Honing household helpers

Imagine a robot able to retrieve a pile of laundry from the back of a cluttered closet, deliver it to a washing machine, start the cycle and then zip off to the kitchen to start preparing dinner. This may have been a domestic dream a half-century ago, when the fields of robotics and artificial intelligence first captured public imagination. However, it quickly became clear that even "simple" human actions are extremely difficult to replicate in robots. Now, MIT computer scientists are tackling the problem with a hierarchical, progressive algorithm that has the potential to greatly reduce the computational cost associated with performing complex actions. Leslie Kaelbling, the Panasonic Professor of Computer Science and Engineering, and Tomás Lozano-Pérez, the School of Engineering Professor of Teaching Excellence and co-director of MIT's Center for Robotics, outline their approach in a paper titled "Hierarchical Task and Motion Planning in the Now," which they presented at the IEEE Conference on Robotics and Automation earlier this month in Shanghai.