Resolving disorientation of the surgeon caused by wrong recognition of scope's position, which often increases procedural time and workload, remains a significant challenge in robotic-assisted retrograde intrarenal surgery (RIRS). This paper introduces a novel hybrid ureteroscope tracking algorithm that integrates low-latency lumen identification with robotic motion data to enhance intrarenal navigation. The system estimates the ureteroscope's position on the centerline of the kidney by recognizing its pathway. In validation tests using a 3D-printed phantom, the proposed method achieved an average localization success rate of 89.2% for major calyx entry and 84.1% for minor calyx entry, with an average computation time of 0.26 seconds, ensuring low-latency operation. Usability testing with ten novice participants demonstrated a 44.5% reduction in cognitive workload (NASA-TLX), improved task success rates, and reduced manipulation effort. These results indicate that the proposed tracking algorithm significantly enhances ureteroscope navigation, improving efficiency and reducing the surgeon's cognitive load in robotic-assisted RIRS.