Coordinated Manipulation of Hybrid Deformable-Rigid Objects in Constrained Environments

2026-03-13

AI Summary

Manipulating hybrid linear objects composed of both rigid and deformable segments in constrained environments remains challenging. This work proposes a quasi-static optimization–based manipulation planning approach that extends the classical rigid-body kinematic framework to hybrid deformable systems for the first time. By employing a strain-based Cosserat rod model for differentiable deformation representation, the method derives analytical gradients to efficiently solve the inverse statics problem. It enables coordinated dual-arm trajectory optimization and achieves a 33-fold speedup in solving the inverse problem compared to prior approaches. Simulations and physical experiments on a three-segment system demonstrate high accuracy, with average deformation errors of approximately 3 cm—about 5% of the deformable segment’s length—validating the method’s effectiveness and precision.

Technology Category

• Intelligent Robots: Manipulation
• Search and Optimization: Sampling/Simulation-based Search
• Constraint Satisfaction and Optimization: Mixed Discrete/Continuous Optimization

Application Category

• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs
• Systems and Infrastructure for Web, Mobile and WoT: Experiences and lessons learnt from Web-based algorithms and system deployments
• Responsible Web: Human-perceived consequences of algorithmic deployment on the web

Abstract

Coordinated robotic manipulation of deformable linear objects (DLOs), such as ropes and cables, has been widely studied; however, handling hybrid assemblies composed of both deformable and rigid elements in constrained environments remains challenging. This work presents a quasi-static optimization-based manipulation planner that employs a strain-based Cosserat rod model, extending rigid-body formulations to hybrid deformable linear objects (hDLO). The proposed planner exploits the compliance of deformable links to maneuver through constraints while achieving task-space objectives for the object that are unreachable with rigid tools. By leveraging a differentiable model with analytically derived gradients, the method achieves up to a 33x speedup over finite-difference baselines for inverse kinetostatic(IKS) problems. Furthermore, the subsequent trajectory optimization problem, warm-started using the IKS solution, is only practically realizable via analytical derivatives. The proposed algorithm is validated in simulation on various hDLO systems and experimentally on a three-link hDLO manipulated in a constrained environment using a dual-arm robotic system. Experimental results confirm the planner's accuracy, yielding an average deformation error of approximately 3 cm (5% of the deformable link length) between the desired and measured marker positions. Finally, the proposed optimal planner is compared against a sampling-based feasibility planner adapted to the strain-based formulation. The results demonstrate the effectiveness and applicability of the proposed approach for robotic manipulation of hybrid assemblies in constrained environments.

Problem

• hybrid deformable-rigid objects
• constrained environments
• coordinated manipulation
• deformable linear objects
• robotic manipulation

Innovation

• hybrid deformable-rigid manipulation
• Cosserat rod model
• differentiable optimization
• inverse kinetostatics
• constrained environment