Hybrid motion–measurement control and traceable HMI for a 3-PSP manipulator

Abstract

Purpose This study aims to present and validate a hybrid motion–measurement control architecture and a traceability-oriented human–machine interface (HMI) for a three-DOF 3-prismatic–spherical–prismatic (3-PSP) parallel manipulator configured as a micro-coordinate measuring machine (CMM), improving stability, reproducibility and metrological traceability. Design/methodology/approach Control software integrates LabVIEW with embedded Python for forward/inverse kinematics model. Closed-loop iterative positioning reconciles IKM setpoints with DKM estimates prior to contact; a stop-on-trigger routine then captures coordinates without disturbing contact. Real-time laser-sensor fusion provides pose estimation; deterministic logging records setpoints, sensor snapshots, triggers and operator actions. Performance is benchmarked against a calibrated industrial CMM on a 25-point data set. Findings Mean 3D error is sub-millimetre (≈0.66 mm) with sub-micrometre repeatability under controlled approaches. Bland–Altman analysis shows a small bias (0.317 mm) and negligible proportional bias. Absolute accuracy is mainly limited by geometric calibration and workspace sensitivity; the hybrid logic yields stable convergence and consistent capture. Research limitations/implications Tests cover a translational 3-DOF platform in lab conditions without thermal compensation or geometric error maps. Practical implications The modular LabVIEW–Python framework and traceability-first logging are readily transferable to other PKM/CMM platforms, aiding ISO-aligned auditability and lowering integration cost for SMEs. Originality/value This study provides a software-centric, validated template that couples deterministic hybrid control with comprehensive provenance to enhance reproducibility in PKM-based micro-metrology.