Research Highlight: Enabling Robot Interaction With Articulated Objects

Research from Carnegie Mellon University's Robotics Institute could one day allow robots to seamlessly open drawers, doors and lids on hinges. While humans interact with various articulated objects daily -- opening a refrigerator door or lifting a toilet seat are good examples -- these tasks present a challenge in robotics. Ben Eisner and Harry Zhang, both graduate students in Assistant Professor David Held's Robots Perceiving and Doing Lab, designed a new way to train robots to perceive and manipulate articulated objects in their project, "FlowBot3D: Learning 3D Articulation Flow To Manipulate Articulated Objects." The team presented their research at Robotics: Science and Systems this year, where it was a finalist for a best paper award. FlowBot3D uses a vision-based system to help robots learn how to interact with many different kinds of articulated objects.