ywang077/Trajectory_world_model_dataset

WestWorld Pretraining Dataset

This repository contains the pretraining dataset for WestWorld, a knowledge-encoded scalable trajectory world model for diverse robotic systems.

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Description

WestWorld is designed to address the scalability challenges in trajectory world models for diverse robotic systems. The dataset includes trajectories from 89 complex environments spanning diverse morphologies across both simulation and real-world settings.

The associated model, WestWorld, utilizes a novel system-aware Mixture-of-Experts (Sys-MoE) and incorporates domain knowledge of robot physical structures via structural embeddings to achieve strong zero-shot and few-shot generalization in trajectory prediction and downstream model-based control.

Citation

If you find this dataset useful, please cite the following paper:

@inproceedings{wang2026westworld,
  title={WestWorld: A Knowledge-Encoded Scalable Trajectory World Model for Diverse Robotic Systems},
  author={Wang, Yuchen and Kong, Jiangtao and Wei, Sizhe and Li, Xiaochang and Lin, Haohong and Zhao, Hongjue and Zhou, Tianyi and Gan, Lu and Shao, Huajie},
  booktitle={Forty-third International Conference on Machine Learning},
  year={2026},
  url={https://openreview.net/forum?id=ncRRCG4BfP}
}