A vision-guided robot (VGR) system is a robot fitted with one or more cameras used as sensors to provide a secondary feedback signal to the robot controller for a more accurate movement to a variable target position. VGR is rapidly transforming production processes by enabling robots to be highly adaptable and more easily implemented, while dramatically reducing the cost and complexity of fixed tooling previously associated with the design and set up of robotic cells, whether for material handling, automated assembly, agricultural applications, life sciences, and more.
In one classic but rather dated example of VGR used for industrial manufacturing, the vision system (camera and software) determines the position of randomly fed products onto a recycling conveyor. The vision system provides the exact location coordinates of the components to the robot, which are spread out randomly beneath the camera's field of view, enabling the robot arm(s) to position the attached end effector (gripper) to the selected component and pick from the conveyor belt. The conveyor may stop under the camera to allow the position of the part to be determined, or if the cycle time is sufficient, it is possible to pick a component without stopping the conveyor using a control scheme that tracks the moving component through the vision software, typically by fitting an encoder to the conveyor, and using this feedback signal to update and synchronize the vision and motion control loops.
Such functionality is now common in the field of vision-guided robotics (VGR). It is a rapidly evolving technology that is proving to be economically advantageous in countries with high manufacturing overheads and skilled labor costs by reducing manual intervention, improving safety, increasing quality, and raising productivity rates, among other benefits.
The expansion of vision-guided robotic systems is part of the broader growth within the machine vision market, which is expected to grow to $17.72 billion by 2028. This growth can be attributed to the increasing demand for automation and precision, as well as the broad adoption of smart technologies across industries.