{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,31]],"date-time":"2026-03-31T05:40:59Z","timestamp":1774935659596,"version":"3.50.1"},"reference-count":70,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2023,2,21]],"date-time":"2023-02-21T00:00:00Z","timestamp":1676937600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Science Foundation","award":["CNS-2104742"],"award-info":[{"award-number":["CNS-2104742"]}]},{"name":"National Science Foundation","award":["CNS-2117308"],"award-info":[{"award-number":["CNS-2117308"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Robotics"],"abstract":"<jats:p>Robots are increasingly being employed for diverse applications where they must work and coexist with humans. The trust in human\u2013robot collaboration (HRC) is a critical aspect of any shared-task performance for both the human and the robot. The study of a human-trusting robot has been investigated by numerous researchers. However, a robot-trusting human, which is also a significant issue in HRC, is seldom explored in the field of robotics. Motivated by this gap, we propose a novel trust-assist framework for human\u2013robot co-carry tasks in this study. This framework allows the robot to determine a trust level for its human co-carry partner. The calculations of this trust level are based on human motions, past interactions between the human\u2013robot pair, and the human\u2019s current performance in the co-carry task. The trust level between the human and the robot is evaluated dynamically throughout the collaborative task, and this allows the trust to change if the human performs false positive actions, which can help the robot avoid making unpredictable movements and causing injury to the human. Additionally, the proposed framework can enable the robot to generate and perform assisting movements to follow human-carrying motions and paces when the human is considered trustworthy in the co-carry task. The results of our experiments suggest that the robot effectively assists the human in real-world collaborative tasks through the proposed trust-assist framework.<\/jats:p>","DOI":"10.3390\/robotics12020030","type":"journal-article","created":{"date-parts":[[2023,2,22]],"date-time":"2023-02-22T02:31:55Z","timestamp":1677033115000},"page":"30","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":21,"title":["A Trust-Assist Framework for Human\u2013Robot Co-Carry Tasks"],"prefix":"10.3390","volume":"12","author":[{"given":"Corey","family":"Hannum","sequence":"first","affiliation":[{"name":"Department of Computer Science, Montclair State University, Montclair, NJ 07043, USA"}]},{"given":"Rui","family":"Li","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Montclair State University, Montclair, NJ 07043, USA"}]},{"given":"Weitian","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Montclair State University, Montclair, NJ 07043, USA"}]}],"member":"1968","published-online":{"date-parts":[[2023,2,21]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"916","DOI":"10.1080\/0951192X.2015.1130251","article-title":"Human\u2013robot interaction review and challenges on task planning and programming","volume":"29","author":"Tsarouchi","year":"2016","journal-title":"Int. J. Comput. Integr. Manuf."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1177\/1729881417716010","article-title":"Human\u2013robot collaboration in industrial applications: Safety, interaction and trust","volume":"14","author":"Maurtua","year":"2017","journal-title":"Int. J. Adv. Robot. Syst."},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Shi, J., Jimmerson, G., Pearson, T., and Menassa, R. (2012, January 20\u201322). Levels of human and robot collaboration for automotive manufacturing. Proceedings of the Workshop on Performance Metrics for Intelligent Systems, College Park, MD, USA.","DOI":"10.1145\/2393091.2393111"},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Saupp\u00e9, A. (2014, January 15\u201319). Designing effective strategies for human-robot collaboration. Proceedings of the Companion Publication of the 17th ACM Conference on Computer Supported Cooperative Work & Social Computing, Baltimore, MD, USA.","DOI":"10.1145\/2556420.2556830"},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Dragan, A.D., Bauman, S., Forlizzi, J., and Srinivasa, S.S. (2015, January 2\u20135). Effects of robot motion on human-robot collaboration. Proceedings of the 2015 10th ACM\/IEEE International Conference on Human-Robot Interaction (HRI), Portland, OR, USA.","DOI":"10.1145\/2696454.2696473"},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Wang, W., Li, R., Chen, Y., and Jia, Y. (2018, January 5\u20138). Human Intention Prediction in Human-Robot Collaborative Tasks. Proceedings of the 2018 ACM\/IEEE International Conference on Human-Robot Interaction, Chicago, IL, USA.","DOI":"10.1145\/3173386.3177025"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"1007","DOI":"10.1109\/TMECH.2013.2264533","article-title":"Human\u2013robot collaboration based on motion intention estimation","volume":"19","author":"Li","year":"2013","journal-title":"IEEE\/ASME Trans. Mechatron."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"1933","DOI":"10.1109\/LRA.2017.2714981","article-title":"Optimal task allocation for human\u2013machine collaborative manufacturing systems","volume":"2","author":"Hu","year":"2017","journal-title":"IEEE Robot. Autom. Lett."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"1011","DOI":"10.1007\/s10514-017-9678-1","article-title":"Robot adaptation to human physical fatigue in human\u2013robot co-manipulation","volume":"42","author":"Peternel","year":"2018","journal-title":"Auton. Robot."},{"key":"ref_10","unstructured":"Lynch, K.M., and Liu, C. (2000, January 24\u201328). Designing motion guides for ergonomic collaborative manipulation. Proceedings of the 2000 ICRA, Millennium Conference, IEEE International Conference on Robotics and Automation, Symposia Proceedings (Cat. No. 00CH37065), San Francisco, CA, USA."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"102033","DOI":"10.1016\/j.rcim.2020.102033","article-title":"Human\u2013Robot co-manipulation during surface tooling: A general framework based on impedance control, haptic rendering and discrete geometry","volume":"67","author":"Kana","year":"2021","journal-title":"Robot. Comput.-Integr. Manuf."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"2663","DOI":"10.1007\/s00170-019-03356-3","article-title":"A structured methodology for the design of a human-robot collaborative assembly workplace","volume":"102","author":"Mateus","year":"2019","journal-title":"Int. J. Adv. Manuf. Technol."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"41","DOI":"10.1016\/j.rcim.2018.07.006","article-title":"The effectiveness of virtual environments in developing collaborative strategies between industrial robots and humans","volume":"55","author":"Oyekan","year":"2019","journal-title":"Robot. Comput.-Integr. Manuf."},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Colan, J., Nakanishi, J., Aoyama, T., and Hasegawa, Y. (2020). A Cooperative Human-Robot Interface for Constrained Manipulation in Robot-Assisted Endonasal Surgery. Appl. Sci., 10.","DOI":"10.3390\/app10144809"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"575","DOI":"10.1007\/s12369-017-0415-x","article-title":"Cooperative dynamic manipulation of unknown flexible objects","volume":"9","author":"Donner","year":"2017","journal-title":"Int. J. Soc. Robot."},{"key":"ref_16","unstructured":"Ososky, S., Schuster, D., Phillips, E., and Jentsch, F.G. (2013, January 25\u201327). Building appropriate trust in human-robot teams. Proceedings of the 2013 AAAI Spring Symposium, Palo Alto, CA, USA."},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Ullman, D., Aladia, S., and Malle, B.F. (2021, January 8\u201311). Challenges and opportunities for replication science in HRI: A case study in human-robot trust. Proceedings of the 2021 ACM\/IEEE International Conference on Human-Robot Interaction, Boulder, CO, USA.","DOI":"10.1145\/3434073.3444652"},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Xu, J., and Howard, A. (September, January 29). Evaluating the impact of emotional apology on human-robot trust. Proceedings of the 2022 31st IEEE International Conference on Robot and Human Interactive Communication (RO-MAN), Napoli, Italy.","DOI":"10.1109\/RO-MAN53752.2022.9900518"},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Esterwood, C., and Robert, L.P. (2022, January 7\u201310). Having the Right Attitude: How Attitude Impacts Trust Repair in Human\u2014Robot Interaction. Proceedings of the 2022 17th ACM\/IEEE International Conference on Human-Robot Interaction (HRI), Sapporo, Japan.","DOI":"10.1109\/HRI53351.2022.9889535"},{"key":"ref_20","first-page":"15553434221136358","article-title":"Impact of transparency and explanations on trust and situation awareness in human\u2013robot teams","volume":"17","author":"Ezenyilimba","year":"2022","journal-title":"J. Cogn. Eng. Decis. Mak."},{"key":"ref_21","unstructured":"Malle, B.F., and Ullman, D. (2021). Trust in Human-Robot Interaction, Elsevier."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"107658","DOI":"10.1016\/j.chb.2023.107658","article-title":"Three Strikes and you are out!: The impacts of multiple human-robot trust violations and repairs on robot trustworthiness","volume":"142","author":"Esterwood","year":"2023","journal-title":"Comput. Human Behav."},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Hannum, C., Li, R., and Wang, W. (2020, January 10\u201313). Trust or Not?: A Computational Robot-Trusting-Human Model for Human-Robot Collaborative Tasks. Proceedings of the 2020 IEEE International Conference on Big Data (Big Data), Atlanta, GA, USA.","DOI":"10.1109\/BigData50022.2020.9378119"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"102386","DOI":"10.1016\/j.rcim.2022.102386","article-title":"Deliberative safety for industrial intelligent human\u2013robot collaboration: Regulatory challenges and solutions for taking the next step towards industry 4.0","volume":"78","author":"Hanna","year":"2022","journal-title":"Robot. Comput.-Integr. Manuf."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"107801","DOI":"10.1016\/j.cie.2021.107801","article-title":"Development and validation of guidelines for safety in human-robot collaborative assembly systems","volume":"163","author":"Gualtieri","year":"2022","journal-title":"Comput. Ind. Eng."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"102258","DOI":"10.1016\/j.rcim.2021.102258","article-title":"An integrated mixed reality system for safety-aware human-robot collaboration using deep learning and digital twin generation","volume":"73","author":"Choi","year":"2022","journal-title":"Robot. Comput.-Integr. Manuf."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"04022046","DOI":"10.1061\/(ASCE)CP.1943-5487.0001056","article-title":"Prediction-Based Path Planning for Safe and Efficient Human\u2013Robot Collaboration in Construction via Deep Reinforcement Learning","volume":"37","author":"Cai","year":"2023","journal-title":"J. Comput. Civ. Eng."},{"key":"ref_28","first-page":"1","article-title":"Task allocation model for human-robot collaboration with variable cobot speed","volume":"474","author":"Faccio","year":"2023","journal-title":"J. Intell. Manuf."},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Tariq, U., Muthusamy, R., and Kyrki, V. (2018, January 21\u201325). Grasp planning for load sharing in collaborative manipulation. Proceedings of the 2018 IEEE International Conference on Robotics and Automation (ICRA), Brisbane, Australia.","DOI":"10.1109\/ICRA.2018.8460579"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"640","DOI":"10.1109\/TASE.2018.2840345","article-title":"Facilitating Human\u2013Robot Collaborative Tasks by Teaching-Learning-Collaboration From Human Demonstrations","volume":"16","author":"Wang","year":"2018","journal-title":"IEEE Trans. Autom. Sci. Eng."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"469","DOI":"10.1016\/j.robot.2008.10.024","article-title":"A survey of robot learning from demonstration","volume":"57","author":"Argall","year":"2009","journal-title":"Robot. Auton. Syst."},{"key":"ref_32","unstructured":"Gu, Y., Thobbi, A., and Sheng, W. (2011, January 9\u201313). Human-robot collaborative manipulation through imitation and reinforcement learning. Proceedings of the 2011 IEEE International Conference on Information and Automation, Shanghai, China."},{"key":"ref_33","unstructured":"Arai, H., Takubo, T., Hayashibara, Y., and Tanie, K. (2000, January 24\u201328). Human-robot cooperative manipulation using a virtual nonholonomic constraint. Proceedings of the 2000 ICRA, Millennium Conference, IEEE International Conference on Robotics and Automation. Symposia Proceedings (Cat. No. 00CH37065), San Francisco, CA, USA."},{"key":"ref_34","unstructured":"Cervera, E., del Pobil, A.P., Marta, E., and Serna, M.A. (1995, January 5\u20139). A sensor-based approach for motion in contact in task planning. Proceedings of the 1995 IEEE\/RSJ International Conference on Intelligent Robots and Systems, Human Robot Interaction and Cooperative Robots, Pittsburgh, PA, USA."},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"Kruse, D., Radke, R.J., and Wen, J.T. (2015, January 26\u201330). Collaborative human-robot manipulation of highly deformable materials. Proceedings of the 2015 IEEE International Conference on Robotics and Automation (ICRA), Seattle, DC, USA.","DOI":"10.1109\/ICRA.2015.7139725"},{"key":"ref_36","unstructured":"Demolombe, R. (April, January 29). Reasoning about trust: A formal logical framework. Proceedings of the International Conference on Trust Management, Oxford, UK."},{"key":"ref_37","unstructured":"Wang, Y., Shi, Z., Wang, C., and Zhang, F. (2014). Cooperative Robots and Sensor Networks 2014, Springer."},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"Billings, D.R., Schaefer, K.E., Chen, J.Y., and Hancock, P.A. (2012, January 5\u20138). Human-robot interaction: Developing trust in robots. Proceedings of the seventh annual ACM\/IEEE International Conference on Human-Robot Interaction, Boston, MA, USA.","DOI":"10.1145\/2157689.2157709"},{"key":"ref_39","doi-asserted-by":"crossref","unstructured":"Rossi, A., Dautenhahn, K., Koay, K.L., and Saunders, J. (2017, January 6\u20139). Investigating human perceptions of trust in robots for safe HRI in home environments. Proceedings of the Companion of the 2017 ACM\/IEEE International Conference on Human-Robot Interaction, Vienna, Austria.","DOI":"10.1145\/3029798.3034822"},{"key":"ref_40","unstructured":"Stormont, D.P. (2008, January 13\u201317). Analyzing human trust of autonomous systems in hazardous environments. Proceedings of the Human Implications of Human-Robot Interaction Workshop at AAAI, Chicago, IL, USA."},{"key":"ref_41","doi-asserted-by":"crossref","unstructured":"Freedy, A., DeVisser, E., Weltman, G., and Coeyman, N. (2007, January 21\u201325). Measurement of trust in human-robot collaboration. Proceedings of the 2007 International Symposium on Collaborative Technologies and Systems, Orlando, FL, USA.","DOI":"10.1109\/CTS.2007.4621745"},{"key":"ref_42","doi-asserted-by":"crossref","unstructured":"Chen, M., Nikolaidis, S., Soh, H., Hsu, D., and Srinivasa, S. (2018, January 5\u20138). Planning with trust for human-robot collaboration. Proceedings of the 2018 ACM\/IEEE International Conference on Human-Robot Interaction, Chicago, IL, USA.","DOI":"10.1145\/3171221.3171264"},{"key":"ref_43","doi-asserted-by":"crossref","unstructured":"Kaniarasu, P., Steinfeld, A., Desai, M., and Yanco, H. (2013, January 3\u20136). Robot confidence and trust alignment. Proceedings of the 2013 8th ACM\/IEEE International Conference on Human-Robot Interaction (HRI), Tokyo, Japan.","DOI":"10.1109\/HRI.2013.6483548"},{"key":"ref_44","unstructured":"Basili, P., Huber, M., Brandt, T., Hirche, S., and Glasauer, S. (2009). Human Centered Robot Systems, Springer."},{"key":"ref_45","unstructured":"Lucas, B.D., and Kanade, T. (1981, January 24\u201328). An iterative image registration technique with an application to stereo vision. Proceedings of the 7th International Joint Conference on Artificial Intelligence, San Francisco, CA, USA."},{"key":"ref_46","unstructured":"LaValle, S.M. (2023, February 02). Rapidly-Exploring Random Trees: A New Tool for Path Planning. The Annual Research Report. 1998, 1\u20134. Available online: http:\/\/msl.cs.illinois.edu\/~lavalle\/papers\/Lav98c.pdf."},{"key":"ref_47","first-page":"566","article-title":"Probabilistic Roadmaps for Path Planning in High-Dimensional Configuration Spaces","volume":"1994","author":"Kavraki","year":"1994","journal-title":"IEEE Trans. Robot. Autom."},{"key":"ref_48","unstructured":"Kuffner, J.J., and LaValle, S.M. (2000, January 24\u201328). RRT-connect: An efficient approach to single-query path planning. Proceedings of the Robotics and Automation, 2000, Proceedings ICRA\u201900, San Francisco, CA, USA."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"883","DOI":"10.1177\/0278364915577958","article-title":"Fast marching tree: A fast marching sampling-based method for optimal motion planning in many dimensions","volume":"34","author":"Janson","year":"2015","journal-title":"Int. J. Robot. Res."},{"key":"ref_50","doi-asserted-by":"crossref","unstructured":"Bohlin, R., and Kavraki, L.E. (2000, January 24\u201328). Path planning using lazy PRM. Proceedings of the 2000 ICRA. Millennium Conference, IEEE International Conference on Robotics and Automation, Symposia Proceedings (Cat. No. 00CH37065), San Francisco, CA, USA.","DOI":"10.1109\/ROBOT.2000.844107"},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"495","DOI":"10.1142\/S0218195999000285","article-title":"Path planning in expansive configuration spaces","volume":"9","author":"Hsu","year":"1999","journal-title":"Int. J. Comput. Geom. Appl."},{"key":"ref_52","doi-asserted-by":"crossref","unstructured":"Stilman, M., Schamburek, J.-U., Kuffner, J., and Asfour, T. (2007). Manipulation Planning among Movable Obstacles, Georgia Institute of Technology.","DOI":"10.1109\/ROBOT.2007.363986"},{"key":"ref_53","doi-asserted-by":"crossref","unstructured":"Bier, S., Li, R., and Wang, W. (2020, January 14\u201317). A Full-Dimensional Robot Teleoperation Platform. Proceedings of the 2020 IEEE International Conference on Mechanical and Aerospace Engineering, Athens, Greece.","DOI":"10.1109\/ICMAE50897.2020.9178871"},{"key":"ref_54","doi-asserted-by":"crossref","unstructured":"Quigley, M., Conley, K., Gerkey, B., Faust, J., Foote, T., Leibs, J., Wheeler, R., and Ng, A.Y. (2009, January 12\u201317). ROS: An open-source Robot Operating System. Proceedings of the ICRA Workshop on Open Source Software, Kobe, Japan.","DOI":"10.1109\/MRA.2010.936956"},{"key":"ref_55","doi-asserted-by":"crossref","unstructured":"Diamantopoulos, H., and Wang, W. (2021, January 16\u201319). Accommodating and Assisting Human Partners in Human-Robot Collaborative Tasks through Emotion Understanding. Proceedings of the 2021 International Conference on Mechanical and Aerospace Engineering (ICMAE), Athens, Greece.","DOI":"10.1109\/ICMAE52228.2021.9522451"},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"18","DOI":"10.1109\/MRA.2011.2181749","article-title":"Moveit!","volume":"19","author":"Chitta","year":"2012","journal-title":"IEEE Robot. Autom. Mag."},{"key":"ref_57","unstructured":"(2023, February 02). The Experimental Demo. Available online: https:\/\/www.youtube.com\/watch?v=2sVAmwHPHOc."},{"key":"ref_58","doi-asserted-by":"crossref","unstructured":"B\u00fctepage, J., Kjellstr\u00f6m, H., and Kragic, D. (2017). Anticipating many futures: Online human motion prediction and synthesis for human-robot collaboration. arXiv.","DOI":"10.1109\/ICRA.2018.8460651"},{"key":"ref_59","doi-asserted-by":"crossref","unstructured":"Ding, H., Rei\u00dfig, G., Wijaya, K., Bortot, D., Bengler, K., and Stursberg, O. (2011, January 9\u201313). Human arm motion modeling and long-term prediction for safe and efficient human-robot-interaction. Proceedings of the Robotics and Automation (ICRA), Shanghai, China.","DOI":"10.1109\/ICRA.2011.5980248"},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"856","DOI":"10.1109\/LRA.2017.2655565","article-title":"Adaptive Task Scheduling for an Assembly Task Coworker Robot Based on Incremental Learning of Human\u2019s Motion Patterns","volume":"2","author":"Kinugawa","year":"2017","journal-title":"IEEE Robot. Autom. Lett."},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"591","DOI":"10.1016\/j.robot.2014.01.003","article-title":"Learning intentions for improved human motion prediction","volume":"62","author":"Elfring","year":"2014","journal-title":"Robot. Auton. Syst."},{"key":"ref_62","doi-asserted-by":"crossref","unstructured":"Song, D., Kyriazis, N., Oikonomidis, I., Papazov, C., Argyros, A., Burschka, D., and Kragic, D. (2013, January 6\u201310). Predicting human intention in visual observations of hand\/object interactions. Proceedings of the Robotics and Automation (ICRA), Karlsruhe, Germany.","DOI":"10.1109\/ICRA.2013.6630785"},{"key":"ref_63","doi-asserted-by":"crossref","first-page":"2176","DOI":"10.1109\/TMECH.2022.3175903","article-title":"Analytic Deep Neural Network-Based Robot Control","volume":"27","author":"Nguyen","year":"2022","journal-title":"IEEE\/ASME Trans. Mechatron."},{"key":"ref_64","doi-asserted-by":"crossref","first-page":"108253","DOI":"10.1016\/j.measurement.2020.108253","article-title":"Control framework for cooperative robots in smart home using bio-inspired neural network","volume":"167","author":"Khan","year":"2021","journal-title":"Measurement"},{"key":"ref_65","doi-asserted-by":"crossref","first-page":"193","DOI":"10.1109\/87.486346","article-title":"A fuzzy-Gaussian neural network and its application to mobile robot control","volume":"4","author":"Watanabe","year":"1996","journal-title":"IEEE Trans. Control Syst. Technol."},{"key":"ref_66","doi-asserted-by":"crossref","first-page":"4013","DOI":"10.1109\/TNNLS.2020.3016523","article-title":"Generic neural locomotion control framework for legged robots","volume":"32","author":"Thor","year":"2020","journal-title":"IEEE Trans. Neural Netw. Learn. Syst."},{"key":"ref_67","doi-asserted-by":"crossref","first-page":"54","DOI":"10.1109\/72.896796","article-title":"Neural network-based adaptive controller design of robotic manipulators with an observer","volume":"12","author":"Sun","year":"2001","journal-title":"IEEE Trans. Neural Netw."},{"key":"ref_68","doi-asserted-by":"crossref","first-page":"260","DOI":"10.1016\/j.neucom.2019.04.100","article-title":"A robot learning framework based on adaptive admittance control and generalizable motion modeling with neural network controller","volume":"390","author":"Wang","year":"2020","journal-title":"Neurocomputing"},{"key":"ref_69","doi-asserted-by":"crossref","first-page":"59","DOI":"10.1109\/THMS.2018.2883176","article-title":"Controlling Object Hand-Over in Human\u2013Robot Collaboration Via Natural Wearable Sensing","volume":"49","author":"Wang","year":"2019","journal-title":"IEEE Trans. Hum.-Mach. Syst."},{"key":"ref_70","doi-asserted-by":"crossref","unstructured":"Weiss, K.R., and Khoshgoftaar, T.M. (2016, January 6\u20138). An investigation of transfer learning and traditional machine learning algorithms. Proceedings of the 2016 IEEE 28th International Conference on Tools with Artificial Intelligence (ICTAI), San Jose, CA, USA.","DOI":"10.1109\/ICTAI.2016.0051"}],"container-title":["Robotics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2218-6581\/12\/2\/30\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T18:38:13Z","timestamp":1760121493000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2218-6581\/12\/2\/30"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,2,21]]},"references-count":70,"journal-issue":{"issue":"2","published-online":{"date-parts":[[2023,4]]}},"alternative-id":["robotics12020030"],"URL":"https:\/\/doi.org\/10.3390\/robotics12020030","relation":{},"ISSN":["2218-6581"],"issn-type":[{"value":"2218-6581","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,2,21]]}}}