Uploaded November 2021 | Updated September 2026, 25 minutes ago
ONLINE Lockheed Martin Robotics Seminar: Safety-Critical Control of Dynamic Robots
Aaron D. Ames
Bren Professor
Mechanical and Civil Engineering
Control and Dynamical Systems
California Institute of Technology
Guaranteeing safe behavior is a critical component of translating robots from a laboratory setting to real-world environments in an autonomous fashion. With this as motivation, this talk will present a safety-critical approach to the control of dynamic robotic systems, ranging from legged robots, to multi-robot teams, to robotic assistive devices. To this end, a unified nonlinear control framework for realizing dynamic behaviors will be presented. Underlying this approach is an optimization-based control paradigm leveraging control barrier functions that guarantee safety (represented as forward set invariance). The ability of control Lyapunov functions to stabilize nonlinear systems will be used to motivate these constructions, and the implications on autonomous systems will be considered. Finally, connections with learning in a safety-critical fashion will be discussed. The application of these ideas will be demonstrated experimentally on a wide variety of robotic systems, including: multi-robot systems with guaranteed safe behavior, bipedal and humanoid robots capable of achieving dynamic walking and running behaviors that display the hallmarks of natural human locomotion, and robotic assistive devices (including prostheses and exoskeletons) aimed at restoring mobility.
For more information on the Maryland Robotics Center see:
https://robotics.umd.edu
ONLINE Lockheed Martin Robotics Seminar: Safety-Critical Control of Dynamic Robots
Aaron D. Ames
Bren Professor
Mechanical and Civil Engineering
Control and Dynamical Systems
California Institute of Technology
Guaranteeing safe behavior is a critical component of translating robots from a laboratory setting to real-world environments in an autonomous fashion. With this as motivation, this talk will present a safety-critical approach to the control of dynamic robotic systems, ranging from legged robots, to multi-robot teams, to robotic assistive devices. To this end, a unified nonlinear control framework for realizing dynamic behaviors will be presented. Underlying this approach is an optimization-based control paradigm leveraging control barrier functions that guarantee safety (represented as forward set invariance). The ability of control Lyapunov functions to stabilize nonlinear systems will be used to motivate these constructions, and the implications on autonomous systems will be considered. Finally, connections with learning in a safety-critical fashion will be discussed. The application of these ideas will be demonstrated experimentally on a wide variety of robotic systems, including: multi-robot systems with guaranteed safe behavior, bipedal and humanoid robots capable of achieving dynamic walking and running behaviors that display the hallmarks of natural human locomotion, and robotic assistive devices (including prostheses and exoskeletons) aimed at restoring mobility.
For more information on the Maryland Robotics Center see:
https://robotics.umd.edu
