Benchmarking the HRP-2 Humanoid Robot During Locomotion

Stasse, Olivier; Giraud-Esclasse, Kevin; Brousse, E.; Naveau, Maximilien; Régnier, Rémi; Avrin, Guillaume; Souères, Philippe

doi:10.3389/frobt.2018.00122

Cited by 8 publications

(3 citation statements)

References 44 publications

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“…To complete the analysis performed in simulation, the MAPE-DDP and the EKF algorithms were used on real kinematic and kinetic data obtained during a 20 cm-wide locomotion lasting for 12.5 seconds with the HRP-2 robot taken from [16]. The values of the encoders and of the 6axis forces and torques sensors located in the ankles of the robot were collected at 200 Hz.…”

Section: Application To Robot Experimental Datamentioning

confidence: 99%

Optimal Estimation of the Centroidal Dynamics of Legged Robots

Bailly

Carpentier

Souères

2021

2021 IEEE International Conference on Robotics and Automation (ICRA)

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Estimating the centroidal dynamics of legged robots is crucial in the context of multi-contact locomotion of legged robots. In this paper, we formulate the estimation of centroidal dynamics as a maximum a posteriori problem and we use a differential dynamic programming approach for solving it. The soundness of the proposed approach is first validated on a simulated humanoid robot, where ground truth data is available, enabling error analysis, and then compared to other alternatives of the state of the art, namely an extend Kalman filter and a recursive complementary filter. The results demonstrate that, compared to other approaches, the proposed method reduces the estimation error on the centroidal state in addition to ensuring the dynamics consistency of the state trajectory. Finally, the effectiveness of the proposed method is illustrated on real measurements, obtained from walking experiments with the HRP-2 humanoid robot.

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Section: Application To Robot Experimental Datamentioning

confidence: 99%

Optimal Estimation of the Centroidal Dynamics of Legged Robots

Bailly

Carpentier

Souères

2021

2021 IEEE International Conference on Robotics and Automation (ICRA)

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“…8). The dataset was taken from [27]. In this experience, the robot was programmed to walk on a flat terrain without feedback on its pose in the room.…”

Section: B Application To Real Robot Experimental Datamentioning

confidence: 99%

Estimating the Center of Mass and the Angular Momentum Derivative for Legged Locomotion—A Recursive Approach

Bailly

Carpentier

Benallegue

et al. 2019

IEEE Robot. Autom. Lett.

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Estimating the center of mass position and the angular momentum derivative of legged systems is essential for both controlling legged robots and analyzing human motion. In this paper, a novel recursive approach to concurrently and accurately estimate these two quantities together is introduced. The proposed method employs kinetic and kinematic measurements from classic sensors available in robotics and biomechanics, to effectively exploits the accuracy of each measurement in the spectral domain. The soundness of the proposed approach is first validated on a simulated humanoid robot, where ground truth data is available, against an Extend Kalman Filter. The results demonstrate that the proposed method reduces the estimation error on the center of mass position with regard to kinematic estimation alone, whereas at the same time, it provides an accurate estimation of the derivative of angular momentum. Finally, the effectiveness of the proposed method is illustrated on real measurements, obtained from walking experiments with the HRP-2 humanoid robot.

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“…Following the existing benchmarking of humanoid robot control architectures Romualdi et al (2019) ; Stasse et al (2018) , this study contributes by benchmarking the TALOS humanoid robot. It is performed by comparing three whole-body control schemes on the TALOS robot in simulation.…”

Section: Introductionmentioning

confidence: 99%

Benchmarking Whole‐Body Controllers on the TALOS Humanoid Robot

2022

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This article presents a comparison of three control schemes applied on the commercially available TALOS humanoid robot. The aim is to highlight the advantages and drawbacks of each model applied on three locomotion problems: walking on flat and non-flat terrain and climbing stairs. The different models are based on position control (first and second models) or torque control (third model). The first one uses a hierarchical quadratic program at velocity level. The second one uses a weighted quadratic program named Task Space Inverse Dynamic (TSID) at acceleration level. Finally, the last one also uses TSID but at torque level. The controller performances are compared in simulation, using Gazebo, on the accuracy of their tracking, their energy consumption, and their computational time execution.

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Benchmarking the HRP-2 Humanoid Robot During Locomotion

Cited by 8 publications

References 44 publications

Optimal Estimation of the Centroidal Dynamics of Legged Robots

Optimal Estimation of the Centroidal Dynamics of Legged Robots

Estimating the Center of Mass and the Angular Momentum Derivative for Legged Locomotion—A Recursive Approach

Benchmarking Whole‐Body Controllers on the TALOS Humanoid Robot

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