TALK    [MERL Seminar Series 2026] Zac Manchester presents talk titled Is locomotion really that hard… and other musings on the virtues of simplicity

Date & Time:

Tuesday, January 20, 2026; 12:00 PM

Abstract:

For decades, legged locomotion was a challenging research topic in robotics. In the last few years, however, both model-based and reinforcement-learning approaches have not only demonstrated impressive performance in laboratory settings, but are now regularly deployed "in the wild." One surprising feature of these successful controllers is how simple they can be. Meanwhile, Art Bryson’s timeless advice to control engineers, “Be wise – linearize,” seems to be increasingly falling out of fashion and at risk of being forgotten by the next generation of practitioners. This talk will discuss several recent works from my group that try to push the limits of how simple locomotion (and, possibly, manipulation) controllers for general-purpose robots can be from several different viewpoints, while also making connections to state-of-the-art generative AI methods like diffusion policies.

Speaker:

Zac Manchester
MIT

Zac Manchester is an Associate Professor of Aeronautics and Astronautics at MIT. He holds a Ph.D. in aerospace engineering and a B.S. in applied physics from Cornell University. Zac was a postdoc in the Agile Robotics Lab at Harvard and previously worked at Stanford, NASA Ames Research Center and Analytical Graphics, Inc. He received a NASA Early Career Faculty Award in 2018, a Google Faculty Research Award in 2020, an NSF CAREER Award in 2025, and has led four satellite missions. His research interests include motion planning, control, and numerical optimization, particularly with application to robotic locomotion and spacecraft guidance, navigation, and control.

MERL Host:

Pedro Miraldo

Research Areas:

Computer Vision, Control, Optimization, Robotics