363: Voice-Controlled Workflow For Human–robot Collaborative Timber Joinery

Robotic timber construction requires precise calibration of the workpiece to account for natural dimensional variations in timber. These adjustments, traditionally performed via the robot’s interface, interrupt workflow continuity and increase the risk of human error. We present a voice-controlled workflow for hands-free calibration and task execution on a KUKA robot. The system integrates speech recognition APIs into Grasshopper via Python, defining a command structure interpretable by KUKA|prc to safely simulate and visualize toolpaths prior to execution. Beyond calibrating the workpiece, the workflow enables users to program drilling operations via spoken commands. Validation was performed by executing a rectangular hole array on timber, demonstrating the system’s potential to perform repetitive tasks such as drilling holes for joinery pins or placing metallic fasteners for engineered timber connectors. The approach improves human–robot coordination and reduces reliance on the robot’s interface while enhancing workflow continuity, ergonomics, and accessibility for non-experts in robotic fabrication.