Fiducial markers, like AprilTag and ArUco, are extensively utilized in robotics applications within industrial environments, encompassing navigation, docking, and object grasping tasks. However, in contrast to controlled laboratory conditions, markers installed in factory grounds or equipment surfaces, often face challenges like damage or contamination. These issues can lead to compromised marker integrity, resulting in reduced detection reliability. To address this challenge, we propose a novel fiducial marker called CopperTag, which incorporates circular and square elements to create a robust occlusion-resistant pattern. The CopperTag detection process relies on three fundamental steps: firstly, extracting all lines from the image; secondly, identifying corners; and lastly, searching for quadrilateral candidate regions using ellipses and nearby corners. The Reed-Solomon (RS) algorithm is utilized for both encoding and decoding the information content. This algorithm possesses the ability to recover corrupted messages in situations where CopperTag data is incomplete. The experimental results illustrate that CopperTag exhibits superior robustness and accuracy in detection when compared to other state-of-the-art fiducial markers, even in scenarios with heavy occlusion. Moreover, CopperTag maintains an average processing time of 10ms per frame on a standard laptop, effectively meeting the real-time demands of robotics applications.