Robotic manipulators often face challenges in handling objects of different sizes and materials, limiting their effectiveness in practical applications. This issue is particularly pronounced when manipulating meter-scale objects or those with varying stiffness, as traditional gripping techniques and strategies frequently prove inadequate. In this letter, we introduce a novel surface-based multi-module robotic manipulation framework that utilizes a Central Pattern Generator (CPG)-based motion generator, combined with a simulation-based optimization method to determine the optimal manipulation parameters for a multi-module origami robotic surface (Ori-Pixel). This approach allows for the manipulation of objects ranging from centimeters to meters in size, with varying stiffness and shape. The optimized CPG parameters are tested through both dynamic simulations and a series of prototype experiments involving a wide range of objects differing in size, weight, shape, and material, demonstrating robust manipulation capabilities.

翻译：机器人操纵器在处理不同尺寸和材料的物体时常常面临挑战，这限制了其在实际应用中的有效性。当操控米级物体或具有不同刚度的物体时，这一问题尤为突出，因为传统的抓取技术和策略常常显得不足。本文提出了一种新颖的基于表面的多模块机器人操控框架，该框架利用基于中枢模式发生器（CPG）的运动生成器，并结合基于仿真的优化方法，以确定多模块折纸机器人表面（Ori-Pixel）的最佳操控参数。该方法能够操控尺寸从厘米到米级、具有不同刚度和形状的物体。通过动态仿真和一系列涉及不同尺寸、重量、形状和材料的物体的原型实验，对优化后的CPG参数进行了测试，结果展示了其鲁棒的操控能力。