Latent Diffeomorphic Co-Design of End-Effectors for Deformable and Fragile Object Manipulation

TL;DR

This paper introduces a novel co-design framework that jointly optimizes end-effector shape and control strategies for manipulating deformable and fragile objects, improving performance in complex tasks like food handling.

Contribution

It presents the first integrated approach combining shape parameterization, stress-aware bi-level optimization, and policy distillation for fragile object manipulation.

Findings

Effective in simulation and real-world food manipulation tasks

Outperforms existing methods in handling deformable objects

Enables zero-shot deployment with policy distillation

Abstract

Manipulating deformable and fragile objects remains a fundamental challenge in robotics due to complex contact dynamics and strict requirements on object integrity. Existing approaches typically optimize either end-effector design or control strategies in isolation, limiting achievable performance. In this work, we present the first co-design framework that jointly optimizes end-effector morphology and manipulation control for deformable and fragile object manipulation. We introduce (1) a latent diffeomorphic shape parameterization enabling expressive yet tractable end-effector geometry optimization, (2) a stress-aware bi-level co-design pipeline coupling morphology and control optimization, and (3) a privileged-to-pointcloud policy distillation scheme for zero-shot real-world deployment. We evaluate our approach on challenging food manipulation tasks, including grasping and pushing jelly and scooping fillets. Simulation and real-world experiments demonstrate the effectiveness of the proposed method.