How can you calibrate robots for optimal accuracy?

All the algorithms used on any robot leverage sensor parameter in some way or the other. For instance any vision based algorithms leverage the camera's intrinsic parameters (mentioned in article), so it is crucial to provide the right data to the control system to reduce errors and improve performance. Some errors like drift or noise that are inevitable, can also be counterd by leveraging redundant sensors and sensor fusion algorithms. Despite this, alway, as a robotics engineer, you try to reduce errors before accumulating data to increase accuracy and performance.

Calibrating robots is crucial due to sensor inaccuracies, drifts, and noise impacting data quality. Sensors like cameras, lidars, encoders, or IMUs require calibration to determine their behavior and characteristics accurately. This process involves adjusting parameters, such as focal length, distortion, or orientation, to rectify errors in sensor perception. Precise calibration enhances the reliability and accuracy of the data, ensuring optimal performance in robotics applications.

The accuracy of the system can only be known with a precise knowledge of the inaccuracy if the sensors. Calibrating the sensors helps in evaluating the inaccuracy in measurements. Additionally, calibrating the actuators helps in evaluating the repeatability of the operation, thereby providing an opportunity to correct any errors during the operation or at least gaining confidence on the executed output.

In addition to the above steps mentioned in this article, it is also important to consider the following factors when calibrating robots as a whole. Environmental conditions: The robot's environment can affect its performance, so it is important to calibrate the robot in the same environment where it will be used. Robot wear and tear: In my opinion this is most important to consider. Over time, the robot's components will wear and tear, which can affect their accuracy and performance. It is important to calibrate the robot regularly to compensate for these changes. By following these steps and considerations, we can calibrate robots as a whole to achieve high accuracy and performance continuously.

Most importantly, when to calibrate the robot: ? Before teaching any position or user frame, the robot must be calibrated or mastered, some robot brands don't need to be calibrated as they come already calibrated from the factory. If you calibrate after the program is ready, the positions might change and you have to reteach all positions!

Self-calibration, self-calibration, self-calibration. :-) Self-Calibration is a key capability that should be developed for robots, especially those that are to be release to the mass market.

Adding to Vanessa's point, While developing your program, you can leverage the critical fault flags that indicate failures in conditions like abnormal shutdown, overload etc. and trigger a verification sequence that can be used to verify calibration. Like, for robot workcells, a sequence where robot reaches designated points in worspace with sensors. Or for automated testbeds, running the test sequence on master product. It is crucial to think of these points while designing the system itself as accomodating it later may cause integration issues.