Leslie Pack Kaelbling
Intelligent Robots Redux
Wednesday, May 18, 17:50-18:50, Room A3
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 replanning process. I will describe our application of these ideas to an end-to-end mobile manipulation system, as well as ideas for current and future work on improving correctness and efficiency through learning.