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Proceedings of the 42nd IEEE Conference on Decision and Control Maui, Hawaii USA, December 2003 FrM084 Visual Serving of 6 DOF Manipulator by Multi rate Control with Depth Identification Hiroshi Fujiko

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1. Initialize the visual servoing system by setting up the camera and the robot arm. Make sure the camera is properly calibrated and positioned to capture the necessary visual feedback.
2. Define the desired task or motion that you want the robot arm to perform. This could be anything from picking up an object to following a specific trajectory.
3. Determine the appropriate control algorithm for visual servoing. There are several different approaches, such as image-based or feature-based methods, so choose the one that best suits your application.
4. Configure the visual servoing parameters. This includes setting the gains or weights for the control algorithm, as well as any other specific parameters related to your task.
5. Begin the visual servoing process by acquiring an initial image from the camera. This image will serve as the reference or target image for the servoing system.
6. Continuously capture current images from the camera and compare them to the reference image. Use computer vision techniques to extract the necessary visual features or information that will be used by the control algorithm.
7. Based on the extracted visual features and the desired task, calculate the control commands for the robot arm. These commands will dictate how the arm should move in order to achieve the desired motion or task.
8. Execute the control commands on the robot arm. Monitor the visual feedback in real-time to ensure that the arm is accurately performing the intended task.
9. Iterate the visual servoing process as necessary. Adjust the control parameters or algorithm if the performance is not satisfactory, and continue to refine the system until the desired results are achieved.

Who needs visual servoing of 6:

1. Industrial automation companies that require precise object manipulation or assembly tasks. Visual servoing can be used to guide robots in picking up and placing objects with high accuracy.
2. Researchers in the field of robotics who are developing advanced control algorithms and methods. Visual servoing is a common technique used in robotics research to study vision-based control and perception.
3. Autonomous vehicles or drones that rely on visual feedback for navigation and obstacle avoidance. Visual servoing can be used to track and follow specific objects or paths in real-time.
4. Medical professionals who utilize robotic surgery systems. Visual servoing can assist surgeons in performing delicate and precise procedures by providing visual feedback and control.
5. Augmented reality or virtual reality applications that require real-time tracking and interaction with virtual objects. Visual servoing can be used to accurately track the user's movements and adjust the virtual objects accordingly.

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