Probabilistic scan mode of a robot manipulator workspace using EEG signals. Part II

In this paper a probabilistic-based workspace scan mode of a robot manipulator is presented. The workspace is divided into cells. Each cell has its own probability value associated with it. Once the robot reaches a cell, its probability value is updated. The updating process is governed by a recursive Bayes algorithm. A performance comparison between a sequential scan mode and the one proposed here is made. Mathematical derivations and experimental results are also shown in this paper.