Compute Target Poses
SUMMARY
compute_camera_T_target_list() runs ChArUco detection plus solvePnP per frame with a fixed K, d, producing the camera_T_target_list you can feed into EyeInHandCalibrator.calibrate()'s strict pass-through mode. ChArUco targets only.
The Skill
python
poses = calibrator.compute_camera_T_target_list(
image_list, robot_T_tcp_list, intrinsic_matrix, distortion_coefficients,
)| Skill | Returns | Description |
|---|---|---|
compute_camera_T_target_list(image_list, robot_T_tcp_list, intrinsic_matrix, distortion_coefficients) | AlignedTargetPoses | ChArUco detect + solvePnP per frame with fixed K, d. Drops frames where detection or solvePnP fails, keeping all three returned lists aligned. ChArUco targets only. |
The Code
python
from telekinesis.axon import EyeInHandCalibrator
from telekinesis.axon.targets import CharucoTarget
target = CharucoTarget(squares_x=6, squares_y=9, square_length=0.012, marker_length=0.009)
calibrator = EyeInHandCalibrator(target)
poses = calibrator.compute_camera_T_target_list(
image_list, robot_T_tcp_list, intrinsic_matrix, distortion_coefficients,
)
poses.camera_T_target_list
poses.valid_image_list
poses.valid_robot_T_tcp_list