WEBINAR: Visual Robot Learning for Planning & Control in Unknown Environments

Autonomous robots will soon play a significant role in various domains, such as search-and-rescue, agriculture farms, homes, offices, transportation, and medical surgery, where fast, safe, and optimal response to different situations will be critical. However, to do so, these robots need fast algorithms to plan their task and motion sequences in real-time with limited perception and battery life. This talk will discuss the novel, learning-based methods for scalable robot task and motion planning that emerged from the cross-fertilization of classical planning and machine learning techniques. These methods can achieve unprecedented speed, robustness, and generalization for solving complex problems in cluttered and partially observable environments. Speaker(s): Ahmed H. Qureshi, Room: 4142, Bldg: Engineering Building III, 1840 Entrepreneur Drive, Raleigh, North Carolina, United States, 27606, Virtual: https://events.vtools.ieee.org/m/306026