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The aim is to explore how control-theoretic structures can enhance learning methods for robotic control, ensuring flexibility and safety.

January 23, 2026Open Access

Constructive Learning for Agile Underactuated Control

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The aim is to explore how control-theoretic structures can enhance learning methods for robotic control, ensuring flexibility and safety.
Developed three strategies integrating control structure with learning.
Utilized Lyapunov and barrier functions for ensuring stability and safety.
Validated approaches using neural ordinary differential equations and hardware experiments.
Demonstrated stability and safety guarantees in neural networks through pointwise conditions.
Achieved over three thousand hops in hardware experiments with a bipedal walker and a hopping robot.
Established theoretical results linking zero dynamics policies with global state stability.

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This research demonstrates effective control strategies for underactuated systems, enhancing performance and safety through learning techniques.

Ivan Dario Jimenez Rodriguez (2026) studied this question.

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This research demonstrates effective control strategies for underactuated systems, enhancing performance and safety through learning techniques.