MODELING OF INTELLIGENT ROBOTIC GRIPPER FOR PRECISED OBJECT MANIPULATION USING ADAPTIVE CONTROL TECHNIQUE

This paper presents modeling of an intelligent robotic gripper for précised object manipulation using adaptive controller. The aim was to counter the impact of slip and position displacement constraints on object during grabbing, thus making the gripper inefficient. The methodology employed is the experimental and simulation approach. The methods used are experimental investigation of gripper performance developed with Dahl controller, data collection at Robotics and Artificial Intelligence in Nigeria (R.A.I.N) company, development of the gripper position algorithm using the output from proximity sensor, modeling of the adaptive controller using machine learning, development of the intelligent gripper system. The system was implemented with Simulink and tested. The adaptive controller when implemented on the gripper system and evaluated showed that it was able to apply the desired control force necessary for object grabbing and manipulation