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talos_centroidal_mpc_torque_control: final version

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title: "Torque Controlled Locomotion of a Biped Robot with Link Flexibility"
subtitle: Submitted to 2022 IEEE-RAS Humanoids - International Conference on Humanoid Robots
author:
- <a href="www.linkedin.com/in/nahuelvilla">Nahuel A. Villa ^1^,
- Pierre Fernbach ^2^,
- Maximilien Naveau ^1, 2^,
- Guilhem Saurel ^1^,
- <a href="https://www.linkedin.com/in/ewen-dantec-aerospace/?originalSubdomain=fr">Ewen Dantec ^1^,
- <a href="https://gepettoweb.laas.fr/index.php/Members/NicolasMansard">Nicolas Mansard</a> ^1,3^,
- <a href="https://homepages.laas.fr/ostasse">Olivier Stasse</a> ^1,3^
org:
- ^1^ Gepetto Team, LAAS-CNRS, Université de Toulouse, France
- ^2^ TOWARD, Toulouse, France
- ^3^ Artificial and Natural Intelligence Toulouse Institute, France
# hal: on-progress
peertube: https://peertube.laas.fr/videos/embed/9cc9e696-752b-411d-9706-e2379b4932f0?start=0s
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## Abstract
When a big and heavy robot moves, it exerts big forces on the environment and on its own structure, angular momentum can vary meaningfully, and the robot structure can be deformed in presence of mechanical weakness. Under these conditions, standard locomotion controllers can fail easily. In this article, we propose a full control scheme to work with heavy robots in torque control. The full centroidal dynamics is taken into account to generate walking gaits online, link deflections are taken into account to estimate the robot posture and all postural instructions are designed to be consistent between them and to avoid conflicts with the desired robot motion. These choices reduce model and control errors, allowing our balance stabilizer to compensate for the remaining residual errors. The stabilizer and motion generator are designed together to ensure feasibility under the assumption of bounded errors. We deploy this scheme to control the locomotion of the humanoid robot Talos, whose hip links flex when walking. It allows us to reach steps of 35 cm, for an average speed of 25 cm/sec, which is among the best performances so far for an electric robot.
**This work was supported by the cooperation agreement ROB4FAM.**
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