{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,13]],"date-time":"2026-07-13T16:51:40Z","timestamp":1783961500916,"version":"3.55.0"},"reference-count":59,"publisher":"MDPI AG","issue":"15","license":[{"start":{"date-parts":[[2024,8,5]],"date-time":"2024-08-05T00:00:00Z","timestamp":1722816000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62373233"],"award-info":[{"award-number":["62373233"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62003200"],"award-info":[{"award-number":["62003200"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["GZC20230924"],"award-info":[{"award-number":["GZC20230924"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["IDICP-KF-2024-03"],"award-info":[{"award-number":["IDICP-KF-2024-03"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["2024AFB245"],"award-info":[{"award-number":["2024AFB245"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["202201020101006"],"award-info":[{"award-number":["202201020101006"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["CCNU24XJ005"],"award-info":[{"award-number":["CCNU24XJ005"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Postdoctoral Fellowship Program of CPSF","award":["62373233"],"award-info":[{"award-number":["62373233"]}]},{"name":"Postdoctoral Fellowship Program of CPSF","award":["62003200"],"award-info":[{"award-number":["62003200"]}]},{"name":"Postdoctoral Fellowship Program of CPSF","award":["GZC20230924"],"award-info":[{"award-number":["GZC20230924"]}]},{"name":"Postdoctoral Fellowship Program of CPSF","award":["IDICP-KF-2024-03"],"award-info":[{"award-number":["IDICP-KF-2024-03"]}]},{"name":"Postdoctoral Fellowship Program of CPSF","award":["2024AFB245"],"award-info":[{"award-number":["2024AFB245"]}]},{"name":"Postdoctoral Fellowship Program of CPSF","award":["202201020101006"],"award-info":[{"award-number":["202201020101006"]}]},{"name":"Postdoctoral Fellowship Program of CPSF","award":["CCNU24XJ005"],"award-info":[{"award-number":["CCNU24XJ005"]}]},{"name":"Open Projects funded by Hubei Engineering Research Center for Intelligent Detection and Identification of Complex Parts","award":["62373233"],"award-info":[{"award-number":["62373233"]}]},{"name":"Open Projects funded by Hubei Engineering Research Center for Intelligent Detection and Identification of Complex Parts","award":["62003200"],"award-info":[{"award-number":["62003200"]}]},{"name":"Open Projects funded by Hubei Engineering Research Center for Intelligent Detection and Identification of Complex Parts","award":["GZC20230924"],"award-info":[{"award-number":["GZC20230924"]}]},{"name":"Open Projects funded by Hubei Engineering Research Center for Intelligent Detection and Identification of Complex Parts","award":["IDICP-KF-2024-03"],"award-info":[{"award-number":["IDICP-KF-2024-03"]}]},{"name":"Open Projects funded by Hubei Engineering Research Center for Intelligent Detection and Identification of Complex Parts","award":["2024AFB245"],"award-info":[{"award-number":["2024AFB245"]}]},{"name":"Open Projects funded by Hubei Engineering Research Center for Intelligent Detection and Identification of Complex Parts","award":["202201020101006"],"award-info":[{"award-number":["202201020101006"]}]},{"name":"Open Projects funded by Hubei Engineering Research Center for Intelligent Detection and Identification of Complex Parts","award":["CCNU24XJ005"],"award-info":[{"award-number":["CCNU24XJ005"]}]},{"DOI":"10.13039\/501100003819","name":"Hubei Provincial Natural Science Foundation","doi-asserted-by":"publisher","award":["62373233"],"award-info":[{"award-number":["62373233"]}],"id":[{"id":"10.13039\/501100003819","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003819","name":"Hubei Provincial Natural Science Foundation","doi-asserted-by":"publisher","award":["62003200"],"award-info":[{"award-number":["62003200"]}],"id":[{"id":"10.13039\/501100003819","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003819","name":"Hubei Provincial Natural Science Foundation","doi-asserted-by":"publisher","award":["GZC20230924"],"award-info":[{"award-number":["GZC20230924"]}],"id":[{"id":"10.13039\/501100003819","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003819","name":"Hubei Provincial Natural Science Foundation","doi-asserted-by":"publisher","award":["IDICP-KF-2024-03"],"award-info":[{"award-number":["IDICP-KF-2024-03"]}],"id":[{"id":"10.13039\/501100003819","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003819","name":"Hubei Provincial Natural Science Foundation","doi-asserted-by":"publisher","award":["2024AFB245"],"award-info":[{"award-number":["2024AFB245"]}],"id":[{"id":"10.13039\/501100003819","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003819","name":"Hubei Provincial Natural Science Foundation","doi-asserted-by":"publisher","award":["202201020101006"],"award-info":[{"award-number":["202201020101006"]}],"id":[{"id":"10.13039\/501100003819","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003819","name":"Hubei Provincial Natural Science Foundation","doi-asserted-by":"publisher","award":["CCNU24XJ005"],"award-info":[{"award-number":["CCNU24XJ005"]}],"id":[{"id":"10.13039\/501100003819","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Science and Technology Major Project of Shanxi Province","award":["62373233"],"award-info":[{"award-number":["62373233"]}]},{"name":"Science and Technology Major Project of Shanxi Province","award":["62003200"],"award-info":[{"award-number":["62003200"]}]},{"name":"Science and Technology Major Project of Shanxi Province","award":["GZC20230924"],"award-info":[{"award-number":["GZC20230924"]}]},{"name":"Science and Technology Major Project of Shanxi Province","award":["IDICP-KF-2024-03"],"award-info":[{"award-number":["IDICP-KF-2024-03"]}]},{"name":"Science and Technology Major Project of Shanxi Province","award":["2024AFB245"],"award-info":[{"award-number":["2024AFB245"]}]},{"name":"Science and Technology Major Project of Shanxi Province","award":["202201020101006"],"award-info":[{"award-number":["202201020101006"]}]},{"name":"Science and Technology Major Project of Shanxi Province","award":["CCNU24XJ005"],"award-info":[{"award-number":["CCNU24XJ005"]}]},{"name":"Self-determined Research Funds of CCNU from the Colleges\u2019 basic Research and Operation of MOE","award":["62373233"],"award-info":[{"award-number":["62373233"]}]},{"name":"Self-determined Research Funds of CCNU from the Colleges\u2019 basic Research and Operation of MOE","award":["62003200"],"award-info":[{"award-number":["62003200"]}]},{"name":"Self-determined Research Funds of CCNU from the Colleges\u2019 basic Research and Operation of MOE","award":["GZC20230924"],"award-info":[{"award-number":["GZC20230924"]}]},{"name":"Self-determined Research Funds of CCNU from the Colleges\u2019 basic Research and Operation of MOE","award":["IDICP-KF-2024-03"],"award-info":[{"award-number":["IDICP-KF-2024-03"]}]},{"name":"Self-determined Research Funds of CCNU from the Colleges\u2019 basic Research and Operation of MOE","award":["2024AFB245"],"award-info":[{"award-number":["2024AFB245"]}]},{"name":"Self-determined Research Funds of CCNU from the Colleges\u2019 basic Research and Operation of MOE","award":["202201020101006"],"award-info":[{"award-number":["202201020101006"]}]},{"name":"Self-determined Research Funds of CCNU from the Colleges\u2019 basic Research and Operation of MOE","award":["CCNU24XJ005"],"award-info":[{"award-number":["CCNU24XJ005"]}]},{"name":"1331 Engineering Project of Shanxi Province","award":["62373233"],"award-info":[{"award-number":["62373233"]}]},{"name":"1331 Engineering Project of Shanxi Province","award":["62003200"],"award-info":[{"award-number":["62003200"]}]},{"name":"1331 Engineering Project of Shanxi Province","award":["GZC20230924"],"award-info":[{"award-number":["GZC20230924"]}]},{"name":"1331 Engineering Project of Shanxi Province","award":["IDICP-KF-2024-03"],"award-info":[{"award-number":["IDICP-KF-2024-03"]}]},{"name":"1331 Engineering Project of Shanxi Province","award":["2024AFB245"],"award-info":[{"award-number":["2024AFB245"]}]},{"name":"1331 Engineering Project of Shanxi Province","award":["202201020101006"],"award-info":[{"award-number":["202201020101006"]}]},{"name":"1331 Engineering Project of Shanxi Province","award":["CCNU24XJ005"],"award-info":[{"award-number":["CCNU24XJ005"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Robots execute diverse load operations, including carrying, lifting, tilting, and moving objects, involving load changes or transfers. This dynamic process can result in the shift of interactive operations from stability to instability. In this paper, we respond to these dynamic changes by utilizing tactile images captured from tactile sensors during interactions, conducting a study on the dynamic stability and instability in operations, and propose a real-time dynamic state sensing network by integrating convolutional neural networks (CNNs) for spatial feature extraction and long short-term memory (LSTM) networks to capture temporal information. We collect a dataset capturing the entire transition from stable to unstable states during interaction. Employing a sliding window, we sample consecutive frames from the collected dataset and feed them into the network for the state change predictions of robots. The network achieves both real-time temporal sequence prediction at 31.84 ms per inference step and an average classification accuracy of 98.90%. Our experiments demonstrate the network\u2019s robustness, maintaining high accuracy even with previously unseen objects.<\/jats:p>","DOI":"10.3390\/s24155080","type":"journal-article","created":{"date-parts":[[2024,8,5]],"date-time":"2024-08-05T18:21:40Z","timestamp":1722882100000},"page":"5080","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Detecting Transitions from Stability to Instability in Robotic Grasping Based on Tactile Perception"],"prefix":"10.3390","volume":"24","author":[{"given":"Zhou","family":"Zhao","sequence":"first","affiliation":[{"name":"School of Computer Science, Central China Normal University, Wuhan 430079, China"},{"name":"Hubei Engineering Research Center for Intelligent Detection and Identification of Complex Parts, Wuhan 430079, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dongyuan","family":"Zheng","sequence":"additional","affiliation":[{"name":"School of Computer Science, Central China Normal University, Wuhan 430079, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2184-8268","authenticated-orcid":false,"given":"Lu","family":"Chen","sequence":"additional","affiliation":[{"name":"Institute of Big Data Science and Industry, School of Computer and Information Technology, Shanxi University, Taiyuan 030006, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2024,8,5]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"eaat8414","DOI":"10.1126\/science.aat8414","article-title":"Trends and challenges in robot manipulation","volume":"364","author":"Billard","year":"2019","journal-title":"Science"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"918","DOI":"10.1109\/TRO.2011.2158251","article-title":"Human-like adaptation of force and impedance in stable and unstable interactions","volume":"27","author":"Yang","year":"2011","journal-title":"IEEE Trans. Robot."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"8541","DOI":"10.1109\/LRA.2023.3330664","article-title":"VERGNet: Visual Enhancement Guided Robotic Grasp Detection under Low-light Condition","volume":"8","author":"Niu","year":"2023","journal-title":"IEEE Robot. Autom. Lett."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"105032","DOI":"10.1016\/j.mechmachtheory.2022.105032","article-title":"Robotic manipulation of thin objects within off-the-shelf parallel grippers with a vibration finger","volume":"177","author":"Nahum","year":"2022","journal-title":"Mech. Mach. Theory"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"1041","DOI":"10.1109\/LRA.2018.2794618","article-title":"Improving industrial grippers with adhesion-controlled friction","volume":"3","author":"Roberge","year":"2018","journal-title":"IEEE Robot. Autom. Lett."},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Kolamuri, R., Si, Z., Zhang, Y., Agarwal, A., and Yuan, W. (October, January 7). Improving grasp stability with rotation measurement from tactile sensing. Proceedings of the 2021 IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS), Prague, Czech Republic.","DOI":"10.1109\/IROS51168.2021.9636488"},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Costanzo, M., De Maria, G., and Natale, C. (2018, January 1\u201325). Slipping control algorithms for object manipulation with sensorized parallel grippers. Proceedings of the 2018 IEEE International Conference on Robotics and Automation (ICRA), Brisbane, QLD, Australia.","DOI":"10.1109\/ICRA.2018.8460883"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"108953","DOI":"10.1016\/j.engappai.2024.108953","article-title":"Touch and slippage detection in robotic hands with spiking neural networks","volume":"136","author":"Follmann","year":"2024","journal-title":"Eng. Appl. Artif. Intell."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"66","DOI":"10.1109\/MRA.2022.3188218","article-title":"Biomimetic Force and Impedance Adaptation Based on Broad Learning System in Stable and Unstable Tasks: Creating an Incremental and Explainable Neural Network With Functional Linkage","volume":"29","author":"Lu","year":"2022","journal-title":"IEEE Robot. Autom. Mag."},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Rubert, C., Kappler, D., Morales, A., Schaal, S., and Bohg, J. (2017, January 24\u201328). On the relevance of grasp metrics for predicting grasp success. Proceedings of the 2017 IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS), Vancouver, BC, Canada.","DOI":"10.1109\/IROS.2017.8202167"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"2282","DOI":"10.1109\/TII.2020.2995142","article-title":"Visual-guided robotic object grasping using dual neural network controllers","volume":"17","author":"Fang","year":"2020","journal-title":"IEEE Trans. Ind. Inform."},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Mandikal, P., and Grauman, K. (June, January 30). Learning dexterous grasping with object-centric visual affordances. Proceedings of the 2021 IEEE International Conference on Robotics and Automation, Xi\u2019an, China.","DOI":"10.1109\/ICRA48506.2021.9561802"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"2405722","DOI":"10.1002\/adfm.202405722","article-title":"Innovations in Tactile Sensing: Microstructural Designs for Superior Flexible Sensor Performance","volume":"2024","author":"Wu","year":"2024","journal-title":"Adv. Funct. Mater."},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Wang, C., Liu, C., Shang, F., Niu, S., Ke, L., Zhang, N., Ma, B., Li, R., Sun, X., and Zhang, S. (2023). Tactile sensing technology in bionic skin: A review. Biosens. Bioelectron., 220.","DOI":"10.1016\/j.bios.2022.114882"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"115332","DOI":"10.1016\/j.measurement.2024.115332","article-title":"Tactile sensors: A review","volume":"238","author":"Meribout","year":"2024","journal-title":"Measurement"},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Yuan, W., Dong, S., and Adelson, E.H. (2017). Gelsight: High-resolution robot tactile sensors for estimating geometry and force. Sensors, 17.","DOI":"10.3390\/s17122762"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"3838","DOI":"10.1109\/LRA.2020.2977257","article-title":"Digit: A novel design for a low-cost compact high-resolution tactile sensor with application to in-hand manipulation","volume":"5","author":"Lambeta","year":"2020","journal-title":"IEEE Robot. Autom. Lett."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"216","DOI":"10.1089\/soro.2017.0052","article-title":"The tactip family: Soft optical tactile sensors with 3d-printed biomimetic morphologies","volume":"5","author":"Pestell","year":"2018","journal-title":"Soft Robot."},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Do, W.K., and Kennedy, M. (2022, January 23\u201327). Densetact: Optical tactile sensor for dense shape reconstruction. Proceedings of the 2022 International Conference on Robotics and Automation (ICRA), Philadelphia, PA, USA.","DOI":"10.1109\/ICRA46639.2022.9811966"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"5982","DOI":"10.1109\/LRA.2023.3302191","article-title":"GelFinger: A novel visual-tactile sensor with multi-angle tactile image stitching","volume":"8","author":"Lin","year":"2023","journal-title":"IEEE Robot. Autom. Lett."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"9049","DOI":"10.1109\/JSEN.2018.2868340","article-title":"Tactile sensors for friction estimation and incipient slip detection\u2014Toward dexterous robotic manipulation: A review","volume":"18","author":"Chen","year":"2018","journal-title":"IEEE Sens. J."},{"key":"ref_22","first-page":"827","article-title":"Robust learning-based incipient slip detection using the papillarray optical tactile sensor for improved robotic gripping","volume":"9","author":"Wang","year":"2023","journal-title":"IEEE Robot. Autom. Lett."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"3340","DOI":"10.1109\/LRA.2018.2852797","article-title":"Slip detection with a biomimetic tactile sensor","volume":"3","author":"James","year":"2018","journal-title":"IEEE Robot. Autom. Lett."},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Veiga, F., Van Hoof, H., Peters, J., and Hermans, T. (October, January 28). Stabilizing novel objects by learning to predict tactile slip. Proceedings of the 2015 IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS), Hamburg, Germany.","DOI":"10.1109\/IROS.2015.7354090"},{"key":"ref_25","unstructured":"Calandra, R., Owens, A., Upadhyaya, M., Yuan, W., Lin, J., Adelson, E.H., and Levine, S. (2017). The feeling of success: Does touch sensing help predict grasp outcomes?. arXiv."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"73027","DOI":"10.1109\/ACCESS.2020.2987849","article-title":"Methods and sensors for slip detection in robotics: A survey","volume":"8","author":"Romeo","year":"2020","journal-title":"IEEE Access"},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Gentile, C., Lunghi, G., Buonocore, L.R., Cordella, F., Di Castro, M., Masi, A., and Zollo, L. (2023). Manipulation tasks in hazardous environments using a teleoperated robot: A case study at cern. Sensors, 23.","DOI":"10.3390\/s23041979"},{"key":"ref_28","unstructured":"Li, H., Zhang, Y., Zhu, J., Wang, S., Lee, M.A., Xu, H., Adelson, E., Fei-Fei, L., Gao, R., and Wu, J. (2022). See, hear, and feel: Smart sensory fusion for robotic manipulation. arXiv."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"509","DOI":"10.1089\/soro.2020.0199","article-title":"A microfabricated dual slip-pressure sensor with compliant polymer-liquid metal nanocomposite for robotic manipulation","volume":"9","author":"Accoto","year":"2022","journal-title":"Soft Robot."},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Xie, Z., Liang, X., and Roberto, C. (2023). Learning-based robotic grasping: A review. Front. Robot. AI, 10.","DOI":"10.3389\/frobt.2023.1038658"},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Mandil, W., Rajendran, V., Nazari, K., and Ghalamzan-Esfahani, A. (2023). Tactile-sensing technologies: Trends, challenges and outlook in agri-food manipulation. Sensors, 23.","DOI":"10.3390\/s23177362"},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Ward-Cherrier, B., Pestell, N., and Lepora, N.F. (August, January 31). Neurotac: A neuromorphic optical tactile sensor applied to texture recognition. Proceedings of the 2020 IEEE International Conference on Robotics and Automation (ICRA), Paris, France.","DOI":"10.1109\/ICRA40945.2020.9197046"},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Sferrazza, C., and D\u2019Andrea, R. (2019). Design, motivation and evaluation of a full-resolution optical tactile sensor. Sensors, 19.","DOI":"10.3390\/s19040928"},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Romero, B., Veiga, F., and Adelson, E. (August, January 31). Soft, round, high resolution tactile fingertip sensors for dexterous robotic manipulation. Proceedings of the 2020 IEEE International Conference on Robotics and Automation (ICRA), Paris, France.","DOI":"10.1109\/ICRA40945.2020.9196909"},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"Padmanabha, A., Ebert, F., Tian, S., Calandra, R., Finn, C., and Levine, S. (August, January 31). Omnitact: A multi-directional high-resolution touch sensor. Proceedings of the 2020 IEEE International Conference on Robotics and Automation (ICRA), Paris, France.","DOI":"10.1109\/ICRA40945.2020.9196712"},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Alspach, A., Hashimoto, K., Kuppuswamy, N., and Tedrake, R. (2020\u201324, January 24). Soft-bubble: A highly compliant dense geometry tactile sensor for robot manipulation. Proceedings of the 2019 2nd IEEE International Conference on Soft Robotics (RoboSoft), Las Vegas, NV, USA.","DOI":"10.1109\/ROBOSOFT.2019.8722713"},{"key":"ref_37","first-page":"390","article-title":"Large-scale vision-based tactile sensing for robot links: Design, modeling, and evaluation","volume":"37","author":"Ho","year":"2020","journal-title":"IEEE Trans. Robot."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"5017810","DOI":"10.1109\/TIM.2024.3386205","article-title":"Flexible Material Quality Assessment Based on Visual-tactile Fusion","volume":"73","author":"Xu","year":"2024","journal-title":"IEEE Trans. Instrum. Meas."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"1499","DOI":"10.1007\/s10439-023-03153-w","article-title":"A reliable and sensitive framework for simultaneous type and stage detection of colorectal cancer polyps","volume":"51","author":"Kara","year":"2023","journal-title":"Ann. Biomed. Eng."},{"key":"ref_40","doi-asserted-by":"crossref","unstructured":"Lin, Y., Zhou, Y., Huang, K., Zhong, Q., Cheng, T., Yang, H., and Yin, Z. (2023). GelSplitter: Tactile Reconstruction from Near Infrared and Visible Images. International Conference on Intelligent Robotics and Applications, Springer.","DOI":"10.1007\/978-981-99-6498-7_2"},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"1599","DOI":"10.1109\/TRO.2021.3111786","article-title":"Proximity perception in human-centered robotics: A survey on sensing systems and applications","volume":"38","author":"Navarro","year":"2021","journal-title":"IEEE Trans. Robot."},{"key":"ref_42","doi-asserted-by":"crossref","unstructured":"Huang, I., and Bajcsy, R. (August, January 31). High resolution soft tactile interface for physical human-robot interaction. Proceedings of the 2020 IEEE International Conference on Robotics and Automation (ICRA), Paris, France.","DOI":"10.1109\/ICRA40945.2020.9197365"},{"key":"ref_43","doi-asserted-by":"crossref","unstructured":"Agarwal, A., Man, T., and Yuan, W. (June, January 30). Simulation of vision-based tactile sensors using physics based rendering. Proceedings of the 2021 IEEE International Conference on Robotics and Automation, Xi\u2019an, China.","DOI":"10.1109\/ICRA48506.2021.9561122"},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"2300042","DOI":"10.1002\/aisy.202300042","article-title":"Minsight: A Fingertip-Sized Vision-Based Tactile Sensor for Robotic Manipulation","volume":"5","author":"Andrussow","year":"2023","journal-title":"Adv. Intell. Syst."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"5384","DOI":"10.1109\/LRA.2023.3295296","article-title":"Visual-Tactile Robot Grasping based on Human Skill Learning from Demonstrations using A Wearable Parallel Hand Exoskeleton","volume":"8","author":"Lu","year":"2023","journal-title":"IEEE Robot. Autom. Lett."},{"key":"ref_46","doi-asserted-by":"crossref","unstructured":"Zhao, Z., and Lu, Z. (2022, January 23\u201327). Multi-purpose Tactile Perception Based on Deep Learning in a New Tendon-driven Optical Tactile Sensor. Proceedings of the 2022 IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS), Kyoto, Japan.","DOI":"10.1109\/IROS47612.2022.9981477"},{"key":"ref_47","unstructured":"Simonyan, K., and Zisserman, A. (2014). Very deep convolutional networks for large-scale image recognition. arXiv."},{"key":"ref_48","doi-asserted-by":"crossref","unstructured":"He, K., Zhang, X., Ren, S., and Sun, J. (2016, January 27\u201330). Deep residual learning for image recognition. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Las Vegas, NV, USA.","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref_49","doi-asserted-by":"crossref","unstructured":"Huang, G., Liu, Z., Van Der Maaten, L., and Weinberger, K.Q. (2017, January 21\u201326). Densely connected convolutional networks. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Honolulu, HI, USA.","DOI":"10.1109\/CVPR.2017.243"},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"106760","DOI":"10.1016\/j.optlastec.2020.106760","article-title":"2D tactile sensor based on multimode interference and deep learning","volume":"136","author":"Ding","year":"2021","journal-title":"Opt. Laser Technol."},{"key":"ref_51","doi-asserted-by":"crossref","unstructured":"Sferrazza, C., Bi, T., and D\u2019Andrea, R. (2020\u201324, January 24). Learning the sense of touch in simulation: A sim-to-real strategy for vision-based tactile sensing. Proceedings of the 2020 IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS), Las Vegas, NV, USA.","DOI":"10.1109\/IROS45743.2020.9341285"},{"key":"ref_52","doi-asserted-by":"crossref","unstructured":"Takahashi, K., and Tan, J. (2019, January 20\u201324). Deep visuo-tactile learning: Estimation of tactile properties from images. Proceedings of the 2019 International Conference on Robotics and Automation (ICRA), Montreal, QC, Canada.","DOI":"10.1109\/ICRA.2019.8794285"},{"key":"ref_53","first-page":"1097","article-title":"Imagenet classification with deep convolutional neural networks","volume":"25","author":"Krizhevsky","year":"2012","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"1735","DOI":"10.1162\/neco.1997.9.8.1735","article-title":"Long short-term memory","volume":"9","author":"Hochreiter","year":"1997","journal-title":"Neural Comput."},{"key":"ref_55","first-page":"5998","article-title":"Attention is all you need","volume":"30","author":"Vaswani","year":"2017","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"2278","DOI":"10.1109\/5.726791","article-title":"Gradient-based learning applied to document recognition","volume":"86","author":"LeCun","year":"1998","journal-title":"Proc. IEEE"},{"key":"ref_57","doi-asserted-by":"crossref","unstructured":"Syed, M.A.B., and Ahmed, I. (2023). A CNN-LSTM Architecture for Marine Vessel Track Association Using Automatic Identification System (AIS) Data. arXiv.","DOI":"10.3390\/s23146400"},{"key":"ref_58","unstructured":"Kingma, D.P., and Ba, J. (2014). Adam: A method for stochastic optimization. arXiv."},{"key":"ref_59","unstructured":"Tan, M., and Le, Q. (2019, January 9\u201315). Efficientnet: Rethinking model scaling for convolutional neural networks. Proceedings of the International Conference on Machine Learning (PMLR, 2019), Long Beach, CA, USA."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/24\/15\/5080\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T15:30:31Z","timestamp":1760110231000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/24\/15\/5080"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,8,5]]},"references-count":59,"journal-issue":{"issue":"15","published-online":{"date-parts":[[2024,8]]}},"alternative-id":["s24155080"],"URL":"https:\/\/doi.org\/10.3390\/s24155080","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,8,5]]}}}