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The University of Texas at Austin
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A4D redefines robot interaction by enabling planning based on what objects can do, not just how they look, achieving unprecedented accuracy and speed in novel scenarios.
Achieve reliable UGV deployment in hidden spaces using only RGB data by enforcing consistency between predicted camera motion and onboard platform egomotion to recover metric scale.
Achieve 75% task success in computer-use agents by explicitly modeling and reusing user intent, outperforming standard RL and trajectory-based approaches.
