Programming 3 DOF Industrial Robots with Natural Hand Motions: An Impedance Control Approach

Programming industrial robots is a complex and time-consuming task that requires skilled operators. To simplify this process, this study proposes a method for programming a 3 DOF robot using natural hand motions. During the robot learning phase, the human operator holds and moves the robot's endpoint to the desired position, and saves it without using force/torque sensors. The impedance controller coefficients are then adjusted to minimize the gravity effects to zero, ensuring seamless movement of the robot without resistance. It has been observed that the reaction forces on the human hand are very low except for the singular position of the robot, where the reaction forces increase. During the operating mode, the robot's endpoint visits the sequential positions taught by the human, and the Bees Algorithm is used to optimize the impedance controller coefficients based on simulations. The proposed method is flexible and can be applied to various tasks, making it suitable for a wide range of applications. Simulation results demonstrate the effectiveness of this method, highlighting its potential to enhance the performance of industrial robots when interacting with the environment. The optimized impedance controller ensures precise movements, and the proposed method offers several advantages over traditional programming methods, such as reduced programming time and improved ease of use. Overall, this study presents a promising solution to the challenges of programming industrial robots using natural hand motions, offering a more efficient and user-friendly approach that can enhance productivity and improve product quality. Further research is needed to explore the potential of this method in more complex tasks and environments.