前交叉韧带（ACL）损伤是一种常见的运动损伤，关节镜下ACL重建术（ACLR）是现今ACL损伤的标准手术方式，手术成功与否很大程度上取决于骨隧道精度，技术失误是ACL重建失败的最主要原因。为此，机器人辅助手术（RAS）作为一种新兴技术应运而生，旨在提高手术准确性及可重复性，减少人为失误。本综述对机器人辅助ACLR的现状、现阶段存在问题及未来研究方向进行阐述。但目前研究证实了已有的临床研究结果存在着核心的“精准-结局”悖论：从尸体研究到临床研究均表明机器人系统在建立骨隧道的精准度远高于常规徒手方法，但这一精准优势却不能使患者获得更好的临床结果或中、长期的膝关节稳定性随访结果。这涉及多方面原因，包括移植物生物学上的修复、术后的康复状况、个体差异及评估工具本身敏感性不足等，这些因素在最终疗效中发挥的作用可能比微小的精度提升更为关键。而机器人技术的长期应用还面临着高昂的机器设备成本、更长的手术时间及缺乏触觉反馈等现实问题。展望未来，机器人辅助ACLR的发展方向将会由单纯追求精准的工具发展为一个“更加聪明”的临床伙伴，未来结合人工智能（AI）、增强现实（AR）及术后处理在内构成的全流程管理，以填补技术精准和临床疗效之间的差异，为患者带来更好的临床结局。

Anterior Cruciate Ligament (ACL) injury is a common sports-related injury. Although arthroscopic ACL reconstruction (ACLR) is the standard treatment, the success of the surgery is highly dependent on the precise placement of bone tunnels, with technical errors being one of the primary causes of surgical failure. To address the precision challenges of traditional surgery, robot-assisted surgery has been introduced into clinical practice as an emerging technology, aiming to reduce human error by enhancing operational accuracy and reproducibility. This review elaborated on the current status, existing problems and future research directions of robot-assisted ACLR. Current research reveals a core "precision-outcome" paradox: although studies ranging from cadaveric models to multicenter clinical trials have consistently confirmed that robotic systems achieve significantly higher precision in bone tunnel creation than traditional manual methods, this technical advantage has not translated into superior clinical functional outcomes or knee stability for patients in short- to mid-term follow-up. This phenomenon may stem from the combined influence of multiple factors, including the biological healing of the graft, the quality of postoperative rehabilitation, patient-specific variables, and the insensitivity of existing clinical assessment tools. These factors may play a more critical role in determining the final outcome than marginal improvements in precision. Furthermore, the widespread adoption of robotic technology is still hindered by practical issues such as high equipment costs, longer surgical times, and a lack of haptic feedback. Looking ahead, the future direction for robot-assisted ACLR is to evolve from a tool merely pursuing precision into a "smarter" clinical partner. Through the deep integration of artificial intelligence (AI), augmented reality (AR), and comprehensive management of the entire process including postoperative rehabilitation, it may ultimately bridge the gap between technical precision and clinical efficacy, delivering long-term, tangible benefits to patients.