Robotics and Biology Laboratory

How can we create robots that are truly intelligent and autonomous, not just in the context of some specific and narrow setting but in some broad and general sense? This requires building a truly intelligent embodied system.  It is a formidable challenge both in terms of engineering and science. Autonomous systems capable of intelligent behavior must tightly integrate many capabilities in synergistic ways, challenging our ability to build truly robust systems. At the same time, we still lack a foundational scientific understanding of how to generate versatile, robust, adaptable behavior in general, everyday environments.

Research in the Robotics and Biology Laboratory approaches these challenges in the context of real-world problems, including manipulation, in-hand manipulation, interactive perception, learning from demonstration, co-design of manipulation skills, and system building. We closely collaborate with researchers from psychology and behavioral biology to support them in their quest to understand the behavior of biological agents and in turn learn about these agents and the methods employed. Imported into robotics, both methods and understanding push our ability to build better robots. Still, we are far away from matching human abilities but we have begun laying a conceptual foundation that one day might.

Our approach to the aforementioned challenges in science and engineering is inspired by insights from biological intelligent agents. But we also take advantage of the achievements of synthetic disciplines, of course. We work in a problem-centric manner, not by pushing a particular method.  Instead, we employ whatever method appears most suitable to the problem. We identify general principles and explore their power for intelligent agency. So far, this has been a journey across disciplinary boundaries generally accepted but seldomly questioned. Instead of using general-purpose, generic robotic platforms, we believe that embodiment and control must be considered together; this is generally called co-design. Instead of attributing the responsibility of intelligent behavior exclusively to the robot (or even the "brain") itself, we believe that robustness and generality arises from the interplay of a robot's software and hardware with its environment. As Rod Brooks famously said: "The world is its own best model." And the world can serve in many other ways to augment the ability of machines. We have shown that by considering perception and manipulation as two sides of a single coin, we can produce very robust and general robot behavior; we have termed this Interactive Perception. These are just a few of the insights we believe will ultimately contribute to the foundational principles of generating intelligent behavior. And, after all, that is the goal of robotics.