Hierarchy, Abstractions and Geometry (Nicholas Roy, MIT)

Spring 2021: Robotics Colloquium
In the last few years, the ability for robots to understand and operate in the world around them has advanced considerably. Examples include the growing number of self-driving car systems, the considerable work in robot mapping, and the growing interest in home and service robots. However, one limitation is that robots most often reason and plan using very geometric models of the world, such as point features, dense occupancy grids and action cost maps. To be able to plan and reason over long length and timescales, as well as planning more complex missions, robots need to be able to reason about abstract concepts such as landmarks, segmented objects and tasks (among other representations). I will talk about recent work in joint reasoning about semantic representations and physical representations and what these joint representations mean for planning and decision making.

Bio: Nicholas Roy is the Bisplinghoff Professor of Aeronautics & Astronautics and a member of the Computer Science and Artificial Intelligence Laboratory (CSAIL) at the Massachusetts Institute of Technology. He received his B.Sc. in Physics and Cognitive Science and his M.Sc. in Computer Science from McGill University. He received his Ph.D. in Robotics from Carnegie Mellon University. He has made research contributions to planning under uncertainty, machine learning, human-computer interaction and aerial robotics. He is currently the director of the Bridge in MIT's Quest for Intelligence.

This lecture was recorded on April 16, 2021 and is closed captioned.

[andrewbouras]

That was a great presentation with some really helpful graphics, thanks!