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J4 ›› 2009, Vol. 6 ›› Issue (3): 255-264.doi: 10.1016/S1672-6529(08)60119-5

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An Anthropomorphic Robot Hand Developed Based on Underactuated Mechanism and Controlled by EMG Signals

Da-peng Yang1, Jing-dong Zhao1, Yi-kun Gu1, Xin-qing Wang1, Nan Li1, Li Jiang1, Hong Liu1,2, Hai Huang3, Da-wei Zhao4   

  1. 1. State Key Laboratory of Robotics and System, Harbin Institute of Technology, Harbin 150001, P. R. China
    2. Institute of Robotics and Mechatronics, German Aerospace Center, Munich 82230, Germany
    3. College of Shipbuilding Engineering, Harbin Engineering University, Harbin 150001, P. R. China
    4. College of Automation, Harbin Engineering University, Harbin 150001, P. R. China
  • Online:2009-09-30
  • Contact: Da-peng Yang E-mail: law_1209@hit.edu.cn E-mail:law_1209@hit.edu.cn

Abstract:

When developing a humanoid myo-control hand, not only the mechanical structure should be considered to afford a high dexterity, but also the myoelectric (electromyography, EMG) control capability should be taken into account to fully accomplish the actuation tasks. This paper presents a novel humanoid robotic myocontrol hand (AR hand III) which adopted an underac-tuated mechanism and a forearm myocontrol EMG method. The AR hand III has five fingers and 15 joints, and actuated by three embedded motors. Underactuation can be found within each finger and between the rest three fingers (the middle finger, the ring finger and the little finger) when the hand is grasping objects. For the EMG control, two specific methods are proposed: the three-fingered hand gesture configuration of the AR hand III and a pattern classification method of EMG signals based on a statistical learning algorithm – Support Vector Machine (SVM). Eighteen active hand gestures of a testee are recognized ef-fectively, which can be directly mapped into the motions of AR hand III. An on-line EMG control scheme is established based on two different decision functions: one is for the discrimination between the idle and active modes, the other is for the recog-nition of the active modes. As a result, the AR hand III can swiftly follow the gesture instructions of the testee with a time delay less than 100 ms.

Key words: humanoid hand, underactuated mechanism, EMG control, support vector machine