This guest talk was given Dec. 11, 2017 as part of the Intelligent & Interactive Systems Talk Series at Indiana University.
Abstract: In industries as varied as mining, agriculture, health care, and automated driving, many practical applications in robotics involve interacting with intelligent agents while navigating dynamic environments. While impressive results have been demonstrated in these domains, there are still basic types of interacting navigation problems for which robust and general solutions have remained elusive. One such problem type is efficient navigation in the presence of non-cooperative and non-adversarial agents. This is the kind of problem pedestrians face when navigating crowded sidewalks or drivers face when navigating crowded roadways. Two primary reasons for difficulties addressing this problem are that the problem models used tend to exhibit prohibitive computational complexity and the problem formulations tend to have difficult-to-satisfy requirements for problem input and representations. This talk will present recent work that provides more efficient problem models for this problem, as well as new, vision-based problem formulations that seek to significantly simplify problem input and representation requirements.