Abstract
A multi-fingered hand has been used in the explosive Disposal Robot to improve the disposal ability of explosive. Grasping ability of the multi-fingered hand is a problem with the change of grasping posture. This paper discusses grasping ability of the multi-fingered robot hand. Screw theory and BP neural network are used to optimize the joint angle of the finger. The most favorite grasping posture is calculated when the multi-fingered robot hand can withstand the largest external wrench. In order to guarantee the explosive not to be exploded under the exceeding grasp force, the weight of the explosive the multi-fingered hand can hold is also discussed in this paper. It is an important theoretical guidance for the multi-fingered robot hand handling of hazardous items.
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