Model-Based External Force/Moment Estimation for Humanoid Robots with no Torque Measurement

Benallegue, Mehdi; Gergondet, Pierre; Audrerr, Herve; Mifsud, Alexis; Morisawa, Masaaki; Lamiraux, Florent; Kheddar, Abderrahmane; Kanehiro, Fumio

doi:10.1109/icra.2018.8460809

Cited by 16 publications

(6 citation statements)

References 22 publications

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“…By applying inverse dynamics to the kinematic chain from the point at which the force is applied to the robot's CoM, the wrench vectors in the second and third experiments as well as the virtual forces, as defined in (11), are respectively: Those three experiments are very similar to the experiments conducted in [14]. As such, they can be used as a benchmark to compare with their results.…”

Section: Applying a Force To A Point Of The Robot Armmentioning

confidence: 99%

“…Since the acceleration of the robot's CoM is known using IMU measurements and the floor reaction force can be directly measured with the F/T sensors, their results show that a strong impact force can be estimated somewhat accurately using that model. Another interesting method that can also estimate the external moment is proposed in [11]. That method relies on a modelbased estimator to fuse the data of the robot's sensors (F/T sensors and IMU) and the whole body dynamics.…”

Section: Model-based Approachmentioning

confidence: 99%

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External Force Observer for Small- and Medium-Sized Humanoid Robots

Hawley

Rahem

Suleiman

2019

Int. J. Human. Robot.

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External force observer for humanoid robots has been widely studied in the literature. However, most of the proposed approaches generally rely on information from six-axis force/torque sensors, which the small or medium-sized humanoid robots usually do not have. As a result, those approaches cannot be applied to this category of humanoid robots, which are widely used nowadays in education or research. In this paper, we propose a Kalman filter-based observer to estimate the three components of an external force applied in any direction and at an arbitrary point of the robot’s structure. The observer is simple to implement and can easily run in real time using the embedded processor of a small or medium-sized humanoid robot such as Nao or Darwin-OP. Moreover, the observer does not require any changes to the robot’s hardware, as it only uses measurements from the available force-sensing resistors (FSR) inserted under the feet of the humanoid robot and from the robot’s inertial measurement unit (IMU). The proposed observer was extensively validated on a Nao humanoid robot in both cases of standing still or walking while an external force was applied to the robot. In the conducted experiments, the observer successfully estimated the external force within a reasonable margin of error. Moreover, the experimental data and the MATLAB and C++/ROS implementations of the proposed observer are available as an open source package. https://goo.gl/VkhejY.

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Section: Applying a Force To A Point Of The Robot Armmentioning

confidence: 99%

Section: Model-based Approachmentioning

confidence: 99%

External Force Observer for Small- and Medium-Sized Humanoid Robots

Hawley

Rahem

Suleiman

2019

Int. J. Human. Robot.

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“…An alternative method is to accurately estimate external forces and the corresponding ground reaction forces relying on the dynamic model of the robot Xin et al (2018). For humanoid robotic applications, an external force/moment can be estimated based on an extended Kalman filter using whole-body dynamics, force sensor on the feet, and an IMU Benallegue et al (2018). In some cases, external forces can be measured using force-sensing resistors Hawley et al (2019) on the feet.…”

Section: Robots With External Disturbancesmentioning

confidence: 99%

Online Gain Adaptation of Whole-Body Control for Legged Robots with Unknown Disturbances

et al. 2022

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This paper proposes an online gain adaptation approach to enhance the robustness of whole-body control (WBC) framework for legged robots under unknown external force disturbances. Without properly accounting for external forces, the closed-loop control system incorporating WBC may become unstable, and therefore the desired task goals may not be achievable. To study the effects of external disturbances, we analyze the behavior of our current WBC framework via the use of both full-body and centroidal dynamics. In turn, we propose a way to adapt feedback gains for stabilizing the controlled system automatically. Based on model approximations and stability theory, we propose three conditions to ensure that the adjusted gains are suitable for stabilizing a robot under WBC. The proposed approach has four contributions. We make it possible to estimate the unknown disturbances without force/torque sensors. We then compute adaptive gains based on theoretic stability analysis incorporating the unknown forces at the joint actuation level. We demonstrate that the proposed method reduces task tracking errors under the effect of external forces on the robot. In addition, the proposed method is easy-to-use without further modifications of the controllers and task specifications. The resulting gain adaptation process is able to run in real-time. Finally, we verify the effectiveness of our method both in simulations and experiments using the bipedal robot Draco2 and the humanoid robot Valkyrie.

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“…Since the acceleration of the robot's CoM is known using IMU measurements and the floor reaction force can be directly measured with the F/T sensors, their results show that a strong impact force can be estimated somewhat accurately using that model. Another interesting method that can also estimate the external moment is proposed in [10], that method relies on a model-based estimator to fuse the data of the robot's sensors (F/T sensors and IMU) and the whole body dynamics. An advantage of this approach over the previously presented sensor-based approach is that the external force/moment do not have to be applied at a particular point in order to be estimated.…”

Section: A Relevant Workmentioning

confidence: 99%

Kalman Filter Based Observer for an External Force Applied to Medium-sized Humanoid Robots

Hawley

Rahem

Suleiman

2018

2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

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External force observer for humanoid robots has been widely studied in the literature. However, most of the proposed approaches generally rely on information from sixaxis force/torque sensors, which the small or medium-sized humanoid robots usually do not have. As a result, those approaches cannot be applied to this category of humanoid robots, which is widely used nowadays in education or research. In this paper, we improve the external force observer in [1] to handle the case of an external force applied in any direction and at an arbitrary point of the robot structure. The new observer is based on Kalman filter formulation and it allows the estimation of the three force components. The observer is simple to implement and can easily run in real time using the embedded processor of a medium-sized humanoid robot such as Nao or Darwin-OP. Moreover, the observer does not require any change to the robot hardware as it only uses measurements from the available force-sensing resistors (FSR) inserted under the feet of the humanoid robot and from the robot inertial measurement unit (IMU). The proposed observer was extensively validated on a Nao humanoid robot. In all conducted experiments, the observer successfully estimated the external force within a reasonable margin of error.

show abstract

Model-Based External Force/Moment Estimation for Humanoid Robots with no Torque Measurement

Cited by 16 publications

References 22 publications

External Force Observer for Small- and Medium-Sized Humanoid Robots

External Force Observer for Small- and Medium-Sized Humanoid Robots

Online Gain Adaptation of Whole-Body Control for Legged Robots with Unknown Disturbances

Kalman Filter Based Observer for an External Force Applied to Medium-sized Humanoid Robots

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