mlsanityData to 7 Oct 2026

Dynamics-Guided Diffusion Model for Sensor-less Robot Manipulator Design

arXiv 2402.15038 ↗First posted 23 Feb 2024cs.RO cs.AI cs.LGcited by 7

On the map: Diffusion models → Diffusion and flow policies for robotics

Abstract (arXiv)

We present Dynamics-Guided Diffusion Model (DGDM), a data-driven framework for generating task-specific manipulator designs without task-specific training. Given object shapes and task specifications, DGDM generates sensor-less manipulator designs that can blindly manipulate objects towards desired motions and poses using an open-loop parallel motion. This framework 1) flexibly represents manipulation tasks as interaction profiles, 2) represents the design space using a geometric diffusion model, and 3) efficiently searches this design space using the gradients provided by a dynamics network trained without any task information. We evaluate DGDM on various manipulation tasks ranging from shifting/rotating objects to converging objects to a specific pose. Our generated designs outperform optimization-based and unguided diffusion baselines relatively by 31.5% and 45.3% on average success rate. With the ability to generate a new design within 0.8s, DGDM facilitates rapid design iteration and enhances the adoption of data-driven approaches for robot mechanism design. Qualitative results are best viewed on our project website https://dgdm-robot.github.io/.

Key facts. Cited by 7 papers in the map (data through 7 Oct 2026). Placed in Diffusion and flow policies for robotics, one of 14 directions in Diffusion models. Builds on 22 of its 40 references that are in the map. First posted on arXiv 23 Feb 2024.

Builds on

22 of 40 references.

Closest ancestors · 1

Same direction, newest first

  1. 2023DiffuseBot: Breeding Soft Robots With Physics-Augmented Generative Diffusion Models28 Nov

Other references · 21

  1. 2020Denoising Diffusion Probabilistic Modelscited by 20,851
  2. 2015U-Net: Convolutional Networks for Biomedical Image Segmentationcited by 19,604
  3. 2020Denoising Diffusion Implicit Modelscited by 9,655
  4. 2020Score-Based Generative Modeling through Stochastic Differential Equationscited by 8,964
  5. 2021Diffusion Models Beat GANs on Image Synthesiscited by 8,185
  6. 2015Deep Unsupervised Learning using Nonequilibrium Thermodynamicscited by 7,005
  7. 2017PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Spacecited by 4,384
  8. 2021Improved Denoising Diffusion Probabilistic Modelscited by 3,736
  9. 2020Improved Techniques for Training Score-Based Generative Modelscited by 1,036
  10. 2018Benchmarking Neural Network Robustness to Common Corruptions and Surface Variationscited by 99
  11. 2018ChainQueen: A Real-Time Differentiable Physical Simulator for Soft Roboticscited by 98
  12. 2021An End-to-End Differentiable Framework for Contact-Aware Robot Designcited by 53
9 more
  1. 2018Jointly Learning to Construct and Control Agents using Deep Reinforcement Learningcited by 51
  2. 2019Data-efficient Co-Adaptation of Morphology and Behaviour with Deep Reinforcement Learningcited by 34
  3. 2020Hardware as Policy: Mechanical and Computational Co-Optimization using Deep Reinforcement Learningcited by 29
  4. 2020Fit2Form: 3D Generative Model for Robot Gripper Form Designcited by 21
  5. 2021Multi-Objective Graph Heuristic Search for Terrestrial Robot Designcited by 18
  6. 2022GLSO: Grammar-guided Latent Space Optimization for Sample-efficient Robot Design Automationcited by 16
  7. 2022Learning Tool Morphology for Contact-Rich Manipulation Tasks with Differentiable Simulationcited by 9
  8. 2019Certified Graspingcited by 3
  9. 2023Computational Design of Passive Gripperscited by 3

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 1; 2025: 3; 2026: 3.

7 papers.

  1. 2025DynaGuide: Steering Diffusion Polices with Active Dynamic Guidancecited by 39
  2. 2024M2Diffuser: Diffusion-based Trajectory Optimization for Mobile Manipulation in 3D Scenescited by 26
  3. 2025Embodied Co-Design for Rapidly Evolving Agents: Taxonomy, Frontiers, and Challengescited by 4
  4. 2025Designing Tools with Control Confidencecited by 1
  5. 2026Few-Shot Design Optimization by Exploiting Auxiliary Informationcited by 0
  6. 2026STRIDE: Structured Lagrangian and Stochastic Residual Dynamics via Flow Matchingcited by 0
  7. 2026Evolving Dexterous Robots from Scratchcited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2025Diffusion Models for Robotic Manipulation: A Survey
  2. 2024APEX: Ambidextrous Dual-Arm Robotic Manipulation Using Collision-Free Generative Diffusion Models
  3. 2024Learning Diffusion Policies from Demonstrations For Compliant Contact-rich Manipulation
  4. 2025D2PPO: Diffusion Policy Policy Optimization with Dispersive Loss
  5. 2025CoDA: Coordinated Diffusion Noise Optimization for Whole-Body Manipulation of Articulated Objects
  6. 2025DiffusionRL: Efficient Training of Diffusion Policies for Robotic Grasping Using RL-Adapted Large-Scale Datasets
  7. 2024RobotDiffuse: Diffusion-Based Motion Planning for Redundant Manipulators with the ROP Obstacle Avoidance Dataset
  8. 2026PAC-DP: PAC-Bayesian Diffusion Policy Learning