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Knee arthroplasty requires precise milling of the implant cavity, which can prolong implant life and thus, improve the surgical outcome. Robot knee arthroplasty can significantly increase precision of the milling for the implant cavity. However, robot systems often involve process of registration (matching coordinates of robot, patient, and the image data), which can be one of the major drawbacks. The purpose of this paper is to present a new registration method using a surface data extracted from a 3D laser scanner for registration in robotic arthroplasty. Registration for robotic arthroplasty requires the following steps: 3D reconstruction (3D model) of the distal femur using the bone counters extracted from computed tomography (CT) image sections; surface data extraction using a 3D laser scanner; and matching of the 3D model and the extracted surface data. Bone model mechanism was designed to estimate bone motion and available bone exposure. Surface data extracted using 3D laser scanner was matched with 3D model. ICP matching algorithm was employed to perform the spatial transformation between the 3D model and the surface data extracted using the 3D laser scanner. Four local regions (based on anatomical structure) of distal femur were tested to find RSR (Recommended Scanning Region). Issues regarding the application of 3D laser scanner to robotic knee arthroplasty (TKA) is presented and discussed.