Tariq Iqbal, MIT
11/13/18
Abstract: As autonomous robots are becoming more prominent across various domains, they will be expected to interact and work with people in teams. If a robot has an understanding of the underlying dynamics of a group, then it can recognize, anticipate, and adapt to the human motion to be a more effective teammate. In this talk, I will present algorithms to measure the degree of coordination in groups and approaches to extend these understandings by a robot to enable fluent collaboration with people. I will first describe a non-linear method to measure group coordination, which takes multiple types of discrete, task-level events into consideration. Building on this method, I will then present two anticipation algorithms to predict the timings of future actions in teams. Finally, I will describe a fast online activity segmentation algorithm which enables fluent human-robot collaboration.
Bio: Tariq Iqbal is a postdoctoral associate in the Interactive Robotics Group at MIT. He received his Ph.D. from the University of California San Diego, where he was a member of the Contextual Robotics Institute and the Healthcare Robotics Lab. His research focuses on developing algorithms for robots to solve problems in complex human environments, by enabling them to perceive, anticipate, adapt, and collaborate with people.