Learning Push Recovery Strategies for Bipedal Walking | Zendy

Dicksiano C. Melo | Zendy; Marcos R. O. A. Máximo | Zendy; Adilson Marques da Cunha | Zendy

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Learning Push Recovery Strategies for Bipedal Walking

Author(s) -

Dicksiano C. Melo,

Marcos R. O. A. Máximo,

Adilson Marques da Cunha

Publication year - 2021

Language(s) - English

Resource type - Conference proceedings

DOI - 10.5753/wtdr_ctdr.2021.18686

Subject(s) - computer science , league , humanoid robot , controller (irrigation) , work (physics) , robot , physics engine , simulation , artificial intelligence , human–computer interaction , control engineering , engineering , physics , astronomy , mechanical engineering , agronomy , biology

The present work provides an implementation of a Push Recovery controller that aids the walking engine used by a humanoid simulated robot. The simulation environment is the Robocup Soccer 3D Simulation League. The learned movement policies exceeded our original walking engine. In addition, we evaluated the policies and detected undesired biases. New methodologies were introduced in order to eliminate it.

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