Throwing motion design based on minimum sensitivity with respect to error covariance of robot dynamic parameters

Okada, Masafumi; Sekiguchi, Takahiro

doi:10.1299/mej.20-00299

Cited by 4 publications

(3 citation statements)

References 11 publications

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“…2) Throw specific objects vs. throw generic objects: The majority of previous approaches to throwing were limited to throwing one specific object type ( [1]: a wooden block; [2]- [4], [6], [13], [18]- [20]: a ball; [5]: a square plastic plate; [15], [17]: heavy boxes). In contrast, two recent approaches targeted throwing of a variety of generic objects [8], [9], We review these next.…”

Section: Specific Objectmentioning

confidence: 99%

“…Following a similar planar approach to throwing as in [5], Okada et al [18]- [20] perform sensitivity analysis of the landing position w.r.t. the robot's throwing configuration, initial configuration, and joint friction.…”

Section: B Robust Throwing Against Uncertaintiesmentioning

confidence: 99%

“…parameters of interest. To design a robust throwing configuration, they enumerate discretized valid configurations and select the one with the minimum norm (or weighted norm, considering error covariance [20]) of the sensitivity gradient.…”

Section: B Robust Throwing Against Uncertaintiesmentioning

confidence: 99%

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Tube Acceleration: Robust Dexterous Throwing Against Release Uncertainty

Liu,

Billard

2024

IEEE Trans. Robot.

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In robotic throwing, the release phase involves complex dynamic interactions due to object deformation and limited gripper opening speed, often resulting in inaccurate and nonrepeatable throws. While data-driven methods can be employed to compensate for the release uncertainty, the generalizability of learned models to unseen objects is not guaranteed, and object-specific fine-tuning with new data may be required. This fine-tuning process raises concerns about the scalability of such methods for dexterous throwing, where the robot needs to execute diverse motions for throwing various objects. Instead of case-bycase fine-tuning, we aim at designing throwing motion robust against release uncertainty. We encapsulate all uncertainties resulting from complex contact dynamics in a surrogate model of their resulting effect on gripper opening delay. We introduce the notion of tube acceleration to model the class of constantacceleration motion in joint space that guarantees a release within the set of valid throwing configurations. We propose a convex relaxation of the primal optimization problem with a tight error bound and evaluate its performance in terms of reliability and efficiency. Results show that the approach offers run-time performance to allow online computation of throws on a 7-DoF robot arm. It achieves a high accuracy and success rate (97% for planar throws) at throwing a variety of complex objects, even when using a simple ballistic model for the object's flying dynamics.

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Section: Specific Objectmentioning

confidence: 99%

Section: B Robust Throwing Against Uncertaintiesmentioning

confidence: 99%

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Tube Acceleration: Robust Dexterous Throwing Against Release Uncertainty

Liu,

Billard

2024

IEEE Trans. Robot.

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Design of varying control based on human’s motion proficiency for human - machine cooperative system under physical interaction

Okada

Taneichi

2022

Mechanical Engineering Journal

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Physical training enables us to recover from disability in rehabilitation or to acquire motion skill. So far, many devices that assist human's motion such as power assist suit have been developed. However, these devices do not consider human's proficiency level or recovery degree, therefore some adjustments of the device i.e. how much the device generates its force, will be required according to the human's proficiency level. In this paper, focusing on stabilization of an inverted pendulum, we propose a varying controller design method that changes its contribution for stabilization based on human's proficiency level. The controller is designed based on Model Predictive Control (MPC) for fast on-line calculation. Human's proficiency level is calculated from convergence level of the inverted pendulum system. The convergence level is obtained by a norm of state variables which is coordinate-transformed so that its norm decreases monotonically according to convergence. Based on human's proficiency level, the controller is designed to change its contribution. Experimental results show the degree of controller contribution is decreased for high skilled subjects and increased for low skilled subjects.

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Stochastic parameter identification based on dynamic/static sensitivity analysis for feed-forward control of robot periodic motion

Okada

MORIYAMA

KOIKE

2022

Transactions of the JSME (In Japanese)

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In robotic thick plate welding, the welding strength is ensured by periodically oscillating the welding torch attached to the end-effector in the horizontal direction, which is called weaving motion. Because the vertical accuracy of the end-effector affects a quality of the welding, it is necessary to reduce vertical error of the end-effector. In this paper, we focus on periodic motions, such as the weaving motion, and consider the suppression of vertical errors by feed-forward control. To calculate the feed-forward torque, it is necessary to identify the dynamic parameters of the robot. However, since noise and un-modeled dynamics are included in the experimental data, we identify parameters that have small influence on the motion error even though the existence of the parameter errors by considering the parameters as stochastic variables and identifying their error covariance to be the reference one. The reference error covariance is calculated from the sensitivity analysis of the vertical direction of the end-effector in the periodic motion with respect to the minimum set of dynamic parameters. Sensitivity of the dynamic/static motion, and sensitivity of feed-forward control are employed to improve the stability of the iterative calculation. By experiments using the planar 3-link manipulator, we confirm that vertical errors of the weaving motion are reduced by the feed-forward torque using the proposed method compared to the Least Mean Square.

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Throwing motion design based on minimum sensitivity with respect to error covariance of robot dynamic parameters

Cited by 4 publications

References 11 publications

Tube Acceleration: Robust Dexterous Throwing Against Release Uncertainty

Tube Acceleration: Robust Dexterous Throwing Against Release Uncertainty

Design of varying control based on human’s motion proficiency for human - machine cooperative system under physical interaction

Stochastic parameter identification based on dynamic/static sensitivity analysis for feed-forward control of robot periodic motion

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