Abstract：Fuzzy adaptive impedance control strategy is proposed based on neural network visual servoing in unknown environment. Firstly, the one-to-one mapping relations between the image features variation rate of the curved line and the joint angular velocity of the robot are derived. Secondly, an impedance control model is obtained to control the force servoing of the robot, and the impedance model parameters are adjusted fuzzily according to the change of forces in contact to reduce their disturbance in constraint motion. Lastly, the effectiveness of the presented approach is verified by using a 6 DOF robot with a CCD camera and a force/torque sensor installed in its end effector.
李二超, 李战明, 李炜. 基于神经网络视觉伺服的机器人模糊自适应阻抗控制[J]. 电工技术学报, 2011, 26(4): 40-43.
Li Erchao, Li Zhanming, Li Wei. Robotic Fuzzy Adaptive Impedance Control Based on Neural Network Visual Servoing. Transactions of China Electrotechnical Society, 2011, 26(4): 40-43.
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2011, Vol. 26 
