scholarly journals Grasping force control of a tendon-driven prosthetic finger based on force estimation using motor current signals

2016 ◽  
Author(s):  
Wendi Zhuo ◽  
Yi Zhang ◽  
Hua Deng
Keyword(s):  
Force Control ◽  
Force Estimation ◽  
Motor Current ◽  
Grasping Force ◽  
Prosthetic Finger

scholarly journals Grasping Force Control of Multi-Fingered Robotic Hands through Tactile Sensing for Object Stabilization

Sensors ◽  
2020 ◽  
Vol 20 (4) ◽  
pp. 1050 ◽  
Author(s):  
Zhen Deng ◽  
Yannick Jonetzko ◽  
Liwei Zhang ◽  
Jianwei Zhang
Keyword(s):  
Force Control ◽  
Estimation Method ◽  
Gaussian Mixture ◽  
Tactile Sensing ◽  
Robotic Hand ◽  
Force Estimation ◽  
Robotic Hands ◽  
Grasping Force ◽  
Spatio Temporal ◽  
Object Material

Grasping force control is important for multi-fingered robotic hands to stabilize the grasped object. Humans are able to adjust their grasping force and react quickly to instabilities through tactile sensing. However, grasping force control through tactile sensing with robotic hands is still relatively unexplored. In this paper, we make use of tactile sensing for multi-fingered robot hands to adjust the grasping force to stabilize unknown objects without prior knowledge of their shape or physical properties. In particular, an online detection module based on Deep Neural Network (DNN) is designed to detect contact events and object material simultaneously from tactile data. In addition, a force estimation method based on Gaussian Mixture Model (GMM) is proposed to compute the contact information (i.e., contact force and contact location) from tactile data. According to the results of tactile sensing, an object stabilization controller is then employed for a robotic hand to adjust the contact configuration for object stabilization. The spatio-temporal property of tactile data is exploited during tactile sensing. Finally, the effectiveness of the proposed framework is evaluated in a real-world experiment with a five-fingered Shadow Dexterous Hand equipped with BioTac sensors.

scholarly journals Grasping Force Control of Multi-fingered Robot Hand based on Slip Detection Using Tactile Sensor

2007 ◽  
Vol 25 (6) ◽  
pp. 970-978 ◽  
Author(s):  
Daisuke Gunji ◽  
Takuma Araki ◽  
Akio Namiki ◽  
Aiguo Ming ◽  
Makoto Shimojo
Keyword(s):  
Force Control ◽  
Tactile Sensor ◽  
Robot Hand ◽  
Grasping Force ◽  
Slip Detection

scholarly journals A Finger Grip Force Sensor with an Open-Pad Structure for Glove-Type Assistive Devices

Sensors ◽  
2019 ◽  
Vol 20 (1) ◽  
pp. 4 ◽  
Author(s):  
Junghoon Park ◽  
Pilwon Heo ◽  
Jung Kim ◽  
Youngjin Na
Keyword(s):  
Degrees Of Freedom ◽  
Grip Force ◽  
Force Sensor ◽  
Assistive Devices ◽  
Finger Joint ◽  
Assistive Device ◽  
Force Estimation ◽  
Joint Angles ◽  
Fingertip Force ◽  
Grasping Force

This paper presents a fingertip grip force sensor based on custom capacitive sensors for glove-type assistive devices with an open-pad structure. The design of the sensor allows using human tactile sensations during grasping and manipulating an object. The proposed sensor can be attached on both sides of the fingertip and measure the force caused by the expansion of the fingertip tissue when a grasping force is applied to the fingertip. The number of measurable degrees of freedom (DoFs) are the two DoFs (flexion and adduction) for the thumb and one DoF (flexion) for the index and middle fingers. The proposed sensor allows the combination with a glove-type assistive device to measure the fingertip force. Calibration was performed for each finger joint angle because the variations in the expansion of the fingertip tissue depend on the joint angles. The root mean square error (RMSE) for fingertip force estimation ranged from 3.75% to 9.71% after calibration, regardless of the finger joint angles or finger posture.

Grasping Force Estimation by sEMG Signals and Arm Posture: Tensor Decomposition Approach

2019 ◽  
Vol 16 (3) ◽  
pp. 455-467 ◽  
Author(s):  
Sanghyun Kim ◽  
Joowan Kim ◽  
Mingon Kim ◽  
Seungyeon Kim ◽  
Jaeheung Park
Keyword(s):  
Tensor Decomposition ◽  
Force Estimation ◽  
Decomposition Approach ◽  
Grasping Force ◽  
Semg Signals
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