Standing stabilizability and stepping maneuver in planar bipedalism based on the best COM-ZMP regulator

Sugihara, Tomomichi

doi:10.1109/robot.2009.5152284

Cited by 139 publications

(93 citation statements)

References 25 publications

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“…This dynamics is traditionally reformulated as follows in order to emphasize the linear relationship between the horizontal motion of the CoM and the CoP [9], [1], [24], [23], [5], [10], dropping coordinate indices x and y :…”

Section: Point Mass Model With Bounded Uncertaintiesmentioning

confidence: 99%

“…Such a dead-beat control of the CP was already proposed in [9] for different reasons as uncertainties were not considered. It corresponds also to "the best regulator" proposed in [23]. The set Z corresponding to this choice of gain K, using parameters provided in Table I, can be seen in Fig.1, together with the typical behavior of the closed-loop dynamics (12) of the tracking error.…”

Section: Optimal Tracking Control Gainsmentioning

confidence: 99%

“…It is standard practice to include a saturation in the control law (10) with respect to the constraint (3), either explicitly limiting its value [9], [23] or in an optimization problem [24]. This usually increases significantly the region of attraction of the control law [2].…”

Section: Optimal Tracking Control Gainsmentioning

confidence: 99%

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Model predictive control of biped walking with bounded uncertainties

Villa

Wieber

2017

2017 IEEE-RAS 17th International Conference on Humanoid Robotics (Humanoids)

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Abstract-A biped walking controller for humanoid robots has to handle together hard constraints, dynamic environments, and uncertainties. Model Predictive Control (MPC) is a suitable and widely used control method to handle the first two issues. Uncertainties on the robot imply a non-zero tracking error when trying to follow a reference motion. A standard solution for this issue is to use tighter constraints by introducing some hand tuned safety margins, for the reference motion generation to ensure that the actual robot motion will satisfy all constraints even in presence of the tracking error. In this article, we find bounds for the tracking error and we show how such safety margins can be precisely computed from the tracking error bounds. Also, a tracking control gain is proposed to reduce the restrictiveness introduced with the safety margins. MPC with these considerations ensure the correct operation of the biped robot under a given degree of uncertainties when it is implemented in open-loop. Nevertheless, the straightforward way to implement an MPC closed-loop scheme fails. We discuss the reasons for this failure and propose a robust closed-loop MPC scheme.

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Section: Point Mass Model With Bounded Uncertaintiesmentioning

confidence: 99%

Section: Optimal Tracking Control Gainsmentioning

confidence: 99%

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Model predictive control of biped walking with bounded uncertainties

Villa

Wieber

2017

2017 IEEE-RAS 17th International Conference on Humanoid Robotics (Humanoids)

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“…An efficacy of a controller design scheme for a biped robot based on the center of mass (COM) [1][2][3][4][5][6] has been acknowledged. COM captures the core dynamics in the whole body motion, so that it enables an intuitive design of the controller with low computation cost.…”

Section: Introductionmentioning

confidence: 99%

“…A crucial issue in the scheme is the motion (position and velocity) estimation of COM, since it is embedded in a feedback loop and has a large influence to the controller performance. For example, some biped robot controllers [1][2][3][4][5][6] and on-line walking motion planners [7,8] that use the current position and velocity of COM have been proposed. COM is a point defined from the mass distribution and the whole-body configuration of the robot, and cannot be directly measured.…”

Section: Introductionmentioning

confidence: 99%

COM motion estimation of a biped robot based on kinodynamics and torque equilibrium

Masuya

Sugihara

2016

Advanced Robotics

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A novel technique to estimate motion of the center of mass (COM) for a biped robot is proposed. A Kalman filter is synthesized where the time evolution of COM is predicted from the external force and corrected based on kinematic estimation and torque equilibrium. They complementarily work to compensate the initial estimation offset, the error accumulation, and errors in modeled mass properties. It makes use of the authors' previous method to estimate the translational and rotational motion of the base body from inertial information and joint angle measurements. The information about torque equilibrium helps to reduce an uncertainty of the height of COM and to improve the estimation accuracy of it by utilizing an interference of the horizontal and vertical motion of COM. The parameters are tuned based on error analyses in mass properties and sensor signals. A comparative study showed a better performance of the proposed method than other methods through dynamics simulations. ARTICLE HISTORY

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Experimental Validation of Resolved Viscoelasticity Control on Hydrostatically Driven Humanoid Hydra

Yamamoto

Murotani

et al. 2020

Springer Proceedings in Advanced Robotics

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Standing stabilizability and stepping maneuver in planar bipedalism based on the best COM-ZMP regulator

Cited by 139 publications

References 25 publications

Model predictive control of biped walking with bounded uncertainties

Model predictive control of biped walking with bounded uncertainties

COM motion estimation of a biped robot based on kinodynamics and torque equilibrium

Experimental Validation of Resolved Viscoelasticity Control on Hydrostatically Driven Humanoid Hydra

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