Latent Diffeomorphic Co-Design of End-Effectors for Deformable and Fragile Object Manipulation
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Abstract (arXiv)
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.
Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 32 of its 57 references that are in the map. First posted on arXiv 20 Feb 2026.
Builds on
32 of 57 references.
References · 32
- 2023Diffusion Policy: Visuomotor Policy Learning via Action Diffusioncited by 2,730
- 2023Efficient Online Reinforcement Learning with Offline Datacited by 332
- 2019DiffTaichi: Differentiable Programming for Physical Simulationcited by 248
- 2016Thingi10K: A Dataset of 10,000 3D-Printing Modelscited by 182
- 2018Reinforcement Learning for Improving Agent Designcited by 55
- 2021An End-to-End Differentiable Framework for Contact-Aware Robot Designcited by 53
- 2022Evolution Gym: A Large-Scale Benchmark for Evolving Soft Robotscited by 44
- 2022Topology-Preserving Shape Reconstruction and Registration via Neural Diffeomorphic Flowcited by 38
- 2019Neural Graph Evolution: Towards Efficient Automatic Robot Designcited by 34
- 2021Transform2Act: Learning a Transform-and-Control Policy for Efficient Agent Designcited by 34
- 2020Hardware as Policy: Mechanical and Computational Co-Optimization using Deep Reinforcement Learningcited by 29
- 2019Learning Gentle Object Manipulation with Curiosity-Driven Deep Reinforcement Learningcited by 25
20 more
- 2020Emergent Hand Morphology and Control from Optimizing Robust Grasps of Diverse Objectscited by 11
- 2022Meta Reinforcement Learning for Optimal Design of Legged Robotscited by 9
- 2025VLMgineer: Vision Language Models as Robotic Toolsmithscited by 9
- 2023MORPH: Design Co-optimization with Reinforcement Learning via a Differentiable Hardware Model Proxycited by 8
- 2024Text2Robot: Evolutionary Robot Design from Text Descriptionscited by 8
- 2023Learning-based Design and Control for Quadrupedal Robots with Parallel-Elastic Actuatorscited by 7
- 2023Learning to Design and Use Tools for Robotic Manipulationcited by 7
- 2023Hybrid Neural Diffeomorphic Flow for Shape Representation and Generation via Triplanecited by 6
- 2020Force-guided High-precision Grasping Control of Fragile and Deformable Objects using sEMG-based Force Predictioncited by 4
- 2024CageCoOpt: Enhancing Manipulation Robustness through Caging-Guided Morphology and Policy Co-Optimizationcited by 4
- 2025Co-Design of Soft Gripper with Neural Physicscited by 4
- 2025RobotSmith: Generative Robotic Tool Design for Acquisition of Complex Manipulation Skillscited by 4
- 2025House of Dextra: Cross-embodied Co-design for Dexterous Handscited by 4
- 2025Embodied Co-Design for Rapidly Evolving Agents: Taxonomy, Frontiers, and Challengescited by 4
- 2024Structural Optimization of Lightweight Bipedal Robot via SERLcited by 3
- 2025Grasping Deformable Objects via Reinforcement Learning with Cross-Modal Attention to Visuo-Tactile Inputscited by 3
- 2025From Power to Precision: Learning Fine-grained Dexterity for Multi-fingered Robotic Handscited by 2
- 2023HASHI: Highly Adaptable Seafood Handling Instrument for Manipulation in Industrial Settingscited by 1
- 2025Image-to-Force Estimation for Soft Tissue Interaction in Robotic-Assisted Surgery Using Structured Lightcited by 1
- 2025DexFruit: Dexterous Manipulation and Gaussian Splatting Inspection of Fruitcited by 1
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