A motion resolution-based engineering method and tool enabling high-precision robotic systems

Purpose – This paper aims to present a novel method and tool for evaluating the motion resolution of industrial robots, defined as the minimum effective motion increment, to enable behavior-informed design and optimization of high-precision industrial robotic systems. Design/methodology/approach – A high-precision laser interferometer is used to measure the joint motion resolution of a KUKA KR210 R2700 Prime robot, following an improved test procedure derived from the ISO 230 standard and an objective error-based identification method. The resulting joint maps are then used to build a prediction tool, implemented in Python and integrated with RoboDK to propagate joint-level resolution to pose- and direction-dependent end-effector Cartesian resolution estimates across the robot workspace. Findings – Results show that ISO 230 tests can mask intrinsic joint resolution in the micro-step range due to backlash-driven response flattening. The proposed test procedure highlights marked joint-dependent performance, with the first three joints generally exhibiting finer micro-step resolution and more stable step responses than the wrist joints. The Cartesian predictor reproduces measured micro-displacement trends with uncertainty envelopes. Originality/value – The paper provides an objective and repeatable approach that decouples intrinsic resolution from backlash, and introduces an efficient prediction tool for Cartesian resolution estimation, supporting improved system design as well as robot motion planning and compensation for precision manufacturing tasks.