把持特徴量と把持動作分類を用いたマスタ・スレーブシステム

抄録

In recent years, master-slave system equipped with multi-fingered hands that can be operated intuitively and intricately in hazardous environments, such as disaster sites, are in demand. However, there are two main problems. First, human hand movements have a high degree of freedom, making it difficult to accurately measure shapes in real time. Second, because of the kinematic structural differences between the human hand and the robot hand, it is difficult for the slave side to properly represent the motion intended by the master side. To solve these problems, we propose a method for mapping via grasping features and compensating the mapping using grasping motion classification. Experimental results show that the proposed method enables smooth teleoperation of the robot hand, and the introduction of SVM improves the accuracy of grasping motion classification.