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The dynamic grid map illustrates the environment of robots with moving and static obstacles. Nuss et al. describe in [1] an implementation of this grid map, in which the state of the grid cells is to be modeled as a random finite set (RFS) based on a stochastic measurement system. For a real-time implementation this approach was approximated with Dempster-Shafer (DS). For this Nuss et al. design the...
This paper explores a novel model to describe linear dynamic system with random delays. Compared with the existing research, the probabilities of random delays in the novel model are calculated by conditional probabilities. Therefore, the process noises and measurements noises in the new model for random delay problems are infinitely correlated. By treating the model as random parameter matrices Kalman...
The wide-sense auto-regressive moving-average (ARMA) model is widely applied into varieties of fields. The unknown bounded parameter estimation of an ARMA model is an extremely vital research subject. Up to recent, most research is conducted with the known disturbing environment noise or the model of the known noise with the unknown variance. Actually the disturbing noise in the modern control system...
The multiple hypothesis tracker (MHT) has historically been considered a gold standard for multi-target tracking. In this paper we show that the key formula for hypothesis probabilities in Reid's MHT can be derived from the modern theory of finite set statistics (FISST) insofar as appropriate assumptions (Poisson models for clutter and undetected targets, no target-death, linear-Gaussian Markov target...
In 2016 we developed a new approach for Multi-Criteria Decision-Making (MCDM) inspired by the technique for order preference by similarity to ideal solution (TOPSIS) and based on belief functions (BF). Our BF-TOPSIS (Belief Function based TOPSIS) approach assumes that the input score of each hypothesis for each criterion was a real precise number which is a quite restrictive assumption. In this paper...
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