In recent years, robots play an active role in everyday life: medical robots assist in complex surgeries; search-and-rescue robots are employed in mining accidents; and low-cost commercial robots clean houses. There is a growing need for sophisticated algorithmic tools enabling stronger capabilities for these robots. One fundamental problem that robotic researchers grapple with is motion planning—which deals with planning a collision-free path for a moving system in an environment cluttered with obstacles.
To a layman, it may seem the wide use of robots in modern life implies that the motion-planning problem has already been solved. This is far from true. There is little to no autonomy in surgical robots and every owner of a house-cleaning robot has experienced the highly simplistic (and often puzzling) routes taken by the robot.
The Computational Robotics Lab is a center for foundational research on the computational challenges that arise when planning for robots. We focus primarily on complex robotic systems such as those that arise in medical applications and warehouse domains. For such settings, we analyze the domain-specific computational challenges and, subsequently develop algorithms to address these challenges to provide the robotics community foundational tools to solve real-world problems.