Robotic Manipulation Surfaces (RMS) manipulate objects by deforming the surface on which they rest, offering safe, parallel handling of diverse and fragile items. However, existing designs face a fundamental tradeoff: achieving fine control typically demands dense actuator arrays that limit scalability. Modular architectures can extend the workspace, but transferring objects reliably across module boundaries on soft, continuously deformable surfaces remains an open challenge. We present a multi-modular soft manipulation platform that achieves coordinated inter-module object transfer and precise positioning across interconnected fabric-based modules. A hierarchical control framework, combining conflict-free Manhattan-based path planning with directional object passing and a geometric PID controller, achieves sub-centimeter positioning and consistent transfer of heterogeneous objects including fragile items. The platform employs shared-boundary actuation, where adjacent modules share edge actuators, reducing the required count from $4n^2$ to $(n + 1)^2$ for an $n \times n$ grid; a $2\times 2$ prototype covers $1\times 1$ m with only 9 actuators. This scaling comes at a cost: shared actuators mechanically couple neighbouring modules, creating interference during simultaneous manipulation. We systematically characterise this coupling across spatial configurations and propose compensation strategies that reduce passive-object displacement by 59--78\%. Together, these contributions establish a scalable foundation for soft manipulation surfaces in applications such as food processing and logistics.

翻译：机器人操控表面（RMS）通过变形物体所处的表面来操控物体，为多样且易碎物品提供安全、并行的处理方式。然而，现有设计面临一个根本性的权衡：实现精细控制通常需要密集的致动器阵列，这限制了可扩展性。模块化架构可以扩展工作空间，但在柔软、连续变形的表面上可靠地跨模块边界传递物体仍是一个未解决的挑战。我们提出了一种多模块软体操控平台，该平台在基于织物的互连模块间实现了协调的模块间物体传递与精确定位。一个分层控制框架，结合了无冲突的曼哈顿路径规划、定向物体传递以及几何PID控制器，实现了亚厘米级的定位以及对包括易碎物品在内的异质物体的稳定传递。该平台采用共享边界致动方式，相邻模块共享边缘致动器，使得一个 $n \times n$ 网格所需的致动器数量从 $4n^2$ 减少到 $(n + 1)^2$；一个 $2\times 2$ 的原型机仅用9个致动器覆盖了 $1\times 1$ 米的面积。这种扩展性是有代价的：共享的致动器使相邻模块机械耦合，在同时操控时产生干扰。我们系统地描述了这种耦合在不同空间配置下的特性，并提出了补偿策略，将被动物体位移减少了59--78\%。这些贡献共同为软体操控表面在食品加工和物流等应用中的可扩展性奠定了基础。