Dexterous robotic manipulation requires more than geometrically valid grasps: it demands physically grounded contact strategies that account for the spatially non-uniform mechanical properties of the object. However, existing grasp planners typically treat the surface as structurally homogeneous, even though contact in a weak region can damage the object despite a geometrically perfect grasp. We present a pipeline for grasp selection and force regulation in a five-fingered robotic hand, based on a map of locally admissible contact loads. From an operator command, the system identifies the target object, reconstructs its 3D geometry using SAM3D, and imports the model into Isaac Sim. A physics-informed geometric analysis then computes a force map that encodes the maximum lateral contact force admissible at each surface location without deformation. Grasp candidates are filtered by geometric validity and task-goal consistency. When multiple candidates are comparable under classical metrics, they are re-ranked using a force-map-aware criterion that favors grasps with contacts in mechanically admissible regions. An impedance controller scales the stiffness of each finger according to the locally admissible force at the contact point, enabling safe and reliable grasp execution. Validation on paper, plastic, and glass cups shows that the proposed approach consistently selects structurally stronger contact regions and keeps grip forces within safe bounds. In this way, the work reframes dexterous manipulation from a purely geometric problem into a physically grounded joint planning problem of grasp selection and grip execution for future humanoid systems.

翻译：灵巧机器人操作不仅需要几何可行的抓取，更要求考虑物体空间非均匀力学特性的物理化接触策略。然而，现有抓取规划器通常将表面视为结构均匀体，即使几何构型完美的抓取，若接触于薄弱区域仍可能损坏物体。本文提出一种基于局部可容许接触载荷图的五指灵巧手抓取选择与力调控流水线。系统通过操作员指令识别目标物体，利用SAM3D重建其三维几何，并导入Isaac Sim仿真环境。基于物理信息的几何分析计算力图，编码每个表面位置可承受的无变形最大横向接触力。抓取候选集通过几何有效性与任务目标一致性筛选。当多个候选在经典度量下表现相当，则采用力感知准则重排序：优先选择接触点位于机械可接受区域的抓取方案。阻抗控制器根据接触点局部可容许力值动态缩放每根手指刚度，实现安全可靠的抓取执行。在纸杯、塑料杯和玻璃杯上的实验验证表明，该方法能一致性地选择结构更强的接触区域，并将抓取力控制在安全范围内。这项研究将灵巧操作从纯几何问题重新定义为面向未来人形系统的抓取选择与握力执行联合物理化规划问题。