抄録
Robot manipulators are expected to perform sophisticated tasks in many fields. In order to perform sophisticated tasks, robot manipulators have to control both position and force simultaneously. Robots are also expected to work not only in limited environments, but also in unknown environments. However, conventional controllers have some problems to control force on unknown environments, because they do not have ability of adapting to the unknown environment. Furthermore, friction compensation is difficult, especially for an unknown environment, because the friction between the robot manipulator and the environment varies when the applied force to the environment changes. In this paper, neural networks and fuzzy-neural networks are applied to position/force hybrid control in order to solve these problems.
The effectiveness of the proposed controller is verified with a 3DOF planar robot manipulator by computer simulations.
