Visual Servoing

Visual servoing is a robotics control strategy that employs visual feedback from cameras or sensors to guide the motion and control of a robot. It plays a crucial role in tasks requiring precise manipulation, object tracking, and interaction with the environment based on visual information.

Methods and Techniques

• Image-Based Visual Servoing (IBVS) - Utilizes features extracted from images, such as points or lines, to compute control commands for the robot's motion.

• Position-Based Visual Servoing (PBVS) - Directly specifies the desired position of the robot's end-effector or joints in the image space, simplifying control commands.

• 3D Visual Servoing - Integrates depth information to control the three-dimensional position and orientation of the robot's end-effector or camera.

• Hybrid Visual Servoing - Combines different visual servoing approaches, leveraging the strengths of each method to achieve improved performance.

• Visual Servoing with Predictive Control - Incorporates predictive models to anticipate the future motion of the robot or the environment, enhancing real-time control.

• Event-Based Visual Servoing - Utilizes event-based cameras or sensors that capture changes in the visual scene, enabling fast and asynchronous visual feedback.

• Learning-Based Visual Servoing - Incorporates machine learning techniques to improve the performance of visual servoing algorithms through data-driven approaches.

• Multi-Robot Visual Servoing - Extends visual servoing principles to scenarios involving multiple robots, enabling coordinated control for collaborative tasks.