Prof. Sertac Karaman

Professor Karaman's primary research interests lie in the broad area of analysis, design, and optimization of provably-correct computationally-efficient planning and control algorithms for safety-critical cyber-physical systems, with a large emphasis on robotics applications. Work usually involves a rigorous theoretical analysis that is tightly coupled with implementation and experimental validation on a variety of robotic platforms.
Over the past four years, Karaman has worked on numerous different projects with topics ranging from motion planning to robust control theory and applications ranging from ground robotics to nano-imaging. Currently, he is very engaged with the rigorous analysis of fundamental properties of sampling-based motion planning algorithms. Karaman is also interested in extending the application domain of these algorithms to novel directions such as motion planning with complex task specifications, differential games, stochastic optimal control, and optimal estimation. Most recently, he has been working on the analysis of high-performance navigation through a randomly-generated cluttered environment, motivated by birds’ flight through a dense forest. 

Anytime sampling-based algorithms for control problems
Anytime sampling-based algorithms with suitable convergence guarantees, such as the RRT*, hold the potential to become a practical solution to many problems in robotics and control theory in a unifying way. http://sertac.scripts.mit.edu/web/?p=502

High-speed navigation in cluttered environments

On one hand, roboticists have long been working on agile robotic vehicles that can quickly navigate through cluttered environments. On the other hand, biologists have been trying to understand how some birds manage to fly through dense forests at amazingly high speeds. For instance, a goshawk can reach speeds up to 40 miles per hour while flying through woodlands, according to a BBC documentary. Motivated by these exciting applications in robotics and biology, we analyze high-speed navigation through clutter from a theoretical standpoint by establishing novel connections with statistical physics.
http://sertac.scripts.mit.edu/web/?p=528