Speaker:Professor Leslie Kaelbling
Seminar Venue:Video Conference Room, COM1-02-13
The fields of AI and robotics have made great improvements in many individual subfields, including in motion planning, symbolic planning, probabilistic reasoning, perception, and learning. Our goal is to develop an integrated approach to solving very large problems that are hopelessly intractable to solve optimally. We make a number of approximations during planning, including serializing subtasks, factoring distributions, and determining stochastic dynamics, but regain robustness and effectiveness through a continuous state-estimation and replacing process. This approach is demonstrated on a PR2 robotic system which integrates perception, estimation, planning and manipulation.
There will be time for interaction with the speaker at the end of the seminar. Light refreshments will be served. Please register at https://goo.gl/ECeGMU