In order to investigate the joint torque-based Cartesian impedance control strategies and the influence of compensations for friction, an experimental study on the identification of friction parameters, friction compensation and the Cartesian impedance control are developed for the harmonic drive robot, by using the sensors available in the joint itself. Different from the conventional Cartesian impedance control schemes which are mostly based on the robot end force/torque information, five joint torque-based Cartesian impedance control schemes are considered, including the force-based schemes in Cartesian/joint space, the position-based schemes in Cartesian/joint space and the stiffness control. Four of them are verified by corresponding experiments with/without friction compensations. By comparison, it is found that the force-based impedance control strategy is more suitable than the position-based one for the robot based on joint torque feedback and the friction has even a positive effect on Cartesian impedance control stability.
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.
Da-peng Yang~1 Jing-dong Zhao~1 Yi-kun Gu~1 Xin-qing Wang~1 Nan Li~1 Li Jiang~1Hong Liu~(1,2) Hai Huang~3 Da-wei Zhao~41.State Key Laboratory of Robotics and System,Harbin Institute of Technology,Harbin 150001,P.R.China2.Institute of Robotics and Mechatronics,German Aerospace Center,Munich 82230,Germany3.College of Shipbuilding Engineering,Harbin Engineering University,Harbin 150001,P.R.China4.College of Automation,Harbin Engineering University,Harbin 150001,P.R.China
