<p>The aerospace industry has been at the forefront of robotic automation over the past decades. Existing robotic manufacturing systems are either constrained by limited workspaces, performing specialized single tasks, or rely on hard-coded operations, reducing their flexibility and autonomy. Collaborative robots (Cobots) offer a promising alternative for executing multiple aerospace machining operations within shared workspaces alongside human operators. Nevertheless, their relatively low stiffness and payload capacity pose challenges in achieving the high precision and accuracy demanded in aerospace machining. To address these limitations, this paper presents a fully autonomous, Cobot system for large-scale aerospace machining tasks. The proposed autonomous system introduces novel end-effector designs, including deburring and painting, each customized to the Cobot’s structural characteristics to ensure high precision during machining. In addition, the framework incorporates intelligent vision-based perception and control algorithms that enable autonomous execution of multiple machining tasks at scale, without external supervision. In addition, the proposed framework presents intelligent vision-based control algorithms for autonomously carrying out multiple machining tasks at scale, without requiring external supervision. The system is validated in rigorous experiments reflecting on industrial settings and testing the proposed system’s autonomy and machining precision. The results demonstrate that the introduced Cobot system meets the aerospace industry standards with a machining standard deviation on the order of 0.01 mm under fully autonomous operation. <a href="https://drive.google.com/file/d/1mNmMHT2_xqwcARedQTcqb2lo8f6b_uYV/view?usp=drive_link">Video Link</a></p>