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license: apache-2.0 |
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tags: |
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- robotics |
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- diffusion-policy |
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- flow-matching |
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- lerobot |
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- rram |
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--- |
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# FMLP-Policy: Flow Matching MLP for Robotic Control |
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This project explores RRAM-compatible neural network architectures for robotic manipulation policies, replacing UNet with pure MLP (Linear + ReLU only) for deployment on analog RRAM accelerators. |
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## Overview |
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Diffusion Policy achieves SOTA on robotic manipulation but requires 50-100 denoising steps — impractical for RRAM deployment (each step needs ADC/DAC conversion). We explore: |
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1. **Streaming Flow Policy (SFP)** reduces to 1-4 integration steps |
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2. **MLP velocity networks** replaces UNet with RRAM-friendly architecture |
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3. **Quantization + noise tolerance** validates INT8 deployment with device variation |
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## Models |
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| Model | Architecture | Description | |
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|-------|--------------|-------------| |
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| [pusht_diffusion_v3](https://huggingface.co/Liyux/pusht_diffusion_v3) | ResNet18 + UNet | DP baseline, 136 episodes | |
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| [pusht_diffusion_v4](https://huggingface.co/Liyux/pusht_diffusion_v4) | ResNet18 + UNet | DP baseline, 226 episodes | |
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| [pusht_diffusion_v5](https://huggingface.co/Liyux/pusht_diffusion_v5) | ResNet18 + UNet | DP baseline, 255 episodes (best) | |
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| [pusht_sfp_v9](https://huggingface.co/Liyux/pusht_sfp_v9) | ResNet18 + UNet | SFP working baseline | |
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| [pusht_sfp_v14](https://huggingface.co/Liyux/pusht_sfp_v14) | ResNet18 + UNet | SFP with h50/k2/σ1 params | |
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| [pusht_sfp_v15](https://huggingface.co/Liyux/pusht_sfp_v15) | ResNet18 + MLP | SFP with cond_residual MLP (RRAM-compatible) | |
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## Dataset |
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| Dataset | Episodes | Description | |
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|---------|----------|-------------| |
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| [pusht_real_merged](https://huggingface.co/datasets/Liyux/pusht_real_merged) | 255 | Real robot Push-T task, SO-101 arm, 320x240 | |
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## Key Results |
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**Sim (2D Push-T):** |
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- MLP achieves 0.86-0.88 FP32 vs UNet 0.74 |
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- INT8 quantization: Bottleneck128+Skip achieves 0.86 |
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- Noise tolerance: <6% accuracy drop at 10% multiplicative noise |
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**Real Robot:** |
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- DP v5: >90% success rate |
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- SFP v9: >70% success rate |
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- SFP v14/v15: > 80% success rate |
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## Code |
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- [Liyux3/lerobot_MLP-SFP](https://github.com/Liyux3/lerobot_MLP-SFP) |
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## Hardware |
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- Robot: SO-101 (LeRobot compatible) |
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- Camera: HB Camera, top-down, 320x240 @ 30fps |
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- Training: 2x RTX 4090 |
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## Citation |
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Coming soon. |
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## Acknowledgments |
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- [LeRobot](https://github.com/huggingface/lerobot) framework |
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- [Streaming Flow Policy](https://arxiv.org/abs/2505.21851) paper |
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- HKU EEE |
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--- |
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*Part of FYP project at The University of Hong Kong, supervised by Prof. Han Wang.* |
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