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WorldContact is presented, a contact-centric world model for deformable-object manipulation, constructed from a limited set of high-quality trajectories to generate additional training data efficiently and fine-tune an existing vision-language-action policy and deploy it directly on a real robot.
Automating real-to-sim conversion with vision-language agents could revolutionize how we simulate robotic interactions, making it faster and cheaper than ever before.
BoxTwin enables robots to accurately predict and adapt to the complex dynamics of elastoplastic articulated objects, revolutionizing manipulation in unstructured settings.
NeuralActuator not only predicts actuator dynamics but also enhances sensorless force perception, significantly reducing sim-to-real errors in low-cost robotics.
Thermomechanical dynamics can now be seamlessly integrated into 3D scene rendering, enabling realistic simulations of melting and solidification processes.
