فعالیت‌های پژوهشی

Since the past few decades, human trajectory forecasting has been a field of active research owing to its numerous real-world applications: evacuation situation analysis, deployment of intelligent transport systems, traffic operations, to name a few. We can cast the problem of human trajectory forecasting as learning a representation of human social interactions. However, social interactions in crowded environments are not only diverse but often subtle.

Multi-agent motion planning has recently attracted much interest in the research community and has many applications including robot navigation among pedestrians, self-driving cars, and drone shows. This problem: 1) concerns finding a one-to-one assignment between a set of given agents’ initial locations and the corresponding destination locations and 2) finding the continuous trajectories connecting each agent’s initial position to its goal location.