Data correlation approach for slippage detection in robotic manipulations using tactile sensor array

Cheng, Yu; Su, Chengzhi; Jia, Yunyi; Xi, Ning

doi:10.1109/iros.2015.7353749

Cited by 11 publications

(5 citation statements)

References 13 publications

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“…A technique combining statistical parameters with frequency analysis was introduced few years ago in [82]. The signals taken from two tactile arrays mounted on a robotic manipulator were used to compute the correlation coefficient.…”

Section: B Transform Techniquesmentioning

confidence: 99%

Methods and Sensors for Slip Detection in Robotics: A Survey

Romeo

Zollo

2020

IEEE Access

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The perception of slip is one of the distinctive abilities of human tactile sensing. The sense of touch allows recognizing a wide set of properties of a grasped object, such as shape, weight and dimension. Based on such properties, the applied force can be accordingly regulated avoiding slip of the grasped object. Despite the great importance of tactile sensing for humans, mechatronic hands (robotic manipulators, prosthetic hands etc.) are rarely endowed with tactile feedback. The necessity to grasp objects relying on robust slip prevention algorithms is not yet corresponded in existing artificial manipulators, which are relegated to structured environments then. Numerous approaches regarding the problem of slip detection and correction have been developed especially in the last decade, resorting to a number of sensor typologies. However, no impact on the industrial market has been achieved. This paper reviews the sensors and methods so far proposed for slip prevention in artificial tactile perception, starting from more classical techniques until the latest solutions tested on robotic systems. The strengths and weaknesses of each described technique are discussed, also in relation to the sensing technologies employed. The result is a summary exploring the whole state of art and providing a perspective towards the future research directions in the sector.

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Section: B Transform Techniquesmentioning

confidence: 99%

Methods and Sensors for Slip Detection in Robotics: A Survey

Romeo

Zollo

2020

IEEE Access

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“…However, FT-based methods require a fixed-size time window to be analyzed in real-time. The length of the time window has a trade-off between fast adaptive real-time analysis and loss of information [ 36 , 37 ]. Another method is discrete wavelet transform (DWT), which disassembles the signal into high and low frequencies in the desired frequency range based on the sampling rate [ 38 ].…”

Section: Working Principle and Fundamental Characterizationmentioning

confidence: 99%

BaroTac: Barometric Three-Axis Tactile Sensor with Slip Detection Capability

Kim

Hwang

2022

Sensors

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Tactile sensors for robotic applications enhance the performance of robotic end-effectors as they ca n provide tactile information to operate various tasks. In particular, tactile sensors can measure multi-axial force and detect slip can aid the end-effectors in grasping diverse objects in an unstructured environment. We propose BaroTac, which measures three-axial forces and detects slip with a barometric pressure sensor chip (BPSC) for robotic applications. A BPSC is an off-the-shelf commercial sensor that is inexpensive, easy to customize, robust, and simple to use. While a single BPSC-based tactile sensor can measure pressure, an array of BPSC-based tactile sensors can measure multi-axial force through the reactivity of each sensor and detect slip by observing high frequency due to slip vibration. We first experiment with defining the fundamental characteristics of a single-cell BPSC-based sensor to set the design parameters of our proposed sensor. Thereafter, we suggest the sensing method of BaroTac: calibration matrix for three-axis force measurement and discrete wavelet transform (DWT) for slip detection. Subsequently, we validate the three-axis force measuring ability and slip detectability of the fabricated multi-cell BPSC-based tactile sensor. The sensor measures three-axis force with low error (0.14, 0.18, and 0.3% in the X-, Y- and Z-axis, respectively) and discriminates slip in the high-frequency range (75–150 Hz). We finally show the practical applicability of BaroTac by installing them on the commercial robotic gripper and controlling the gripper to grasp common objects based on our sensor feedback.

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“…Above all, smart skin capabilities provide vital environmental data in a package compatible with humanoid geometries, allowing robots the ability to understand and interact with their surroundings in a variety of ways [ 22 , 23 , 24 , 25 , 26 , 27 , 28 ]. For instance, a smart skin with pressure sensors could allow for the localization and quantification of pressure forces in contact with the skin, permitting safe interactions with humans in the robot’s operating environment, such as a human being able to brush a robot’s arm aside.…”

Section: Introductionmentioning

confidence: 99%

Design and Manufacture of Multifunctional 3-D Smart Skins with Embedded Sensor Networks for Robotic Applications

Ransom,

Chen,

Mangram

et al. 2024

Sensors

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An investigation was performed to develop a process to design and manufacture a 3-D smart skin with an embedded network of distributed sensors for non-developable (or doubly curved) surfaces. A smart skin is the sensing component of a smart structure, allowing such structures to gather data from their surrounding environments to make control and maintenance decisions. Such smart skins are desired across a wide variety of domains, particularly for those devices where their surfaces require high sensitivity to external loads or environmental changes such as human-assisting robots, medical devices, wearable health components, etc. However, the fabrication and deployment of a network of distributed sensors on non-developable surfaces faces steep challenges. These challenges include the conformal coverage of a target object without causing prohibitive stresses in the sensor interconnects and ensuring positional accuracy in the skin sensor deployment positions, as well as packaging challenges resulting from the thin, flexible form factor of the skin. In this study, novel and streamlined processes for making such 3-D smart skins were developed from the initial sensor network design to the final integrated skin assembly. Specifically, the process involved the design of the network itself (for which a physical simulation-based optimization was developed), the deployment of the network to a targeted 3D surface (for which a specialized tool was designed and implemented), and the assembly of the final skin (for which a novel process based on dip coating was developed and implemented.)

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Data correlation approach for slippage detection in robotic manipulations using tactile sensor array

Cited by 11 publications

References 13 publications

Methods and Sensors for Slip Detection in Robotics: A Survey

Methods and Sensors for Slip Detection in Robotics: A Survey

BaroTac: Barometric Three-Axis Tactile Sensor with Slip Detection Capability

Design and Manufacture of Multifunctional 3-D Smart Skins with Embedded Sensor Networks for Robotic Applications

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