Perception, Localization & Planning

Perception turns measurements into estimates of objects, obstacles, pose, state, or intent. Planning turns state and goals into actions. Both operate under uncertainty.

Calibrate the geometry

A vision-guided robot needs camera intrinsics, distortion, camera-to-robot transform, tool center point, and part or fixture frame. Calibration residuals should be checked across the working volume. A small image error can become a large depth or pose error depending on geometry.

Estimate, do not pretend to know

Localization combines motion prediction with measurements. An estimator should carry uncertainty or at least quality indicators. Wheel slip, reflective surfaces, occlusion, lighting changes, vibration, and moving fixtures violate assumptions. Define conditions under which the estimate is invalid.

Planning layers

• task planning chooses actions and order;
• path planning chooses collision-free geometry;
• trajectory generation adds time and dynamic limits;
• control executes while monitoring deviation.

A plan must model robot links, tool, payload, fixtures, cable or hose constraints, stopping behavior, and any shared-space rules. “Collision-free points” are not enough if motion between them is unchecked.

Close the evidence loop

After acting, verify the expected state: part acquired, fixture clear, pose within tolerance, insertion complete, downstream ready. Open-loop assumption chains make a single missed detection propagate into damage.

Perception test set

Create a matrix over lighting, part color, orientation, occlusion, background, camera contamination, vibration, and incorrect parts. Record false positive, false negative, pose error, latency, and confidence. Reserve cases for final evaluation rather than tuning on every example.