Robotic Planning with Limited Sensing

GRAND Seminar May 4, 11 am, Friday, 2012, ENGR 4201

Jason O'Kane
Assistant Professor
Department of Computer Science and Engineering
University of South Carolina

Host:

Jyh-Ming Lien

Abstract:

The usefulness of a mobile robot is limited by its ability to sense and interact with its environment. However, because information from sensors is limited and sometimes unreliable, robots are often confronted with substantial and difficult-to-resolve uncertainty about the state of the world. This talk will present two lines of research that make progress toward autonomy in spite of such uncertainty. First, I will describe new methods for localization and navigation that allow mobile robots with limited sensing capabilities and noisy actuators to move through their environments in provably reliable ways. Second, I will discuss target tracking applications in which a robot or team of robots seeks to locate and follow moving targets, under several different sensing and motion constraints. The overall theme is that many important tasks in robotics require surprisingly little sensing.

Short Bio:

Jason O'Kane is an Assistant Professor in the Department of Computer Science and Engineering at the University of South Carolina. He earned Ph.D. (2007) and M.S. (2005) degrees from the University of Illinois and the B.S. (2001) degree from Taylor University, all in Computer Science. He received an NSF CAREER award in 2010, and is a member of the DARPA Computer Science Study Panel. His research spans algorithmic robotics, planning under uncertainty, and computational geometry.