PhD Thesis Defense
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PhD Thesis Defense
Cherie Ho
Flexible Perception for High-Performance Robot Navigation
Abstract: Real-world autonomy requires perception systems that deliver rich, accurate information given the task and environment. However, as robots scale to diverse and rapidly evolving settings, maintaining this level of performance becomes increasingly brittle and labor-intensive, requiring significant human engineering and retraining for even small changes in environment and problem definition. To overcome this bottleneck, […]
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PhD Thesis Defense
Homanga Bharadhwaj
Watch, Predict, Act: Robot Learning meets Web Videos
Abstract: To enable robots to assist in everyday tasks in diverse natural environments such as homes, offices, and kitchens, it is critical to develop policies that generalize to novel tasks in unseen scenarios. Practical utility demands that these policies do not require task-specific adaptation at test time but can instead execute directly given a natural […]