Grasping Force Optimization for Multi-fingered Robotic Hands Using Projection and Contraction Methods

Mu, Xuewen; Zhang, Yaling

doi:10.1007/s10957-019-01540-9

Cited by 9 publications

(3 citation statements)

References 21 publications

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“…Chen et al [15] proposed a grasping force optimization method based on a generalized penalty function and introduced different penalty factors according to different grasping configurations to construct an augmented optimization target function. Mu et al [16] proposed a projection contraction method to solve the grasping force optimization problem globally converging to the optimal grasping force. Helmke et al [17] proposed an improved Newton algorithm of quadratic convergence to calculate the grasping force, concentrating on the linear constraints and studying the Newton algorithm's step size.…”

Section: Introductionmentioning

confidence: 99%

Optimization Method of the Clamping Force for Large Cabin Parts

Yao,

Luan,

Ceccarelli

et al. 2023

Applied Sciences

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In order to realize the stable clamping of large cabin parts, this paper studied the clamping force optimization of the clamping mechanism for large-mass and large-size cabin parts. Firstly, three kinds of contact models are introduced. Then, a clamping matrix is constructed for a particular clamping configuration. The nonlinear friction cone constraint at the contact point is transformed into a linear affine constraint in a smooth Riemannian manifold using the special structure of the positive definite symmetric matrix. Finally, a large cabin part used in the aerospace field is used as an example for calculating and simulating the clamping force optimization. Different optimization algorithms are used to calculate the initial value which is put into the gradient flow optimization method of the clamping force for optimization calculation. Meanwhile, the normal clamping force value of a 2 t object is measured using relevant experimental equipment. The simulation results and experimental results show that the gradient flow optimization method of the clamping force can quickly complete the clamping force optimization of large-mass and large-size cabin parts. The actual measured value of the normal clamping force is close to the simulated convergence value. The distribution of the normal force of the clamping mechanisms and the convergence value of the clamping force for each clamping mechanism can provide some references for determining the output clamping force of the clamping mechanism and confirming a reasonable distribution of the clamping mechanism. It also confirms the feasibility and effectiveness of this method applied to the clamping force optimization for a large axial part.

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Section: Introductionmentioning

confidence: 99%

Optimization Method of the Clamping Force for Large Cabin Parts

Yao,

Luan,

Ceccarelli

et al. 2023

Applied Sciences

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show abstract

“…Grasp planning is a field of study that commonly focuses on convex objects that a single robot can grasp [20]; its purpose is to either find the greatest stability [21] or optimize grasp force on the robot's contact points [22,23]. To evaluate how good the robot's grasp is, there are metrics that give a refined grasp quantitative value [24].…”

Section: Introductionmentioning

confidence: 99%

Grasp Planning Based on Metrics for Collaborative Tasks Using Optimization

Zafra-Urrea,

López-Damian,

Santana-Díaz

2023

Applied Sciences

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In recent years, technological developments in the field of robotics have expanded their application spectrum to encompass tasks that involve human inclusion in the same workspace. One of the challenges of robotics collaboration is the issue of how a robot and a human can perform daily collaborative tasks, like manipulation of an object. One significant specific problem to solve is where the robot can grasp the object knowing the human grasping points. This research proposes a planning algorithm to find a robot grasping point based on geometric grasp metrics as well as a new heuristic metric focused on the intrinsic inertia in multi-directional object movement. We propose three grasping points: two points emulating each human hand, positioned anywhere on the object and one last point, referencing the robot, which will be optimized as a multi-objective (MO) function problem. The planner was tested using common objects present in human environments (a chair and a table).

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“…Chen et al [5] proposed a grasping force optimization method based on a generalized penalty function and introduced different penalty factors according to different grasping configurations to construct an augmented optimization target function. Mu et al [6] proposed a projection contraction method to solve the grasping force optimization problem, which is globally converging to the optimal grasping force. Helmke et al [7] proposed an improved Newton algorithm of quadratic convergence to calculate the grasping force, which concentrates on the linear constraints and studied the step size of the Newton algorithm.…”

Section: Introductionmentioning

confidence: 99%

Optimization Method of The Clamping Force for Large Cabin Parts

Yao

Luan

Ceccarelli

et al. 2023

Preprint

View full text Add to dashboard Cite

In order to realize a stable clamping of the large cabin part, this paper studied the optimization of the clamping force for the clamping mechanism of the large-mass and large-size cabin part. Firstly, three kinds of contact models are introduced. Then a clamping matrix is constructed for a particular clamping configuration and the nonlinear friction cone constraint at the contact point is transformed into a linear affine constraint in a smooth Riemannian manifold by using the special structure of the positive definite symmetric matrix. Finally, a large cabin part in the aerospace field is used as an example for calculation and simulation of the clamping force optimization. Different optimization algorithms are used to calculate the initial value which will be put into the gradient flow optimization method of the clamping force for optimization calculation. The numerical results and curves show that the gradient flow optimization method of the clamping force can quickly complete the clamping force optimization of the large-mass and large-size cabin part. The distribution of the normal force of the clamping mechanisms and the convergence value of the clamping force for each clamping mechanism can provide some references for determining the output clamping force of the clamping mechanism and confirming a reasonable distribution of the clamping mechanism. It also proved the feasibility and effectiveness of this method applied in the clamping force optimization for the large axial part.

show abstract

Grasping Force Optimization for Multi-fingered Robotic Hands Using Projection and Contraction Methods

Cited by 9 publications

References 21 publications

Optimization Method of the Clamping Force for Large Cabin Parts

Optimization Method of the Clamping Force for Large Cabin Parts

Grasp Planning Based on Metrics for Collaborative Tasks Using Optimization

Optimization Method of The Clamping Force for Large Cabin Parts

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