A Flexible Field-Based Policy Learning Framework for Diverse Robotic Systems and Sensors
On the map: Diffusion models → Diffusion and flow policies for robotics
Abstract (arXiv)
We present a cross robot visuomotor learning framework that integrates diffusion policy based control with 3D semantic scene representations from D3Fields to enable category level generalization in manipulation. Its modular design supports diverse robot camera configurations including UR5 arms with Microsoft Azure Kinect arrays and bimanual manipulators with Intel RealSense sensors through a low latency control stack and intuitive teleoperation. A unified configuration layer enables seamless switching between setups for flexible data collection training and evaluation. In a grasp and lift block task the framework achieved an 80 percent success rate after only 100 demonstration episodes demonstrating robust skill transfer between platforms and sensing modalities. This design paves the way for scalable real world studies in cross robotic generalization.
Key facts. No citing papers in the map yet (data through 7 Oct 2026). Placed in Diffusion and flow policies for robotics, one of 14 directions in Diffusion models. Builds on 19 of its 22 references that are in the map. First posted on arXiv 22 Dec 2025.
Builds on
19 of 22 references.
Closest ancestors · 2
Same direction, newest first
- 2024GenDP: 3D Semantic Fields for Category-Level Generalizable Diffusion Policy23 Oct
- 2023Diffusion Policy: Visuomotor Policy Learning via Action Diffusion7 Mar
Other references · 17
- 2020Denoising Diffusion Probabilistic Modelscited by 20,851
- 2023Segment Anythingcited by 8,158
- 2023DINOv2: Learning Robust Visual Features without Supervisioncited by 7,764
- 2015Deep Unsupervised Learning using Nonequilibrium Thermodynamicscited by 7,005
- 2021Emerging Properties in Self-Supervised Vision Transformerscited by 6,893
- 2017PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Spacecited by 4,384
- 2023Grounding DINO: Marrying DINO with Grounded Pre-Training for Open-Set Object Detectioncited by 3,274
- 2022XMem: Long-Term Video Object Segmentation with an Atkinson-Shiffrin Memory Modelcited by 436
- 2021Neural Descriptor Fields: SE(3)-Equivariant Object Representations for Manipulationcited by 204
- 2023GELLO: A General, Low-Cost, and Intuitive Teleoperation Framework for Robot Manipulatorscited by 180
- 2018Dense Object Nets: Learning Dense Visual Object Descriptors By and For Robotic Manipulationcited by 140
- 2023Distilled Feature Fields Enable Few-Shot Language-Guided Manipulationcited by 130
5 more
- 2023D3Fields: Dynamic 3D Descriptor Fields for Zero-Shot Generalizable Rearrangementcited by 35
- 2025Learning Bimanual Manipulation via Action Chunking and Inter-Arm Coordination with Transformerscited by 8
- 2025Robust Instant Policy: Leveraging Student's t-Regression Model for Robust In-context Imitation Learning of Robot Manipulationcited by 2
- 2024Visual Imitation Learning of Non-Prehensile Manipulation Tasks with Dynamics-Supervised Modelscited by 1
- 2025Attention-Guided Integration of CLIP and SAM for Precise Object Masking in Robotic Manipulationcited by 1
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Close in wording, no citation either way
- 2026CEI: A Unified Interface for Cross-Embodiment Visuomotor Policy Learning in 3D Space
- 2025VO-DP: Semantic-Geometric Adaptive Diffusion Policy for Vision-Only Robotic Manipulation
- 2026Latent Policy Steering: An Efficient and Flexible Framework for Cross-Embodiment Transfer ↗
- 20253D Flow Diffusion Policy: Visuomotor Policy Learning via Generating Flow in 3D Space
- 2026StereoPolicy: Improving Robotic Manipulation Policies via Stereo Perception
- 2025ISS Policy : Scalable Diffusion Policy with Implicit Scene Supervision
- 20243D Diffusion Policy: Generalizable Visuomotor Policy Learning via Simple 3D Representations
- 2025Latent Action Diffusion for Cross-Embodiment Manipulation