UranusroboticspolicyRoboTwinsimulationWorld ModelsCounterfactual TrainingVideo PredictionReinforcement Learning
Robotics
2 related stories
D-Robotics Open-Sources Uranus World Model Simulation Platform, Achieving 0.98 Correlation in RoboTwin Closed-Loop Evaluation
On October 27, the D-Robotics large model team open-sourced the Uranus technical report alongside its inference code, SDK, and model weights, offering 100 early access slots to developers and researchers worldwide.
Institute of Automation, Chinese Academy of Sciences and Amap Introduce DreamTrue, an Action-Faithful Robot World Model for Future Video Prediction
Researchers from the Institute of Automation, Chinese Academy of Sciences and Amap introduce DreamTrue, a robot world model that renders actions as visual conditions to predict both successful and failed outcomes. The method uses counterfactual post-training to address missing failure demonstrations, and the article reports interaction defect rates on AgiBot platforms falling from 48.12% to 6.25%.