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HOME/PEOPLE/AARON D. AMES
// PERSON

Aaron D. Ames

ROLE PROFESSORMENTIONS 6LAST SEEN SEPTEMBER 25, 2026
// BIO

Aaron D. Ames is the Bren Professor of Mechanical and Civil Engineering, Control and Dynamical Systems, and Aerospace at the California Institute of Technology, where he also serves as director of the Center for Autonomous Systems and Technologies. His research focuses on robotics, nonlinear control, hybrid systems, and cyber-physical systems, with particular emphasis on bipedal robotic locomotion, prosthetic devices, and safety-critical control of autonomous systems. He leads the Advanced Mechanical Bipedal Experimental Robotics (AMBER) Lab, which designs, builds, and tests bipedal robots and prostheses aimed at achieving human-like walking and translating those capabilities to assistive devices.

// RECENT MENTIONS
// SIGNALS
6 SIGNALS
01
product·arXiv Physical AI·SEPTEMBER 25, 2026

“Generate, Track, Improve: Perceptive Multi-Skill Humanoid Locomotion with RL-Fine-Tuned Motion Generators”

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02
mention·arXiv Physical AI·SEPTEMBER 25, 2026

“Ames is a leading figure in control-based humanoid robotics, known for CLF (Control Lyapunov Function) methods”

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03
product·arXiv Physical AI·JULY 30, 2026

“The paper demonstrates that the mathematical safety constraints used to train a robot must be explicitly matched to the quality of the robot's sensors.”

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04
mention·arXiv Physical AI·JULY 30, 2026

“We therefore deploy a lightweight Link-CBF policy zero-shot on the Unitree G1 in the real world, where it tolerates imperfect perception, succeeds on 95% of throws”

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05
mention·arXiv Physical AI·JULY 30, 2026

“usable barrier structure depends on perceptual observability”

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06
mention·arXiv Physical AI·JULY 30, 2026

“We theorize that the Joint-CBF gap comes from perception: the policy is asked to internalize a whole-body barrier that it cannot perceive accurately enough, and it learns worse evasions instead”

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AI-extracted from podcast / newsletter / paper summaries. May contain errors.