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Updated: Jul 7, 2026

Estimation of Contact Regions Between Hands and Objects During Human Multi-Digit Grasping

Estimation of Contact Regions Between Hands and Objects During Human Multi-Digit Grasping

Published on: April 21, 2023

A general dynamic force distribution algorithm for multifingered grasping.

B R Zuo¹, W H Qian

¹Res. Inst. of Robotics, Shanghai Jiaotong Univ.

IEEE Transactions on Systems, Man, and Cybernetics. Part B, Cybernetics : a Publication of the IEEE Systems, Man, and Cybernetics Society

|February 5, 2008

Summary

This summary is machine-generated.

A novel dynamic force distribution (DFD) algorithm optimizes multifingered grasping by defining optimal internal forces. This method enhances real-time robotic control by efficiently calculating forces during grasp planning and manipulation.

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Area of Science:

Robotics
Control Systems
Mechanical Engineering

Background:

Multifingered grasping requires sophisticated algorithms to manage complex contact forces.
Existing methods may struggle with nonlinear constraints and temporal discontinuities in real-time control.

Purpose of the Study:

To present a general dynamic force distribution (DFD) algorithm for multifingered grasping.
To define optimal internal forces based on contact constraint properties.
To enable robust real-time control for robotic manipulation tasks.

Main Methods:

The DFD algorithm leverages convexity and cone properties of contact constraints.
Contact force determination is divided into grasp planning and task manipulation phases.
It incorporates both off-line iterative and on-line analytical computations for efficiency.

Main Results:

The algorithm successfully defines optimal internal forces for stable grasps.
It effectively determines manipulation forces and compensation factors during tasks.
The method demonstrates capability in handling nonlinear and coupled constraints.

Conclusions:

The proposed DFD algorithm provides a robust framework for multifingered grasping.
It overcomes temporal discontinuity issues in dynamic force control.
This approach enhances the real-time control capabilities of robotic systems.