas furnace, distillation columns and the U. K. economy.
暂无评论