文摘
This paper introduces the notion of a Probability Navigation Function for motion planning. We start by estimating and predicting the Probability Density Function (PDF) of the obstacles’ locations. We then calculate the PNFs for a sequence of NfwdNfwd time steps. We then calculate the kkth incremental movement taking into consideration the k+1,…,k+Nfwdk+1,…,k+Nfwd predicted configurations. The algorithm is demonstrated on different scenarios and compared with the performance of a static PNF with that of a traditional NF.