Process

Calibration

You might say: sensor calibration

Calibration estimates sensor parameters and relative poses so measurements agree with a robot and object frame.

What it does
It removes systematic camera and sensor errors and makes multi-sensor data geometrically consistent.
Ask
Which parameters are being estimated, with what motions or target, and what residual error remains?
Trouble
A poor target, wrong dimensions, weak pose coverage or stale extrinsic transform makes point clouds misalign and tool placement miss.

What to look for

  1. Known target and robot motions
  2. Point clouds lining up
  3. Tool placement missing from stale calibration

Parts

Catalogue: Calibration

Connections

Sources

  1. OpenCV, Camera Calibration, Intrinsic/extrinsic calibration and chessboard procedureTo find all these parameters, what we have to do is to provide some sample images of a well defined pattern (eg, chess board).
  2. MoveIt, Hand-Eye Calibration, Collect DatasetEach sample in our calibration dataset, then, comprises a pair of poses: the end-effector's pose in the robot base frame paired with the calibration target's pose in the camera frame.
  3. Peter Corke, Robotics, Vision and Control, Ch. 11 §11.2, Camera calibrationSection 11.2 introduces the topic of camera calibration, the estimation of the parameters of the perspective transformation.

Use it on your project

teardown-apply: hold "Calibration" (calibration) from the teardown at https://teardownatlas.com/robotics/ against my project

Paste it into a coding agent that has the teardown skills.

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