Incipient Slip Detection Method With Vision-Based Tactile Sensor Based on Distribution Force and Deformation

Sui, Ruomin; Zhang, Lunwei; Li, Tiemin; Jiang, Yao

doi:10.1109/jsen.2021.3119060

Cited by 26 publications

(17 citation statements)

References 24 publications

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“…First, in the first half of the phase where the tangential force increases, the degree of incipient slip is increasing, and more micro elements that were in the stick state become slip, leading to a decrease in the stick region and stick ratio. In this phase, there is an approximately linear negative correlation between the degree of incipient slip and stick ratio, which is consistent with the findings described in [11], [20]- [24]. The magnitude of the stick ratio in this case correctly reflects the degree of incipient slip.…”

Section: Os Ossupporting

confidence: 89%

“…The vision-based sensor contains an internal camera, often with a number of markers embedded in the surface, which enables the measurement of discrete deformation information on the contact surface by tracking the position of the markers. Several typical works include Goro Obinata et al [20], [21], Siyuan Dong et al [22], [23], and our work [11], [24]. This incipient slip degree evaluation method based on the area ratio of the stick/slip region has a clear physical meaning and can directly indicate the distance of the current state from macro slip (the complete disappearance of the stick region means that macro slip occurs).…”

Section: Introductionmentioning

confidence: 86%

“…In studies on the stick/slip region-based method, researchers often use the stick ratio to evaluate the degree of incipient slip > This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessible < [11], [20], [21], [24], which is defined as the area of the stick region OSg divided by the area of the total contact region OSc, as shown in (3). / stick g c…”

Section: A Evaluation Methods Based On Stick/slip Regionmentioning

confidence: 99%

See 2 more Smart Citations

A Novel Incipient Slip Degree Evaluation Method and Its Application in Adaptive Control of Grasping Force

Sui

Zhang

Huang

et al. 2024

IEEE Trans. Automat. Sci. Eng.

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Section: Os Ossupporting

confidence: 89%

Section: Introductionmentioning

confidence: 86%

Section: A Evaluation Methods Based On Stick/slip Regionmentioning

confidence: 99%

See 1 more Smart Citation

A Novel Incipient Slip Degree Evaluation Method and Its Application in Adaptive Control of Grasping Force

Sui

Zhang

Huang

et al. 2024

IEEE Trans. Automat. Sci. Eng.

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“…The signal generated by the aforementioned tactile sensors enables robots to execute sophisticated tasks using robot grippers that were once deemed challenging or unfeasible. These tasks include stable object grasping [ 14 , 15 ], slip detection [ 16 , 17 ], in-hand manipulation [ 18 ], and object information recognition, such as object recognition [ 19 , 20 ] and texture classification [ 21 , 22 ].…”

Section: Introductionmentioning

confidence: 99%

Effects of Sensing Tactile Arrays, Shear Force, and Proprioception of Robot on Texture Recognition

Yang

Kim

Lim

2023

Sensors

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In robotics, tactile perception is important for fine control using robot grippers and hands. To effectively incorporate tactile perception in robots, it is essential to understand how humans use mechanoreceptors and proprioceptors to perceive texture. Thus, our study aimed to investigate the impact of tactile sensor arrays, shear force, and the positional information of the robot’s end effector on its ability to recognize texture. A deep learning network was employed to classify tactile data from 24 different textures that were explored by a robot. The input values of the deep learning network were modified based on variations in the number of channels of the tactile signal, the arrangement of the tactile sensor, the presence or absence of shear force, and the positional information of the robot. By comparing the accuracy of texture recognition, our analysis revealed that tactile sensor arrays more accurately recognized the texture compared to a single tactile sensor. The utilization of shear force and positional information of the robot resulted in an improved accuracy of texture recognition when using a single tactile sensor. Furthermore, an equal number of sensors placed in a vertical arrangement led to a more accurate distinction of textures during exploration when compared to sensors placed in a horizontal arrangement. The results of this study indicate that the implementation of a tactile sensor array should be prioritized over a single sensor for enhanced accuracy in tactile sensing, and the use of integrated data should be considered for single tactile sensing.

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“…Therefore, thinner thickness elastomer geometry were developed in several studies. Yang et al [ 30 ] and Sui et al [ 31 ] introduced thinner thickness tactile sensors for surface sensing and slip detection. Due to their widespread application, several studies in the literature have focused on the simulation of VBTS sensors to support design optimisation and Sim2Real learning.…”

Section: Introductionmentioning

confidence: 99%

Elastomer-Based Visuotactile Sensor for Normality of Robotic Manufacturing Systems

et al. 2022

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Modern aircrafts require the assembly of thousands of components with high accuracy and reliability. The normality of drilled holes is a critical geometrical tolerance that is required to be achieved in order to realize an efficient assembly process. Failure to achieve the required tolerance leads to structures prone to fatigue problems and assembly errors. Elastomer-based tactile sensors have been used to support robots in acquiring useful physical interaction information with the environments. However, current tactile sensors have not yet been developed to support robotic machining in achieving the tight tolerances of aerospace structures. In this paper, a novel elastomer-based tactile sensor was developed for cobot machining. Three commercial silicon-based elastomer materials were characterised using mechanical testing in order to select a material with the best deformability. A Finite element model was developed to simulate the deformation of the tactile sensor upon interacting with surfaces with different normalities. Additive manufacturing was employed to fabricate the tactile sensor mould, which was chemically etched to improve the surface quality. The tactile sensor was obtained by directly casting and curing the optimum elastomer material onto the additively manufactured mould. A machine learning approach was used to train the simulated and experimental data obtained from the sensor. The capability of the developed vision tactile sensor was evaluated using real-world experiments with various inclination angles, and achieved a mean perpendicularity tolerance of 0.34°. The developed sensor opens a new perspective on low-cost precision cobot machining.

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Incipient Slip Detection Method With Vision-Based Tactile Sensor Based on Distribution Force and Deformation

Cited by 26 publications

References 24 publications

A Novel Incipient Slip Degree Evaluation Method and Its Application in Adaptive Control of Grasping Force

A Novel Incipient Slip Degree Evaluation Method and Its Application in Adaptive Control of Grasping Force

Effects of Sensing Tactile Arrays, Shear Force, and Proprioception of Robot on Texture Recognition

Elastomer-Based Visuotactile Sensor for Normality of Robotic Manufacturing Systems

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