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Explore cutting-edge robotics research in this 52-minute conference talk that delves into enabling robots to perform complex, long-duration manipulation tasks in real-world environments. Learn about the fundamental challenges robots face when perceiving dynamic scenes, planning over extended timescales, and executing precise movements under uncertainty. Discover innovative methods that combine language-conditioned goal specification with object and articulation-aware representations to tackle open-world robotic tasks. Examine hierarchical policy approaches that integrate task and motion planning with reactive control systems for improved performance. Review compelling experimental results demonstrating reliable robot performance across diverse environments including homes, laboratories, and warehouses, with applications ranging from tidying and assembly to tool use. Understand how these systems incorporate safe recovery behaviors and human-in-the-loop supervision to ensure robust operation. Gain insights from Professor Abhinav Valada of the University of Freiburg's Robot Learning Lab, whose research addresses fundamental problems in perception, state estimation, and decision-making to enable reliable robot operation in complex, open-world settings.
