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：灵巧操作不仅需要几何上有效的抓取构型，更要求考虑物体表面力学特性非均匀分布这一物理事实的接触策略。然而，现有抓取规划器通常将物体表面视为力学均匀结构，即便在几何完美抓取中，弱刚度区域的接触仍可能造成物体损伤。本文提出一种面向五指灵巧手的抓取选择与握力调节流水线，其核心是基于局部许可接触载荷的力图。系统根据操作员指令识别目标物体，利用SAM3D重建三维几何模型并导入Isaac Sim仿真环境。基于物理信息的几何分析可生成力图，编码物体表面各位置在无变形条件下可承受的最大横向接触力。抓取候选集经几何有效性及任务目标一致性过滤后，当经典指标下存在多个等效候选时，采用基于力图的筛选准则进行重排序，优先选择接触点位于机械许可区域的抓取方案。阻抗控制器根据接触点局部许可力值调节各手指刚度，实现安全可靠的抓取执行。在纸杯、塑料杯与玻璃杯上的实验验证表明，该方法能持续选择结构强度更高的接触区域，并将握力控制在安全阈值内。这项工作将灵巧操作从纯几何问题重构为面向未来仿人系统的抓取选择与握紧执行联合规划这一具有物理基础的联合规划问题。