Flexible manufacturing demands automation that is both precise and adaptable. However, tasks such as screwdriving are typically automated using costly, rigid robotic cells, making this approach impractical for low-volume, high-mix production. As a scalable solution, mobile manipulators offer a flexible alternative, but achieving the required precision for screwdriving remains challenging due to localization uncertainties. This paper addresses these limitations by presenting a vision-guided mobile robotic manipulation system that performs high-precision screwdriving using only monocular RGB imagery. The proposed pipeline integrates stationary and onboard cameras with perception algorithms for object identification and segmentation, pose estimation, and CAD-based screw hole localization, compensating for base misalignment and object placement variability. Experimental validation using ISO 9283 standard’s metrics demonstrates a translational accuracy between 0.21 mm and 0.50 mm across multiple screw positions. Additionally, the system achieves angular estimation errors as low as 0.07°to 0.20°, verifying its capability for sub-degree precision in orientation estimation. In 50 independent experiments involving a total of 400 screw insertions, the system achieved a 100 % success rate, confirming its reliability in practical conditions. These results confirm the feasibility of using RGB-only vision for precision screwdriving and highlight the mobile manipulation system’s scalability for real-world semi-structured manufacturing environments.
