A unified architecture and control framework for safe and collaborative human-robot manipulation of deformable objects

Abstract

May2025School of EngineeringDeformable object manipulation (DOM) is pervasive in daily life and in industrial settings. Tasks such as cable routing, tent manufacturing, pouring granular material from bags, and laying up composite sheets all involve objects with high internal degrees of freedom, making them notoriously difficult to model and control. This dissertation focuses on enabling multiple mobile robots, in collaboration with human operators, to perform DOM in various scenarios—ranging from 1D ropes and cables to 2D fabric and composite sheets—while ensuring safety, efficiency, and ease of use. A central challenge in DOM is obtaining accurate state estimates from sensors that are frequently subject to occlusions and limited feedback. To address this, we employ position-based dynamics for real-time simulation of object motion, contact, and friction, providing critical data such as predicted object shape, stress, and proximity to obstacles. This simulation underlies a suite of controllers. First, we incorporate control barrier functions to ensure the robots adapt their motion and maintain safe distances from obstacles and prevent overstretching of the deformable objects. Second, we develop an efficient global planning pipeline to manipulate deformable linear objects in cluttered environments, approximating them as serially connected rigid links. Third, we introduce a local control framework for 2D composite layup, where robots transport and position large fabric sheets collaboratively with a human operator. The same simulation reports tensions and contact forces to avoid overstress and prevent unsticking of the material from curved surfaces. We validate the developed architecture and algorithms in simulation and with physical robots under different modes of shared autonomy: human teleoperation, human-robot collaborative manipulation, and fully autonomous control with human guidance. Demonstrations include robotic rope and stiff rod navigation through obstacles, multi-robot formation in tent manufacturing, and real-time composite layup assistance. The system features a unifying touchscreen user interface that simplifies multi-robot programming and visualization, promoting seamless scalability across tasks and facilitating broader industrial adoption. Ultimately, this work advances DOM toward a robust, user-friendly framework, paving the way for safe and versatile human–robot collaboration on a wide range of deformable objects.Ph