PARC: Physics-based Augmentation with Reinforcement Learning for Character Controllers

- diffusion model in motion generation
- combine RL in data augmentation

#SIGGRAPH2025 #diffusion #RL

X Overview, Project Website

🧵 Thread • FixupX

Michael Xu (@mxu_cg)

Interested in simulated characters traversing complex terrains?

PARC: Physics-based Augmentation with Reinforcement Learning for Character Controllers

Project page: https://michaelx.io/parc/index.html

with: @YiShi_333, @KangkangYin, and @xbpeng4

@siggraph…

Steerable Scene Generation with Post Training and Inference-Time Search

- use a diffusion-based framework to generate scalable scenes on procedural data
- use a Monte Carlo Tree Search to find physical feasibility and satisfy downstream objective

#arxiv #diffusion #generative

X Overview, Project Website

🧵 Thread • FixupX

0:39

Nicholas Pfaff (@NicholasEPfaff)

Want to scale robot data with simulation, but don’t know how to get large numbers of realistic, diverse, and task-relevant scenes?

Our solution:
➊ Pretrain on broad procedural scene data
➋ Steer generation toward downstream objectives

🌐 https://steerable…

Unified World Models: Coupling Video and Action Diffusion
for Pretraining on Large Robotic Datasets

- combine video and action diffusion in one transformer, can be train from robot trajectories and action-free videos.

- represents a policy, a forward dynamics model, an inverse dynamics model, and a video prediction model in a unified framework.

#RSS2025 #diffusion
X overview, Project Website

🧵 Thread • FixupX

Chuning Zhu (@chuning_zhu)

Scaling imitation learning has been bottlenecked by the need for high-quality robot data, which are expensive to collect. But are we utilizing existing data to the fullest extent? A thread (1/11)