การควบคุมแขนกลแบบผสมระหว่างภาพกับแรง - รัชทิน จันทร์เจริญ (จุฬาลงกรณ์มหาวิทยาลัย, 1999)
Normally, Industrial robots must be operated where the environment is contrived to suit the robot. The robots have less use in the applications where the working environment and the object position cannot be accurately specified. This limitation is due to the lack of sensory capability. Force and vision sensors can be used to improve the flexibility of the robot since they mimic the human sense of force and vision respectively. The robots are able to interact with its environment using these capabilities. In this research, the vision system is used to navigate the manipulator hand to a target object. The camera is in an eye-in-hand configuration and is able to capture the target position relative to the manipulator hand. Force sensor is also equipped to the robot hand. The task is to control force and visual parameters simultaneously, i.e., the target is in the middle of the image and also has the specified touching force, a 3 degrees of freedom task. The position of the target in the world coordinate is unknown. A new technique called Learning Control is developed to complete the task. This technique determines the Jacobian from the robot movement and uses it to determine the direction for updating joint angles. Since this technique does not require system modelling, it is applicable to any robots. Furthermore, this technique works on joint command and thus is able to implement on any industrial robot controller. We performed several experiments to validate the proposed method. The computer simulation is used to analyse the performance in various conditions.