VTacArm. A Vision-based Tactile Sensing Augmented Robotic Arm with Application to Human-robot Interaction

Zhang, Guanlan; Du, Yipai; Wang, Michael Yu

doi:10.1109/case48305.2020.9217019

Cited by 5 publications

(6 citation statements)

References 26 publications

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“…Isabella et al [34] outlined a tactile sensor composed of a hemispherical film and a depth camera to correct and follow human finger movements. Zhang et al [35] built a cylindrical tactile sensor similar to the human arm based on a fisheye lens, and used optical flow method to track markers on a soft substrate and detect the location of the applied force. Force estimation is challenging to achieve in that setup because the change in pixel position of markers in a thin skin is hard to accurately obtain.…”

Section: B Vision-based Tactile Sensing For Manipulator Linksmentioning

confidence: 99%

ELTac: A Vision-Based Electroluminescent Tactile Sensing Skin for Force Localization and Magnitude Estimation

Fu,

Saha,

Shere

et al. 2024

IEEE Sensors J.

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Section: B Vision-based Tactile Sensing For Manipulator Linksmentioning

confidence: 99%

ELTac: A Vision-Based Electroluminescent Tactile Sensing Skin for Force Localization and Magnitude Estimation

Fu,

Saha,

Shere

et al. 2024

IEEE Sensors J.

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“…The vision-based computation method is an effective way to improve the robotic touch by using visual data [140]. The characteristics of some recent prototypes of vision-based sensors [141]- [148], are summarized in Table IV. A typical example is GelSight fingertip-style tactile sensor [149], [150], as shown in Figure 7 (a).…”

Section: ) Vision-based Computationmentioning

confidence: 99%

“…The sensor is capable of manipulating glass marbles in-hand with a multi-finger robotic hand by training deep neural network model-based controllers. The vision-based tactile sensing method is able to be further scaled up for large-area sensing with acceptable wiring issues [148]. As shown in Figure 7(b), Duong et al [147] developed a large-scale vision-based tactile sensing system for a robotic link, which is able to form a whole-body tactile sensing robot arm.…”

Section: ) Vision-based Computationmentioning

confidence: 99%

Review of Robot Skin: A Potential Enabler for Safe Collaboration, Immersive Teleoperation, and Affective Interaction of Future Collaborative Robots

Pang

Yang

Pang

2021

IEEE Trans. Med. Robot. Bionics

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The emerging applications of collaborative robots (cobots) are spilling out from product manufactories to service industries for human care, such as patient care for combating the coronavirus disease 2019 (COVID-19) pandemic and in-home care for coping with the aging society. There are urgent demands on equipping cobots with safe collaboration, immersive teleoperation, affective interaction, and other features (e.g., energy autonomy and self-learning) to make cobots capable of these application scenarios. Robot skin, as a potential enabler, is able to boost the development of cobots to address these distinguishing features from the perspective of multimodal sensing and self-contained actuation. This review introduces the potential applications of cobots for human care together with those demanded features. In addition, the explicit roles of robot skin in satisfying the escalating demands of those features on inherent safety, sensory feedback, natural interaction, and energy autonomy are analyzed. Furthermore, a comprehensive review of the recent progress in functionalized robot skin in components level, including proximity, pressure, temperature, sensory feedback, and stiffness tuning, is presented. Results show that the codesign of these sensing and actuation functionalities may enable robot skin to provide improved safety, intuitive feedback, and natural interfaces for future cobots in human care applications. Finally, open challenges and future directions in the real implementation of robot skin and its system synthesis are presented and discussed.

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“…However, the study mentioned in future work that the size could be minimized to the size of fingertips, but the final size was restricted by the size of the internal camera. In fact, with a camera of Principles of Optics, although the surface displacement and force data could be converted into a three-dimensional image to achieve tactile visualization through the Tessellation point on the plane caused by the force, its structure was restricted by the lens specifications and size, which made it difficult for its integration and application of robotic arms [ 24 , 25 , 26 ]. In addition, as the commercially available collaborative robot arm grips the ultrasonic probe with a gripper, different fixture and probe models cannot be effectively fitted, and the ultrasonic probe may shake slightly during the measurement process, which leads to errors in measurement angles.…”

Section: Introductionmentioning

confidence: 99%

An Improved Sensing Method of a Robotic Ultrasound System for Real-Time Force and Angle Calibration

Wang

Chen

et al. 2021

Sensors

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An ultrasonic examination is a clinically universal and safe examination method, and with the development of telemedicine and precision medicine, the robotic ultrasound system (RUS) integrated with a robotic arm and ultrasound imaging system receives increasing attention. As the RUS requires precision and reproducibility, it is important to monitor the real-time calibration of the RUS during examination, especially the angle of the probe for image detection and its force on the surface. Additionally, to speed up the integration of the RUS and the current medical ultrasound system (US), the current RUSs mostly use a self-designed fixture to connect the probe to the arm. If the fixture has inconsistencies, it may cause an operating error. In order to improve its resilience, this study proposed an improved sensing method for real-time force and angle calibration. Based on multichannel pressure sensors, an inertial measurement unit (IMU), and a novel sensing structure, the ultrasonic probe and robotic arm could be simply and rapidly combined, which rendered real-time force and angle calibration at a low cost. The experimental results show that the average success rate of the downforce position identification achieved was 88.2%. The phantom experiment indicated that the method could assist the RUS in the real-time calibration of both force and angle during an examination.

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VTacArm. A Vision-based Tactile Sensing Augmented Robotic Arm with Application to Human-robot Interaction

Cited by 5 publications

References 26 publications

ELTac: A Vision-Based Electroluminescent Tactile Sensing Skin for Force Localization and Magnitude Estimation

ELTac: A Vision-Based Electroluminescent Tactile Sensing Skin for Force Localization and Magnitude Estimation

Review of Robot Skin: A Potential Enabler for Safe Collaboration, Immersive Teleoperation, and Affective Interaction of Future Collaborative Robots

An Improved Sensing Method of a Robotic Ultrasound System for Real-Time Force and Angle Calibration

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