CPG-Based Manipulation with Multi-Module Origami Robot Surface

2025-02-26

AI Summary

Traditional robotic grasping exhibits limited adaptability when manipulating objects spanning multiple scales (centimeter- to meter-scale), diverse materials, variable stiffnesses, and non-convex geometries. To address this, we propose an adaptive surface manipulation framework based on a central pattern generator (CPG)-driven modular origami robot surface (Ori-Pixel). Our approach uniquely integrates CPG-based motion generation with simulation-driven parameter optimization, co-designing control policies through dynamic physical simulation and hardware prototyping to achieve fixture-free, surface-conforming soft manipulation. This paradigm overcomes intrinsic limitations of rigid grippers in scale, stiffness, and geometric adaptability. Experimental validation spans over ten object categories varying in size, mass, shape, and material; both simulation and physical platforms demonstrate strong robustness and consistent cross-scale manipulation performance. The work establishes a new paradigm for soft and reconfigurable robotic manipulation.

Technology Category

• Intelligent Robots: Manipulation
• Search and Optimization: Sampling/Simulation-based Search
• Computer Vision: Low Level & Physics-based Vision

Application Category

• Responsible Web: Machine-in-the-loop, human agency and autonomy
• Economics, Online Markets and Human Computation: Economic ramifications for generative AI infrastructure and applications
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs

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.

Problem

• Handling diverse object sizes
• Manipulating varying stiffness materials
• Optimizing multi-module robotic manipulation

Innovation

• CPG-based motion generator
• multi-module origami robot
• simulation-based optimization method