# Motion Before Action: Diffusing Object Motion as Manipulation Condition

arXiv: https://arxiv.org/abs/2411.09658 · HTML: https://mlsanity.com/paper/2411.09658/

## Key facts

- Cited by 16 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 14 Nov 2024.

## Built on by (most cited first, 16 of 16)

- [CoMo: Learning Continuous Latent Motion from Internet Videos for Scalable Robot Learning](https://mlsanity.com/paper/2505.17006/) (2025)
- [World Guidance: World Modeling in Condition Space for Action Generation](https://mlsanity.com/paper/2602.22010/) (2026)
- [CLAP: Contrastive Latent Action Pretraining for Learning Vision-Language-Action Models from Human Videos](https://mlsanity.com/paper/2601.04061/) (2026)
- [Dense Policy: Bidirectional Autoregressive Learning of Actions](https://mlsanity.com/paper/2503.13217/) (2025)
- [CordViP: Correspondence-based Visuomotor Policy for Dexterous Manipulation in Real-World](https://mlsanity.com/paper/2502.08449/) (2025)
- [Neural Brain: A Neuroscience-inspired Framework for Embodied Agents](https://mlsanity.com/paper/2505.07634/) (2025)
- [Point-It-Out: Benchmarking Embodied Reasoning for Vision Language Models in Multi-Stage Visual Grounding](https://mlsanity.com/paper/2509.25794/) (2025)
- [GenFlowRL: Shaping Rewards with Generative Object-Centric Flow in Visual Reinforcement Learning](https://mlsanity.com/paper/2508.11049/) (2025)
- [3D Flow Diffusion Policy: Visuomotor Policy Learning via Generating Flow in 3D Space](https://mlsanity.com/paper/2509.18676/) (2025)
- [RoboRouter: Training-Free Policy Routing for Robotic Manipulation](https://mlsanity.com/paper/2603.07892/) (2026)
- [Diffusion Model as a Generalist Segmentation Learner](https://mlsanity.com/paper/2604.24575/) (2026)
- [Language-Conditioned Representations and Mixture-of-Experts Policy for Robust Multi-Task Robotic Manipulation](https://mlsanity.com/paper/2510.24055/) (2025)
- [ReSeFlow: Rectifying SE(3)-Equivariant Policy Learning Flows](https://mlsanity.com/paper/2509.22695/) (2025)
- [RoTri-Diff: A Spatial Robot-Object Triadic Interaction-Guided Diffusion Model for Bimanual Manipulation](https://mlsanity.com/paper/2603.07165/) (2026)
- [FocalPolicy: Frequency-Optimized Chunking and Locally Anchored Flow Matching for Coherent Visuomotor Policy](https://mlsanity.com/paper/2605.15944/) (2026)
- [Human2Any: Human-to-Robot Transfer via Constraint-Aware Compositional Planning](https://mlsanity.com/paper/2606.28813/) (2026)

## Abstract (arXiv)

Inferring object motion representations from observations enhances the performance of robotic manipulation tasks. This paper introduces a new paradigm for robot imitation learning that generates action sequences by reasoning about object motion from visual observations. We propose MBA (Motion Before Action), a novel module that employs two cascaded diffusion processes for object motion generation and robot action generation under object motion guidance. MBA first predicts the future pose sequence of the object based on observations, then uses this sequence as a condition to guide robot action generation. Designed as a plug-and-play component, MBA can be flexibly integrated into existing robotic manipulation policies with diffusion action heads. Extensive experiments in both simulated and real-world environments demonstrate that our approach substantially improves the performance of existing policies across a wide range of manipulation tasks. Project page: https://selen-suyue.github.io/MBApage/