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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.
NeuralActuator not only predicts actuator dynamics but also enhances sensorless force perception, significantly reducing sim-to-real errors in low-cost robotics.
