Surgical navigation involves transferring preoperative imaging data, along with preplanned information, onto the patient in the operating theater without using constant radiation. This technique has proven effective and is widely adopted across various surgical specialties. Research has shown a consistent trend in surgical robotics, with numerous initiatives using this technology to navigate the robot’s end-effector within the patient’s anatomy. For this purpose, commercially available surgical navigation systems are often employed. However, these systems, which are primarily dominated by optical tracking, are not necessarily suited for robotic systems and exhibit limitations such as low update frequency and line-of-sight issues. Additionally, performance reporting in current surgical robotic research is highly inconsistent, and clear guidelines are lacking. This research aims to develop a surgical robotic navigation system to work towards establishing a performance benchmark and systematically assess various error components as a first step toward guiding the field of surgical robotic navigation. To this end, two systems, the Haply System and the Dual-Robot System, have been developed and evaluated for technical accuracy and registration accuracy in both static and dynamic environments. Furthermore, sensor fusion methods have been explored to enhance performance in the Haply system. The results and analysis indicate that the Dual-Robot System is the most accurate in dynamic navigation and presents a viable alternative to optical tracking systems in terms of performance. However, its clinical adoptability remains questionable.