Abstract-We address the problem of controlling a mobile robot to explore a partially known environment. The robot's objective is the maximization of the amount of information collected about the environment. We formulate the problem as a partially observable Markov decision process (POMDP) with an information-theoretic objective function, and solve it applying forward simulation algorithms with an open-loop approximation. We present a new sample-based approximation for mutual information useful in mobile robotics. The approximation can be seamlessly integrated with forward simulation planning algorithms. We investigate the usefulness of POMDP based planning for exploration, and to alleviate some of its weaknesses propose a combination with frontier based exploration. Experimental results in simulated and real environments show that, depending on the environment, applying POMDP based planning for exploration can improve performance over frontier exploration.
The key operation in tissue production is the creping at the Yankee cylinder. The tissue sheet is adhered to a Yankee cylinder and then detached from the surface with a blade. As a result a strong microstructure - crepe folds - is generated on the web. In this work the structure of creping pattern in CD and MD of tissue paper was studied. The samples available in this work consisted of bath tissue and towel grades. The significant difference between the samples was in the number of crepe folds. The tissue sheets were analyzed with an imaging system. The variation of crepe folds in images was studied in spatial frequency space through 2D Welch spectrum. It was noticed that the difference in creping pattern structure between the samples can be seen clearly in spectra. The creping pattern was simulated based on the creping pattern variation found from the Welch spectra of tissue paper images. The simulation was based on a set of sinusoidal terms representing several orientations and amplitudes. The amplitudes of sinusoidal terms located in regular grid in spectra were approximated with 2D normal distribution. Thus, the structure of creping pattern can be represented with three parameters originating from the deviations and location of 2D normal distribution. The creping pattern reconstructed with simulations contains the relevant features in the creping pattern of true tissue images.
In pulp and paper the modelling and simulation of the pulp production processes was the first major application. Since then several other applications have been realised though papermaking has never been on the lead concerning the use of computer-based modelling and simulation. The complex nature of the materials is one of the most demanding challenges and the biggest hurdle for any electronic description of the papermaking process or paper itself. So other industries took the lead and it is now for the paper industry to learn from these industries what can be done with the help of computers to control or optimise processes or to design new grades.The application of results gained with the use of modelling and simulation techniques in pulp and paper manufacturing processes has helped the industry to, for example, reduce emissions and increase the productivity and cost-efficiency of the processes. Still there are many important tasks open. A better understanding of the mechanisms of the processes and their control loops has to be achieved in order to further improve the paper quality, stabilise the wet-end chemistry, and enhance the runnability. Important features to be developed are new process designs, efficient process monitoring and systems that offer decision support during operation.In this paper a review of the state of the art on modelling and simulation in the pulp and paper industry is presented as well as further research needs.
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