CPG-Based Manipulation with Multi-Module Origami Robot Surface

TL;DR

This work tackles the challenge of manipulating objects across a wide range of sizes and stiffness using a surface-based multi-module origami robot surface, Ori-Pixel. It presents a CPG-based motion generator coupled with a simulation-based optimization framework to reduce control complexity from 75 actuators to a small set of parameters, enabling coordinated translation and rotation of objects from centimeters to meters. Dynamic simulations in MuJoCo and prototype experiments on a 5×5 Ori-Pixel array validate robust manipulation of diverse objects, with fast and smooth operation modes tailored to application needs. The study demonstrates sim-to-real transfer with high fidelity and outlines practical robustness and limitations, laying the groundwork for scalable, programmable origami-surface manipulation in soft-robotic platforms.

Abstract

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.

Figures (6)

• Figure 1: Conceptual overview. (a) Conceptual illustration of the proposed 3-DoF CPG-based manipulation framework using a multi-module origami robot surface; (b) experiments demonstrating the system's versatility for manipulating various objects: (i) 300$\times$300 mm acrylic plate, (ii) 200$\times$200 mm wood plate, (iii) 300$\times$300 mm acrylic plate with a slender foam cylinder loosely positioned on top, (iv) 1000$\times$300 mm acrylic plate weighing 1 kg, (v) 400$\times$400 mm Polo shirt weighing 280 g, and (vi) 250$\times$270 mm Trilby hat weighing 55 g.
• Figure 2: Kinematic model, workspace, and simulation setups. (a) Kinematic model of the Canfield origami structure; (b) non-monotonic behavior of end-effector's workspace from lower to higher Z-height configurations, first expanding then contracting; (c) single module model for simulation; (d) simulation contact model; (e) 5$\times$5 multi-module model for simulation.
• Figure 3: Single-module CPG motion plan and inter-group motion plan. (a) Single module motion plan; (b) multi-module manipulation motion plan. (c) inter-group motion planning for translation manipulations; (d) motion planning for clock-wise rotation manipulation.
• Figure 4: Control and Optimization Frameworks. (a) Control framework for CPG-based manipulation; (b) optimization framework for CPG parameters.
• Figure 5: Experimental validation. (a) Comparison of simulated and prototype object motions for translational and rotational manipulations; (b) lab test setup.