<![CDATA[Five-axis machining and robotic machining play a critical role in manufacturing complex-geometry components such as blades/bladisks, impellers, free-form surfaces, and thin-walled parts. Research developments from 2020–2026 reveal a shift from predominantly geometry-based toolpath planning toward integrated frameworks that incorporate machine/robot kinematic constraints, drive limits, singularity avoidance, process stability (e.g., chatter), and feedback-based error compensation. This review synthesizes the literature from multiple sources to construct a taxonomy of contributions, assess methodological trends, and identify top-tier research agendas. The synthesis focuses on: (i) tool orientation and tool center point (TCP) calibration in robotic milling; (ii) smooth and collision-safe tool orientation planning while maintaining favorable performance of rotary axes/joints; (iii) toolpath planning on NURBS/mesh surfaces, including iso-scallop strategies and geodesic mapping; (iv) time-optimal feedrate scheduling under geometry–drive constraints; (v) Jacobian-condition-based singularity avoidance with bounded orientation variation; (vi) control of surface texture/topography quality based on posture ranges; (vii) prediction and optimization of process stability to suppress chatter; and (viii) iterative contour error compensation and vision–CNC integration for real-time adaptation. The review shows that the best performance is achieved when tool orientation, toolpath, and feedrate are optimized coherently (co-optimization), and when surface quality is treated as an explicit constraint rather than merely an output. The review identifies key research gaps, including the need for integrated differentiable/real-time models, operational surface texture quality measurement for industrial systems, and the integration of stability, drive limits, and singularity avoidance in end-to-end planning for practical CNC and robotic machining systems.]]>
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