Traditional approaches to robotic surface machining often rely on a predefined, constant direction and speed of tool motion, regardless of the local characteristics of the workpiece. Such a uniform strategy results in inefficient utilization of the robot's capabilities, particularly when dealing with complex geometries where the kinematic performance can vary significantly across different surface regions. In this study, we present an advanced approach based on surface segmentation of the workpiece into regions, where each region is assigned a locally optimal machining direction and speed, derived from the robot's kinematic capabilities and the geometry of the surface. An improved machining time index was developed, incorporating a penalty for toolpath transitions, along with a new procedure for determining the optimal number of initial segments. This enables a more realistic estimation of the overall process efficiency. Numerical and experimental results confirm that the proposed region-based strategy achieves up to 22% reduction in machining time compared to conventional unidirectional strategies.
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