Map Building for a Mobile Robot Based on Grey System Theory

In this paper, a new method for mobile robot map building based on grey system theory is presented, by which interpretation and integration of sonar readings can be solved robustly and efficiently. The conception of 'grey number is introduced to model and handle the uncertainty of sonar reading. A new data fusion approach based on grey system theory is proposed to construct environment model. Map building experiments are performed both on a platform of simulation and a real mobile robot. Experimental results show that our method is robust and accurate.

The simulation and mapping of building performance indicators based on European weather stations

Due to the climate change debate, a lot of research and maps of external climate parameters are availtabte. However, maps of indoor climate performance parameters are still Lacking. This paper presents a methodology for obtaining maps of performances of similar buitdings that are virtually spread over whole Europe. The produced maps are useful for anaty-zing regional climate influence on building performance indicators such as energy use and indoor climate. This is shown using the Bestest building as a reference benchmark. An important application of the mapping tool is the visualization of potential building measures over the EU. Also the performances of singte building components can be simulated and mapped. It is concluded that the presented method is efficient as it takes less than 15min to simulate and produce the maps on a 2.6GHz/4GB computer. Moreover, the approach is applicable for any type of building.

An efficient method of evaluating large scale urban residential skylight environment and an empirical study of Beijing main area

A good skylight environment in urban residential areas is an important component of a healthy city,and has always been highly valued.With the rapid development of new-type urbanization,the density of buildings continues to increase,and megacities have entered the stage of stock transformation.An effective method for evaluating the skylight environment of large-scale urban residential areas is urgently needed.However,there is still a lack of empirical research methods and cases of large-scale residential skylight environment.In this regard,this article takes the megacity Beijing as the research object,and proposes an efficient analysis method of residential skylight environment that integrates multiple real-world data at city scale.In terms of data,it collects and integrates 3D data of urban-scale building space and residential boundary data;in terms of algorithm,Sky View Factor(SVF)is used as the evaluation index of residential skylight environment,and an efficient analysis method of urban-scale skylight environment based on cloud parallel simulation is realized.Through analysis,it is found that:(1)the average SVF value of Beijing residential area is 61%,which means that its skylight quality is in general level;(2)the skylight environment of Beijing residential area is distributed in a circle,and there are 4 types of skylight environment quality residential areas;(3)The skylight environment of Beijing residential area is relatively weakly related to the distance from the residential area to the city center and the average height of the residential buildings,and is closely related to the plot volume ratio,the residential building density and the shading from surrounding buildings.The highlight of this study lies in the empirical research on the skylight environment of mega-city residential areas that incorporates multiple real data for the first time,which can promote the study of skylight environment on a city scale and provide a reference for the updating of Beijing’s residential daylight environment.