Comparison of Position and Torque Whole-Body Control Schemes on the Humanoid Robot TALOS

Ramuzat, Noëlie; Buondonno, Gabriele; Boria, Sébastien; Stasse, Olivier

doi:10.1109/icar53236.2021.9659380

Cited by 20 publications

(18 citation statements)

References 28 publications

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“…1. TALOS's hip flexibility has a significant impact on its leg control and, as a result, its balance and locomotion [6]. Since the hip flexibility is due to the vertical linkage following previous work [10], we model the flexibility along the pitch and roll axis for each leg.…”

Section: Resultsmentioning

confidence: 99%

“…The whole-body control layer typically assumes that all robot links are rigid bodies, which models correctly the whole-body motion in most cases [4], [5], [6], but becomes problematic with even small link deflections. This problem is common in heavy robot with mechanical weakness in their structure, such as the robot Talos (≈ 100 kg), whose hips bend while walking.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Whole-Body Control and Estimation of Humanoid Robots with Link Flexibility

Romualdi

Villa

Dafarra

et al. 2022

2022 IEEE-RAS 21st International Conference on Humanoid Robots (Humanoids)

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This article presents a whole-body controller for humanoid robots affected by concentrated link flexibility. We characterize the link flexibility by introducing passive joints at the concentration of deflections, which separate the flexible links into two or more rigid bodies. In this way, we extend our robot model to take link deflections into account as underactuated extra degrees of freedom, allowing us to design a whole-body controller capable to anticipate deformations. Since in a real scenario, the deflection is not directly measurable, we present an observer aiming at estimating the flexible joint state, namely position, velocity, and torque, only considering the measured contact force and the state of actuated joint. We validate the overall approach in simulations with the humanoid robot TALOS, whose hip is mechanically flexible due to a localized mechanical weakness. Furthermore, the paper compares the proposed wholebody control strategy with state-of-the-art approaches. Finally, we analyze the performance of the estimator in the case of different values of hip elasticity.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Whole-Body Control and Estimation of Humanoid Robots with Link Flexibility

Romualdi

Villa

Dafarra

et al. 2022

2022 IEEE-RAS 21st International Conference on Humanoid Robots (Humanoids)

View full text Add to dashboard Cite

show abstract

“…Once the CoM and the footsteps trajectories are computed, they have to be executed on the robot through a whole-body controller. In this article, we used the torque controller introduced in [25], [26]. It is a weighted quadratic program based on the Task Space Inverse Dynamic (TSID) library [27].…”

Section: B Whole-body Controller Of the Robotmentioning

confidence: 99%

From the Study of Table Trajectories during Collaborative Carriages toward Pro-active Human-Robot Table Handling Tasks

Maroger

Stasse

Watier

2022

2022 IEEE-RAS 21st International Conference on Humanoid Robots (Humanoids)

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The study of human-human interactions is essential for a better understanding of human behaviour during collaborative tasks. This knowledge is not only interesting in life science but can also be useful in robotic science. Indeed, to efficiently assist a human partner during a human-robot collaboration, the robot needs to be as reactive as a human would be. This can only be achieved by embedding a model of human behaviour into the robot control scheme. In this paper, a human-humanoid robot collaboration to carry a table is tackled. First, the experimental Center of Mass (CoM) trajectories of a table carried by 20 pairs of subjects to various goal positions are studied and modeled using an optimal control problem. Then, based on this model, a prediction process which accurately predicts the table trajectories is designed. Finally, this prediction process is coupled with the robot Walking Pattern Generator (WPG). Using a torque whole-body controller, this framework is tested in simulation on Gazebo on a TALOS humanoid robot model. In this simulation, the robot actively assists a simulated human partner in lifting and carrying a table to an unknown goal position.

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“…Indeed, besides the ground reac-tion forces that are exchanged when dealing with legged robots (Liu et al, 2016), no optimal controller is currently formulated to describe the multiple types of interaction that can occur with the environment or, in a more complex case, with a human, as discussed above. In particular, current optimization-based controllers consider simple tasks that do not include environmental interaction, such as constrained pick and place (Escande et al, 2014;Flacco and De Luca, 2015) or trajectory tracking (Hoffman et al, 2018;Ramuzat et al, 2021). On the other hand, the works that account for physical interaction often employ nonoptimal formulations, which exploit a closed-form impedance controller to absorb any unforeseen force and perturbation (Pollayil et al, 2022).…”

Section: Introductionmentioning

confidence: 99%

Multi-Modal and Adaptive Control of Human-Robot Interaction through Hierarchical Quadratic Programming

Tassi

Ajoudani

2023

Preprint

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This paper proposes a novel Hierarchical Quadratic Programming (HQP)-based framework that enables multi-tasking control under multiple Human-Robot Interaction (HRI) scenarios. The objective is to create a unique framework for various types of HRI control modalities, avoiding the necessity of switching between different controllers that are usually tailored to a specific task. To achieve this, we firstly propose a HQP-based hybrid Cartesian/joint space impedance control formulation. This is based on the system's dynamics and provides an adaptive compliance behaviour during HRI, while performing hierarchical motion control. This is validated through a series of experiments that show the accuracy of trajectory tracking and the variable compliance behaviour. We then consider the case in which the human needs to move the robot by acting directly onto it, by proposing a hybrid admittance/impedance hierarchical control, which is then validated through several experiments in which the human moves the robot in the workspace. Next, we formulate a HQP-based force controller for HRI applications in which a specific interaction force must be maintained and lastly, we extend this to simultaneous force and trajectory tracking for applications that need higher position accuracy. Further experiments are conducted, to validate the proposed framework, using a redundant mobile manipulator. Overall, we obtain a single multi-purpose HQP-based control framework, that can switch continuously between interaction modes, enclosing multiple behaviours adjusted online based on the type of interaction.

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Comparison of Position and Torque Whole-Body Control Schemes on the Humanoid Robot TALOS

Cited by 20 publications

References 28 publications

Whole-Body Control and Estimation of Humanoid Robots with Link Flexibility

Whole-Body Control and Estimation of Humanoid Robots with Link Flexibility

From the Study of Table Trajectories during Collaborative Carriages toward Pro-active Human-Robot Table Handling Tasks

Multi-Modal and Adaptive Control of Human-Robot Interaction through Hierarchical Quadratic Programming

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