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.

翻译：可变形与易碎物体的操作因其复杂的接触动力学特性及对物体完整性的严格要求，始终是机器人学领域的核心挑战。现有方法通常孤立地优化末端执行器设计或控制策略，限制了可实现的性能边界。本研究首次提出一个协同设计框架，针对可变形与易碎物体的操作任务，联合优化末端执行器形态学结构与操作控制策略。我们引入：(1) 一种隐式微分同胚形状参数化方法，实现高表现力且可处理的末端执行器几何优化；(2) 融合形态学与控制优化的应力感知双层协同设计流程；(3) 基于特权信息到点云策略蒸馏的零样本现实世界部署方案。我们在具有挑战性的食品操作任务上评估所提方法，包括果冻抓取与推挤、鱼片舀取等任务。仿真与真实世界实验验证了该方法的有效性。