Here's how it works. The robot executes a motion by traveling a specified incremental distance. As the motion progresses, the system continuously takes pictures, updating the motion command with every image. Since the motion continues until the vision system confirms that the target has been reached, it doesn't matter if the robot is unable to move exactly to each requested position. The visual servoing loop adjusts for any differences. Thus, as long as the resolution of the camera capturing the images is as good as (or better than) the resolution of the robot's encoders, the system can achieve placement accuracies equal to the encoder resolution. Visual servoing also confirms that motions are properly executed before advancing to the next step.

End effectors made easy

Visual servoing automatically compensates for inaccurate grippers such as vacuum end effectors, so parts can be gripped in a range of positions and the vision system will adjust.

Because traditional vision-guidance systems only observe target locations, and not parts as they are seized, it falls to the robot to capture parts in an identical manner. This is almost impossible with low-cost end effectors, such as vacuum grippers. That's why traditional systems must rely on expensive or custom grippers to reliably clasp parts.

In contrast, visual servoing systems track instantaneous relative position, so parts can be gripped in a range of positions or orientations. This is particularly useful where parts and targets change in real time, such as during the insertion of sutures into suture-needle holes. As a part or target changes position, the vision system detects the variation and adjusts accordingly.

Variation in camera position

Traditional vision guidance requires an accurate calibration between its field of view and its robot's coordinates. If the camera is mounted on a stand, the stand is susceptible to the same thermal expansion and age inaccuracies as a robotic mechanism. Likewise, even on-robot mounts can vary over time.

With visual servoing, as long as the relationship between pixels and real distance stays relatively constant, small disturbances in camera mounting do not affect system accuracy. Visual servoing provides dynamically adaptive calibration, so the need to recalibrate is minimized.

Lens and lighting

Visual servoing requires that both the target location and the part in the end effector are viewed simultaneously. Because these two objects are often in different Z planes, the choices of lens and lighting are very important. A lens with a large depth of field is useful, but it's also necessary to choose a focal distance that either fully views the part, the target, or an area between the two. In any case, setups in which one or both objects go slightly out of focus necessitate vision software with an extensive toolkit.

Cycle time critical

The cycle time from image capture to robot motion is critical. A tightly integrated robot, controller, and vision software system maximizes visual servoing benefits.

The cycle time from image capture to robot motion is critical. Because systems must process multiple images for every assembly operation, they should be able to successfully complete an image-processing-to-robot-motion cycle in less than 100 ms. Faster processors and improved vision algorithms make these speeds possible. With a fully integrated system, communication delays are as low as 2 ms and (with efficient messaging) as many as 17 frames/sec can be processed. On the other hand, a visual servoing system created with mixed-and-matched components typically suffers from vision-to-motion-system communication delays of about 50 ms. These delays added to processing and motion time reduce throughput to 5 to 10 frames/sec.

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