Vision-Based High-Resolution Tactile Sensor By Using Visual Light Ring

He, Kaiyang; Shi, Xiaoxiao; Yu, Duli; Guo, Xiaoliang

doi:10.1109/lsens.2022.3156290

Cited by 7 publications

(2 citation statements)

References 8 publications

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“…[1,132,157] The next generation of intelligent robots is defined as a robot that can obtain external environmental information using builtin sensors, extract information necessary for a work by itself, judge the situation, and operate autonomously in a workspace. [163,164] The size and shape of the robots vary depending on the work space and the target task, which requires the convergence of various technologies [164] such as smart sensors for vision, [165,166] tactility, and auditory sensation. [167,168] Performance of those sensors can be improved with the aid of simultaneous localization and mapping [169] and artificial intelligence algorithms.…”

Section: Prospectsmentioning

confidence: 99%

Current Landscape of the Robotic Tactile Array Sensors and Algorithm‐Based Performance Enhancement

Cho,

Park,

Kim

et al. 2024

Adv Eng Mater

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The automated robots utilizing the traditional rigid tactile sensors have achieved significant success in effective task execution. Advancing into the era of service robots and humanoids that should perform sophisticated works in daily life, recent research trends in robotic tactile sensors have been shifting from the conventional rigid sensors to flexible/stretchable sensors. Over the past decade, the flexible/stretchable tactile sensors with human skin‐like mechanical compliance and stimulation perceptions have seen considerable advances. However, there are many substantial remaining challenges to produce practically useful flexible/stretchable tactile sensors such as the signal hysteresis originating from sensor material and the limited spatial resolution resulting from excessive addressing lines and signal interferences. Incorporation of learning‐based algorithms and data analysis techniques have been introduced recently and made remarkable successes in improving the challenges. Because most robotic tactile sensors are fabricated by using the electronic sensing mechanisms or platforms, this article presents a concise overview on recent flexible/stretchable tactile sensors. This article introduces a brief discussion on the sensor performance parameters and sensing mechanisms, and the algorithmic approaches. In addition, it addresses existing challenges associated with current tactile array sensors and algorithms, then discusses prospects and proposes a research direction for immediate practical uses in robots.This article is protected by copyright. All rights reserved.

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Section: Prospectsmentioning

confidence: 99%

Current Landscape of the Robotic Tactile Array Sensors and Algorithm‐Based Performance Enhancement

Cho,

Park,

Kim

et al. 2024

Adv Eng Mater

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“…Herein, we aimed to detect pressure and slippage information directly from a single sensor design. To overcome the above-mentioned challenges of static tactile sensors, we are inspired by vision-based solutions, which are recognized as highly reliable, wide-range-sensing and successfully adopted in various systems [9][10][11][12]. Vison-based tactile sensors analysis the change of light and need no complex integrated circuits, it can detect both pressure and slippage information by image processing.…”

Section: Introductionmentioning

confidence: 99%

A vision-based tactile sensor with single contact surface for pressure and slippage estimation

Feng,

Fang,

Wang

2024

Fourth International Conference on Computer Vision and Information Technology (CVIT 2023)

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Touch is an important way that a human being senses the surrounding environment, but in robotic applications, it is difficult to obtain static and dynamic tactile signals simultaneously. In this paper, we proposed a new vison-based tactile sensor to estimate pressure and slippage distance at the same time. The sensor recognizes the deformation degree of elastomer through image processing, and the pressure is estimated according to the radius of contact region. Sensor captures the surface of the contact object and tracks feature point to calculate optical flow. Then the slippage distance is estimated by Kalman filtering and integration of the optical flow. The sensor is realized in a small package, so it can be useful in wide range of scenarios. Here we also built a two-dimensional experimental platform to test the sensor, and the experimental results show that the average error of pressure estimation is 6.4%, and the average error of slippage estimation is 14.4% at 5mm/s, demonstrating a good sensing performance for providing pressure and slippage via the single contact surface.

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