Robots as Tokens: Unified Diffusion Transformer for Coordinated Multi-Robot Trajectory Generation

arXiv:2606.15550 · cs.RO · Submitted 2026-06-14 · Read on arXiv

cs.RO

Submitted: 2026-06-14

Updated: 2026-06-14

Comments: 23 pages, 13 figures; \textbf{Project page:} \href{https://bairuofei.github.io/roken-project-page/}{\texttt{bairuofei.github.io/roken-project-page}}

Journal ref: The Conference on Robot Learning (CoRL) 2026

Code: https://github.com/AprilRobotics/apriltag

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Transformer — 14× in this paper · explained in 2 episodes
• Diffusion Model — 11× in this paper · explained in 8 episodes
• Ablation — 10× in this paper · explained in 1 episode
• Diffusion Models — 9× in this paper · explained in 6 episodes
• Generative Model — 8× in this paper · explained in 2 episodes
• Reinforcement Learning — 7× in this paper · explained in 4 episodes
• Generalizability — 5× in this paper · explained in 6 episodes
• Loss Function — 5× in this paper · explained in 2 episodes
• Embeddings — 4× in this paper · explained in 2 episodes
• Generative Models — 4× in this paper · explained in 2 episodes
• IEEE International Conference on Robotics and Automation — 3× in this paper
• Reward Function — 3× in this paper · explained in 2 episodes
• Clustering — 2× in this paper · explained in 2 episodes
• Core — 2× in this paper · explained in 2 episodes
• Decode — 2× in this paper · explained in 2 episodes
• Generalization — 2× in this paper · explained in 13 episodes
• Iterative Refinement — 2× in this paper · explained in 3 episodes
• Ablation Studies — 1× in this paper · explained in 1 episode
• AdamW Optimizer — 1× in this paper · explained in 1 episode
• Adaptability — 1× in this paper · explained in 1 episode
• Adjacency Matrix — 1× in this paper · explained in 1 episode
• Curse of Dimensionality — 1× in this paper · explained in 6 episodes
• GRPO — 1× in this paper · explained in 6 episodes
• Graph Construction — 1× in this paper · explained in 3 episodes
• Graph Neural Network — 1× in this paper
• Graph Neural Network (GNN) — 1× in this paper · explained in 2 episodes
• Latent Diffusion Model — 1× in this paper · explained in 2 episodes
• Latent Diffusion Models — 1× in this paper · explained in 2 episodes
• Regularization — 1× in this paper · explained in 3 episodes
• Reinforcement Learning (RL) — 1× in this paper · explained in 25 episodes
• Sim-to-Real Gap — 1× in this paper · explained in 6 episodes

Sources

• Stable Video Diffusion: Scaling Latent Video Diffusion Models to Large Datasets
• Wan: Open and Advanced Large-Scale Video Generative Models
• $\pi_0$: A Vision-Language-Action Flow Model for General Robot Control
• ImagiNav: Scalable Embodied Navigation via Generative Visual Prediction and Inverse Dynamics
• Multi-Robot Motion Planning with Diffusion Models
• Simultaneous Multi-Robot Motion Planning with Projected Diffusion Models
• Discrete-Guided Diffusion for Scalable and Safe Multi-Robot Motion Planning
• DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models

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