In recent years, enormous advancement has taken place in biomedical engineering, which has paved the way for robot-assisted surgery in various complex surgical procedures. In robotic surgery, the reinforcement-based Temporal Difference (TD) based approach through assistive approaches has tremendous potential. Probabilistic Roadmap (PR) can be used for recognition of the path to the region of interest without any obstacles and, Inverse Kinematics (IK) approach can be used for the accurate approximation of the pixel space to the real-time workspace. Our proposed system would be more effective in approximating the path length, depth evaluation, and less invasive contact force sensor. This article presents a robust algorithm that would assist in robotic surgery for censorious surgeries in real-time. For working on such soft tissues, software-driven procedures and algorithms must be more precise in choosing the optimal path for reaching out to the procedural region. The statistical analysis has proven that the proposed approach would be outperforming under favorable learning rate, discount factor, and the exploration factor.

近年来，生物医学工程取得了巨大进步，为机器人辅助手术在各种复杂外科手术中的应用铺平了道路。在机器人手术中，通过辅助方法的基于强化的时间差 (TD) 方法具有巨大的潜力。概率路线图 (PR) 可用于识别没有任何障碍的感兴趣区域的路径，逆运动学 (IK) 方法可用于将像素空间准确逼近实时工作空间。我们提出的系统在近似路径长度、深度评估和侵入性较小的接触力传感器方面会更有效。本文提出了一种强大的算法，该算法将有助于实时进行审查手术的机器人手术。为了在这种软组织上工作，软件驱动的程序和算法在选择到达程序区域的最佳路径时必须更加精确。统计分析证明，所提出的方法在有利的学习率、折扣因子和探索因子下将表现出色。