SCARA Arm Calibration — Lucas Marques

The Problem

In a cooperative 3D printing swarm, multiple robots share a single build surface. If their positioning isn't perfectly aligned, the final object will have structural flaws. We needed to achieve a positioning accuracy of 200µm (0.2mm) for SCARA robot arms that inherently lack rigid linearity in their kinematic structure.

Animated SCARA arm kinematic movement and error simulation — SCARA arm kinematic simulation.

The Engineering

I designed a mathematical model and a Python-based calibration algorithm to correct kinematic errors. By measuring the joint angles required to reach four specific reference points, the algorithm solves for the exact X-Y variances in the arm’s physical construction. It calculates the discrepancy between the virtual ideal model and the real-world mechanics, adjusting the control variables to zero out the error.

Mathematical formula for SCARA kinematic error minimization — Kinematic Error Model: the mathematical algorithm used to calculate and minimize the variance between the virtual ideal model and real-world mechanics.

Visual breakdown of physical variables defining SCARA arm structure — Visual breakdown of the physical variables defining the SCARA arm's structure. These parameters are the inputs tuned by the calibration algorithm.

The Results

The calibration process improved positioning accuracy by 50 times, successfully hitting the 200µm target. This precision was the key enabler for the swarm platform, allowing multiple robots to print on the same object seamlessly without visible seams or layer shifts.

SCARA arm line traces before calibration showing mechanical error — [BEFORE] Inherent mechanical errors cause the robot to trace curved, inaccurate lines.

SCARA arm grid alignment after calibration showing precise straight lines — [AFTER] The corrected algorithm eliminates these errors, achieving precise grid alignment.

Learn more: https://github.com/lucasgmx/scara-arm-calibration