In this paper, we present a deciding technique for robotic dexterous hand configurations. This algorithm can be used to decide on how to configure a robotic hand so it can grasp objects in different scenarios. Receiving as input, several sensor signals that provide information on the object's shape, the DSmT decision-making algorithm passes the information through several steps before deciding what hand configuration should be used for a certain object and task. The proposed decision-making method for real time control will decrease the feedback time between the command and grasped object, and can be successfully applied on robot dexterous hands. For this, we have used the Dezert-Smarandache theory which can provide information even on contradictory or uncertain systems.

This paper presents the workflow to create a robotic humanoid hand simulation environment using two top software packages and also the implementation of an intelligent hybrid force - position control method using neural networks for force closing operation of a humanoid robotic hand modeled in the 3D virtual environment. The benefits that the 3D modeling provides are described and then the results of the proposed method are presented. This approach allows studying the motion of the robotic system under different circumstances without any greater costs.

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