{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,26]],"date-time":"2026-04-26T09:40:33Z","timestamp":1777196433697,"version":"3.51.4"},"reference-count":163,"publisher":"MDPI AG","issue":"12","license":[{"start":{"date-parts":[[2021,6,15]],"date-time":"2021-06-15T00:00:00Z","timestamp":1623715200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Portugal 2020 ( Competitiveness and Internationalization Operational Program, Lisbon Regional Operational Program, European Regional Development Fund)","award":["POCI-01-0247-FEDER-046103 (Project Augmented Humanity)"],"award-info":[{"award-number":["POCI-01-0247-FEDER-046103 (Project Augmented Humanity)"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Repetitive industrial tasks can be easily performed by traditional robotic systems. However, many other works require cognitive knowledge that only humans can provide. Human-Robot Collaboration (HRC) emerges as an ideal concept of co-working between a human operator and a robot, representing one of the most significant subjects for human-life improvement.The ultimate goal is to achieve physical interaction, where handing over an object plays a crucial role for an effective task accomplishment. Considerable research work had been developed in this particular field in recent years, where several solutions were already proposed. Nonetheless, some particular issues regarding Human-Robot Collaboration still hold an open path to truly important research improvements. This paper provides a literature overview, defining the HRC concept, enumerating the distinct human-robot communication channels, and discussing the physical interaction that this collaboration entails. Moreover, future challenges for a natural and intuitive collaboration are exposed: the machine must behave like a human especially in the pre-grasping\/grasping phases and the handover procedure should be fluent and bidirectional, for an articulated function development. These are the focus of the near future investigation aiming to shed light on the complex combination of predictive and reactive control mechanisms promoting coordination and understanding. Following recent progress in artificial intelligence, learning exploration stand as the key element to allow the generation of coordinated actions and their shaping by experience.<\/jats:p>","DOI":"10.3390\/s21124113","type":"journal-article","created":{"date-parts":[[2021,6,15]],"date-time":"2021-06-15T21:24:29Z","timestamp":1623792269000},"page":"4113","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":90,"title":["Trends of Human-Robot Collaboration in Industry Contexts: Handover, Learning, and Metrics"],"prefix":"10.3390","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9571-9808","authenticated-orcid":false,"given":"Afonso","family":"Castro","sequence":"first","affiliation":[{"name":"Department of Mechanical Engineering (DEM), Institute of Electronics and Informatics Engineering of Aveiro (IEETA), University of Aveiro, 3810-193 Aveiro, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6191-0727","authenticated-orcid":false,"given":"Filipe","family":"Silva","sequence":"additional","affiliation":[{"name":"Department of Electronics, Telecommunications and Informatics (DETI), Institute of Electronics and Informatics Engineering of Aveiro (IEETA), University of Aveiro, 3810-193 Aveiro, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1283-7388","authenticated-orcid":false,"given":"Vitor","family":"Santos","sequence":"additional","affiliation":[{"name":"Department of Mechanical Engineering (DEM), Institute of Electronics and Informatics Engineering of Aveiro (IEETA), University of Aveiro, 3810-193 Aveiro, Portugal"}]}],"member":"1968","published-online":{"date-parts":[[2021,6,15]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Chandrasekaran, B., and Conrad, J.M. (2015, January 9\u201312). Human-robot collaboration: A survey. Proceedings of the SoutheastCon 2015, Fort Lauderdale, FL, USA.","DOI":"10.1109\/SECON.2015.7132964"},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Ajoudani, A., Zanchettin, A.M., Ivaldi, S., Albu-Sch\u00e4ffer, A., Kosuge, K., and Khatib, O. (2018). Progress and Prospects of the Human-Robot Collaboration. Auton. Robot., 42.","DOI":"10.1007\/s10514-017-9677-2"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"764","DOI":"10.1080\/01691864.2019.1636714","article-title":"Human\u2013robot interaction in industrial collaborative robotics: A literature review of the decade 2008\u20132017","volume":"33","author":"Hentout","year":"2019","journal-title":"Adv. Robot."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"162","DOI":"10.1016\/j.robot.2019.03.003","article-title":"Cobot programming for collaborative industrial tasks: An overview","volume":"116","author":"Marei","year":"2019","journal-title":"Robot. Auton. Syst."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"248","DOI":"10.1016\/j.mechatronics.2018.02.009","article-title":"Survey on human-robot collaboration in industrial settings: Safety, intuitive interfaces and applications","volume":"55","author":"Villani","year":"2018","journal-title":"Mechatronics"},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Matheson, E., Minto, R., Zampieri, E.G.G., Faccio, M., and Rosati, G. (2019). Human-Robot Collaboration in Manufacturing Applications: A Review. Robotics, 8.","DOI":"10.3390\/robotics8040100"},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Kumar, S., Savur, C., and Sahin, F. (2021). Survey of Human-Robot Collaboration in Industrial Settings: Awareness, Intelligence, and Compliance. IEEE Trans. Syst. Man Cybern. Syst.","DOI":"10.1109\/TSMC.2020.3041231"},{"key":"ref_8","unstructured":"Ogenyi, U., Liu, J., Yang, C., Ju, Z., and Liu, H. (2019). Physical Human-Robot Collaboration: Robotic Systems, Learning Methods, Collaborative Strategies, Sensors, and Actuators. IEEE Trans. Cybern., 1\u201314."},{"key":"ref_9","first-page":"67","article-title":"Collaborative Systems (AAAI-94 Presidential Address)","volume":"17","author":"Grosz","year":"1996","journal-title":"AI Mag."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"1","DOI":"10.5772\/5664","article-title":"Human-Robot Collaboration: A Literature Review and Augmented Reality Approach in Design","volume":"5","author":"Green","year":"2008","journal-title":"Int. J. Adv. Robot. Syst."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"47","DOI":"10.1142\/S0219843608001303","article-title":"Human-Robot Collaboration: A Survey","volume":"5","author":"Bauer","year":"2008","journal-title":"I. J. Humanoid Robot."},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"De Luca, A., and Flacco, F. (2012, January 24\u201327). Integrated control for pHRI: Collision avoidance, detection, reaction and collaboration. Proceedings of the 2012 4th IEEE RAS EMBS International Conference on Biomedical Robotics and Biomechatronics (BioRob), Rome, Italy.","DOI":"10.1109\/BioRob.2012.6290917"},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Rozo, L., Ben Amor, H., Calinon, S., Dragan, A., and Lee, D. (2018). Special issue on learning for human\u2013robot collaboration. Auton. Robot., 42.","DOI":"10.1007\/s10514-018-9756-z"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"355","DOI":"10.1016\/j.ergon.2017.02.004","article-title":"Gesture recognition for human-robot collaboration: A review","volume":"68","author":"Liu","year":"2018","journal-title":"Int. J. Ind. Ergon."},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Chai, J.Y., She, L., Fang, R., Ottarson, S., Littley, C., Liu, C., and Hanson, K. (2014, January 3\u20136). Collaborative Effort towards Common Ground in Situated Human-Robot Dialogue. Proceedings of the 9th ACM\/IEEE International Conference on Human-Robot Interaction (HRI), Bielefeld, Germany.","DOI":"10.1145\/2559636.2559677"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"1729881417716043","DOI":"10.1177\/1729881417716043","article-title":"Natural multimodal communication for human\u2013robot collaboration","volume":"14","author":"Maurtua","year":"2017","journal-title":"Int. J. Adv. Robot. Syst."},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Coupet\u00e9, E., Moutarde, F., and Manitsaris, S. (2016). A User-Adaptive Gesture Recognition System Applied to Human-Robot Collaboration in Factories. MOCO \u201916: Proceedings of the 3rd International Symposium on Movement and Computing, Association for Computing Machinery.","DOI":"10.1145\/2948910.2948933"},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Peppoloni, L., Brizzi, F., Avizzano, C., and Ruffaldi, E. (2015, January 23\u201324). Immersive ROS-integrated framework for robot teleoperation. Proceedings of the 2015 IEEE Symposium on 3D User Interfaces (3DUI), Arles, France.","DOI":"10.1109\/3DUI.2015.7131758"},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Barattini, P., Morand, C., and Robertson, N.M. (2012, January 9\u201313). A proposed gesture set for the control of industrial collaborative robots. Proceedings of the 2012 IEEE RO-MAN: The 21st IEEE International Symposium on Robot and Human Interactive Communication, Paris, France.","DOI":"10.1109\/ROMAN.2012.6343743"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"311","DOI":"10.1109\/TSMCC.2007.893280","article-title":"Gesture Recognition: A Survey","volume":"37","author":"Mitra","year":"2007","journal-title":"IEEE Trans. Syst. Man Cybern. Part C (Appl. Rev.)"},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Akkaladevi, S.C., and Heindl, C. (2015, January 2\u20133). Action recognition for human robot interaction in industrial applications. Proceedings of the 2015 IEEE International Conference on Computer Graphics, Vision and Information Security (CGVIS), Bhubaneswar, India.","DOI":"10.1109\/CGVIS.2015.7449900"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"345","DOI":"10.1080\/01691864.2014.1003096","article-title":"Understanding the intention of human activities through semantic perception: Observation, understanding and execution on a humanoid robot","volume":"29","author":"Beetz","year":"2015","journal-title":"Adv. Robot."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"396","DOI":"10.1016\/j.procir.2017.03.126","article-title":"Human-robot Collaboration Demonstrator Combining Speech Recognition and Haptic Control","volume":"63","author":"Gustavsson","year":"2017","journal-title":"Procedia CIRP"},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Kragic, D., Gustafson, J., Karaoguz, H., Jensfelt, P., and Krug, R. (2018, January 13\u201319). Interactive, Collaborative Robots: Challenges and Opportunities. Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, IJCAI-18, Stockholm, Sweden.","DOI":"10.24963\/ijcai.2018\/3"},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Stenmark, M., and Nugues, P. (2013, January 24\u201326). Natural language programming of industrial robots. Proceedings of the 2013 44th International Symposium on Robotics, ISR 2013, Seoul, Korea.","DOI":"10.1109\/ISR.2013.6695630"},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Nakata, S., Kobayashi, H., Kumata, M., and Suzuki, S. (2011, January 19\u201321). Human speech ontology changes in virtual collaborative work. Proceedings of the 4th International Conference on Human System Interaction, HSI 2011, Yokohama, Japan.","DOI":"10.1109\/HSI.2011.5937393"},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Yamaguchi, A., and Atkeson, C.G. (2016, January 15\u201317). Combining finger vision and optical tactile sensing: Reducing and handling errors while cutting vegetables. Proceedings of the 2016 IEEE-RAS 16th International Conference on Humanoid Robots (Humanoids), Cancun, Mexico.","DOI":"10.1109\/HUMANOIDS.2016.7803400"},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Kawasetsu, T., Horii, T., Ishihara, H., and Asada, M. (2018). Mexican-Hat-Like Response in a Flexible Tactile Sensor Using a Magnetorheological Elastomer. Sensors, 18.","DOI":"10.3390\/s18020587"},{"key":"ref_29","unstructured":"Kaboli, M., and Cheng, G. (2016, January 15\u201317). Novel Tactile Descriptors and a Tactile Transfer Learning Technique for Active In-Hand Object Recognition via Texture Properties. Proceedings of the IEE-RAS International Conference on Humanoid Robots-Workshop Tactile Sensing for Manipulation: New Progress and Challenges, Cancun, Mexico."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"985","DOI":"10.1109\/TRO.2018.2830364","article-title":"Robust Tactile Descriptors for Discriminating Objects From Textural Properties via Artificial Robotic Skin","volume":"34","author":"Kaboli","year":"2018","journal-title":"IEEE Trans. Robot."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"329","DOI":"10.1109\/TASE.2017.2743000","article-title":"Interface Design of a Physical Human\u2013Robot Interaction System for Human Impedance Adaptive Skill Transfer","volume":"15","author":"Yang","year":"2018","journal-title":"IEEE Trans. Autom. Sci. Eng."},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Mangukiya, Y., Purohit, B., and George, K. (2017, January 13\u201315). Electromyography(EMG) sensor controlled assistive orthotic robotic arm for forearm movement. Proceedings of the 2017 IEEE Sensors Applications Symposium (SAS), Glassboro, NJ, USA.","DOI":"10.1109\/SAS.2017.7894065"},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Faidallah, E.M., Hossameldin, Y.H., Abd Rabbo, S.M., and El-Mashad, Y.A. (2014, January 9\u201311). Control and modeling a robot arm via EMG and flex signals. Proceedings of the 15th International Workshop on Research and Education in Mechatronics (REM), El Gouna, Egypt.","DOI":"10.1109\/REM.2014.6920226"},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Tzallas, A.T., Giannakeas, N., Zoulis, K.N., Tsipouras, M.G., Glavas, E., Tzimourta, K.D., Astrakas, L.G., and Konitsiotis, S. (2017, January 22\u201324). EEG Classification and Short-Term Epilepsy Prognosis Using Brain Computer Interface Software. Proceedings of the 2017 IEEE 30th International Symposium on Computer-Based Medical Systems (CBMS), Thessaloniki, Greece.","DOI":"10.1109\/CBMS.2017.97"},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"Guerin, K.R., Riedel, S.D., Bohren, J., and Hager, G.D. (2014, January 14\u201318). Adjutant: A framework for flexible human-machine collaborative systems. Proceedings of the 2014 IEEE\/RSJ International Conference on Intelligent Robots and Systems, Chicago, IL, USA.","DOI":"10.1109\/IROS.2014.6942739"},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Pedersen, M.R., Herzog, D.L., and Kr\u00fcger, V. (2014, January 14\u201318). Intuitive skill-level programming of industrial handling tasks on a mobile manipulator. Proceedings of the 2014 IEEE\/RSJ International Conference on Intelligent Robots and Systems, Chicago, IL, USA.","DOI":"10.1109\/IROS.2014.6943203"},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"1362","DOI":"10.1109\/LRA.2018.2798300","article-title":"RAZER\u2014A HRI for Visual Task-Level Programming and Intuitive Skill Parameterization","volume":"3","author":"Steinmetz","year":"2018","journal-title":"IEEE Robot. Autom. Lett."},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"Kr\u00fcger, J., Lien, T.K., and Verl, A. (2009). Cooperation of human and machines in assembly lines. CIRP Ann. Manuf. Technol.","DOI":"10.1016\/j.cirp.2009.09.009"},{"key":"ref_39","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_40","doi-asserted-by":"crossref","first-page":"26754","DOI":"10.1109\/ACCESS.2017.2773127","article-title":"Working Together: A Review on Safe Human-Robot Collaboration in Industrial Environments","volume":"5","author":"Becerra","year":"2017","journal-title":"IEEE Access"},{"key":"ref_41","doi-asserted-by":"crossref","unstructured":"Bi, Z.M., Luo, M., Miao, Z., Zhang, B., Zhang, W.J., and Wang, L. (2021). Safety assurance mechanisms of collaborative robotic systems in manufacturing. Robot. Comput. Integr. Manuf.","DOI":"10.1016\/j.rcim.2020.102022"},{"key":"ref_42","doi-asserted-by":"crossref","unstructured":"Gualtieri, L., Rauch, E., and Vidoni, R. (2021). Emerging research fields in safety and ergonomics in industrial collaborative robotics: A systematic literature review. Robot. Comput. Integr. Manuf.","DOI":"10.1016\/j.rcim.2020.101998"},{"key":"ref_43","doi-asserted-by":"crossref","unstructured":"Valori, M., Scibilia, A., Fassi, I., Saenz, J., Behrens, R., Herbster, S., Bidard, C., Lucet, E., Magisson, A., and Schaake, L. (2021). Validating safety in human-robot collaboration: Standards and new perspectives. Robotics, 10.","DOI":"10.3390\/robotics10020065"},{"key":"ref_44","doi-asserted-by":"crossref","unstructured":"Zanchettin, A.M., Ceriani, N.M., Rocco, P., Ding, H., and Matthias, B. (2016). Safety in Human-Robot Collaborative Manufacturing Environments: Metrics and Control. IEEE Trans. Autom. Sci. Eng.","DOI":"10.1109\/TASE.2015.2412256"},{"key":"ref_45","doi-asserted-by":"crossref","unstructured":"Mauro, S., Scimmi, L.S., and Pastorelli, S. (2017, January 21\u201323). Collision Avoidance System for Collaborative Robotics. Proceedings of the International Conference on Robotics in Alpe-Adria Danube Region, Turin, Italy.","DOI":"10.1007\/978-3-319-61276-8_38"},{"key":"ref_46","doi-asserted-by":"crossref","unstructured":"Ragaglia, M., Zanchettin, A.M., and Rocco, P. (2018). Trajectory generation algorithm for safe human-robot collaboration based on multiple depth sensor measurements. Mechatronics.","DOI":"10.1016\/j.mechatronics.2017.12.009"},{"key":"ref_47","unstructured":"Scimmi, L.S., Melchiorre, M., Mauro, S., and Pastorelli, S. (2018, January 29\u201331). Multiple collision avoidance between human limbs and robot links algorithm in collaborative tasks. Proceedings of the 15th International Conference on Informatics in Control, Automation and Robotics, Porto, Portugal."},{"key":"ref_48","doi-asserted-by":"crossref","unstructured":"Kanazawa, A., Kinugawa, J., and Kosuge, K. (2019). Adaptive Motion Planning for a Collaborative Robot Based on Prediction Uncertainty to Enhance Human Safety and Work Efficiency. IEEE Trans. Robot.","DOI":"10.1109\/TRO.2019.2911800"},{"key":"ref_49","doi-asserted-by":"crossref","unstructured":"Melchiorre, M., Scimmi, L.S., Pastorelli, S.P., and Mauro, S. (2019, January 23\u201326). Collison Avoidance using Point Cloud Data Fusion from Multiple Depth Sensors: A Practical Approach. Proceedings of the 2019 23rd International Conference on Mechatronics Technology, ICMT, Salerno, Italy.","DOI":"10.1109\/ICMECT.2019.8932143"},{"key":"ref_50","doi-asserted-by":"crossref","unstructured":"Nikolakis, N., Maratos, V., and Makris, S. (2019). A cyber physical system (CPS) approach for safe human-robot collaboration in a shared workplace. Robot. Comput. Integr. Manuf.","DOI":"10.1016\/j.rcim.2018.10.003"},{"key":"ref_51","doi-asserted-by":"crossref","unstructured":"Scimmi, L.S., Melchiorre, M., Mauro, S., and Pastorelli, S.P. (2019, January 23\u201326). Implementing a Vision-Based Collision Avoidance Algorithm on a UR3 Robot. Proceedings of the 2019 23rd International Conference on Mechatronics Technology, ICMT, Salerno, Italy.","DOI":"10.1109\/ICMECT.2019.8932105"},{"key":"ref_52","doi-asserted-by":"crossref","unstructured":"Zanchettin, A.M., Rocco, P., Chiappa, S., and Rossi, R. (2019). Towards an optimal avoidance strategy for collaborative robots. Robot. Comput. Integr. Manuf.","DOI":"10.1016\/j.rcim.2019.01.015"},{"key":"ref_53","doi-asserted-by":"crossref","unstructured":"Huber, G., and Wollherr, D. (2020). An Online Trajectory Generator on SE(3) for Human-Robot Collaboration. Robotica.","DOI":"10.1017\/S0263574719001619"},{"key":"ref_54","doi-asserted-by":"crossref","unstructured":"Liu, Z., Wang, X., Cai, Y., Xu, W., Liu, Q., Zhou, Z., and Pham, D.T. (2020). Dynamic risk assessment and active response strategy for industrial human-robot collaboration. Comput. Ind. Eng.","DOI":"10.1016\/j.cie.2020.106302"},{"key":"ref_55","doi-asserted-by":"crossref","unstructured":"Murali, P.K., Darvish, K., and Mastrogiovanni, F. (2020). Deployment and evaluation of a flexible human-robot collaboration model based on AND\/OR graphs in a manufacturing environment. Intell. Serv. Robot.","DOI":"10.1007\/s11370-020-00332-9"},{"key":"ref_56","doi-asserted-by":"crossref","unstructured":"Liu, H., and Wang, L. (2021). Collision-free human-robot collaboration based on context awareness. Robot. Comput. Integr. Manuf.","DOI":"10.1016\/j.rcim.2020.101997"},{"key":"ref_57","doi-asserted-by":"crossref","unstructured":"Pupa, A., Arrfou, M., Andreoni, G., and Secchi, C. (2021). A Safety-Aware Kinodynamic Architecture for Human-Robot Collaboration. IEEE Robot. Autom. Lett.","DOI":"10.1109\/LRA.2021.3068634"},{"key":"ref_58","doi-asserted-by":"crossref","unstructured":"Scimmi, L.S., Melchiorre, M., Troise, M., Mauro, S., and Pastorelli, S. (2021). A practical and effective layout for a safe human-robot collaborative assembly task. Appl. Sci., 11.","DOI":"10.3390\/app11041763"},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"4121","DOI":"10.1109\/JSEN.2013.2279056","article-title":"Directions Toward Effective Utilization of Tactile Skin: A Review","volume":"13","author":"Dahiya","year":"2013","journal-title":"IEEE Sens. J."},{"key":"ref_60","doi-asserted-by":"crossref","unstructured":"Bj\u00f6rkman, M., Bekiroglu, Y., H\u00f6gman, V., and Kragic, D. (2013, January 3\u20137). Enhancing visual perception of shape through tactile glances. Proceedings of the 2013 IEEE\/RSJ International Conference on Intelligent Robots and Systems, Tokyo, Japan.","DOI":"10.1109\/IROS.2013.6696808"},{"key":"ref_61","doi-asserted-by":"crossref","unstructured":"Li, M., Bekiroglu, Y., Kragic, D., and Billard, A. (2014, January 14\u201318). Learning of grasp adaptation through experience and tactile sensing. Proceedings of the 2014 IEEE\/RSJ International Conference on Intelligent Robots and Systems, Chicago, IL, USA.","DOI":"10.1109\/IROS.2014.6943027"},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"2625","DOI":"10.1109\/JSEN.2017.2674965","article-title":"Non-Invasive Stimulation-Based Tactile Sensation for Upper-Extremity Prosthesis: A Review","volume":"17","author":"Li","year":"2017","journal-title":"IEEE Sens. J."},{"key":"ref_63","doi-asserted-by":"crossref","unstructured":"Gienger, M., Ruiken, D., Bates, T., Regaieg, M., MeiBner, M., Kober, J., Seiwald, P., and Hildebrandt, A. (2018, January 1\u20135). Human-Robot Cooperative Object Manipulation with Contact Changes. Proceedings of the 2018 IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS), Madrid, Spain.","DOI":"10.1109\/IROS.2018.8594140"},{"key":"ref_64","doi-asserted-by":"crossref","first-page":"880","DOI":"10.1109\/TRO.2016.2572698","article-title":"A Model for Human\u2013Human Collaborative Object Manipulation and Its Application to Human\u2013Robot Interaction","volume":"32","author":"Noohi","year":"2016","journal-title":"IEEE Trans. Robot."},{"key":"ref_65","doi-asserted-by":"crossref","unstructured":"Magrini, E., Flacco, F., and De Luca, A. (2015, January 26\u201330). Control of generalized contact motion and force in physical human-robot interaction. Proceedings of the 2015 IEEE International Conference on Robotics and Automation (ICRA), Seattle, WA, USA.","DOI":"10.1109\/ICRA.2015.7139504"},{"key":"ref_66","doi-asserted-by":"crossref","first-page":"333","DOI":"10.1016\/j.automatica.2008.08.021","article-title":"Human\u2013robot collaboration in precise positioning of a three-dimensional object","volume":"45","author":"Wojtara","year":"2009","journal-title":"Automatica"},{"key":"ref_67","doi-asserted-by":"crossref","unstructured":"Roy, S., and Edan, Y. (2018). Investigating joint-action in short-cycle repetitive handover tasks: The role of giver versus receiver and its implications for human-robot collaborative system design. Int. J. Soc. Robot.","DOI":"10.1007\/s12369-017-0424-9"},{"key":"ref_68","doi-asserted-by":"crossref","unstructured":"Kupcsik, A., Hsu, D., and Lee, W.S. (2018). Learning Dynamic Robot-to-Human Object Handover from Human Feedback. Robotics Research: Volume 1, Springer.","DOI":"10.1007\/978-3-319-51532-8_10"},{"key":"ref_69","doi-asserted-by":"crossref","first-page":"1642","DOI":"10.1109\/LRA.2020.2969200","article-title":"Benchmark for human-to-robot handovers of unseen containers with unknown filling","volume":"5","author":"Chatzilygeroudis","year":"2020","journal-title":"IEEE Robot. Autom. Lett."},{"key":"ref_70","doi-asserted-by":"crossref","first-page":"112","DOI":"10.5898\/JHRI.2.1.Strabala","article-title":"Toward Seamless Human-Robot Handovers","volume":"2","author":"Strabala","year":"2013","journal-title":"J. Hum. Robot Interact."},{"key":"ref_71","doi-asserted-by":"crossref","unstructured":"Kshirsagar, A., Kress-Gazit, H., and Hoffman, G. (2019, January 3\u20138). Specifying and Synthesizing Human-Robot Handovers. Proceedings of the IEEE International Conference on Intelligent Robots and Systems, Macau, China.","DOI":"10.1109\/IROS40897.2019.8967709"},{"key":"ref_72","doi-asserted-by":"crossref","unstructured":"Medina, J.R., Duvallet, F., Karnam, M., and Billard, A. (2016, January 15\u201317). A human-inspired controller for fluid human-robot handovers. Proceedings of the 2016 IEEE-RAS 16th International Conference on Humanoid Robots (Humanoids), Cancun, Mexico.","DOI":"10.1109\/HUMANOIDS.2016.7803296"},{"key":"ref_73","doi-asserted-by":"crossref","unstructured":"Chan, W.P., Pan, M.K., Croft, E.A., and Inaba, M. (2020). An Affordance and Distance Minimization Based Method for Computing Object Orientations for Robot Human Handovers. Int. J. Soc. Robot.","DOI":"10.1007\/s12369-019-00546-7"},{"key":"ref_74","doi-asserted-by":"crossref","unstructured":"van Hoof, H., Hermans, T., Neumann, G., and Peters, J. (2015, January 3\u20135). Learning robot in-hand manipulation with tactile features. Proceedings of the 2015 IEEE-RAS 15th International Conference on Humanoid Robots (Humanoids), Seoul, Korea.","DOI":"10.1109\/HUMANOIDS.2015.7363524"},{"key":"ref_75","doi-asserted-by":"crossref","unstructured":"Rasch, R., Wachsmuth, S., and Konig, M. (2019, January 3\u20138). An Evaluation of Robot-to-Human Handover Configurations for Commercial Robots. Proceedings of the IEEE International Conference on Intelligent Robots and Systems, Macau, China.","DOI":"10.1109\/IROS40897.2019.8967882"},{"key":"ref_76","doi-asserted-by":"crossref","unstructured":"Nemlekar, H., Dutia, D., and Li, Z. (2019, January 20\u201324). Object Transfer Point Estimation for Fluent Human-Robot Handovers. Proceedings of the 2019 International Conference on Robotics and Automation (ICRA), Montreal, QC, Canada.","DOI":"10.1109\/ICRA.2019.8794008"},{"key":"ref_77","doi-asserted-by":"crossref","first-page":"593","DOI":"10.1007\/s10514-016-9556-2","article-title":"Probabilistic movement primitives for coordination of multiple human-robot collaborative tasks","volume":"41","author":"Maeda","year":"2017","journal-title":"Auton. Robot."},{"key":"ref_78","doi-asserted-by":"crossref","unstructured":"Suay, H.B., and Sisbot, E.A. (2015, January 26\u201330). A position generation algorithm utilizing a biomechanical model for robot-human object handover. Proceedings of the 2015 IEEE International Conference on Robotics and Automation (ICRA), Seattle, WA, USA.","DOI":"10.1109\/ICRA.2015.7139724"},{"key":"ref_79","doi-asserted-by":"crossref","unstructured":"Pan, M.K.X.J., Knoop, E., B\u00e4cher, M., and Niemeyer, G. (2019, January 3\u20138). Fast Handovers with a Robot Character: Small Sensorimotor Delays Improve Perceived Qualities. Proceedings of the 2019 IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS), Macau, China.","DOI":"10.1109\/IROS40897.2019.8967614"},{"key":"ref_80","doi-asserted-by":"crossref","unstructured":"Moon, A., Troniak, D.M., Gleeson, B., Pan, M.K., Zheng, M., Blumer, B.A., MacLean, K., and Croft, E.A. (2014). Meet Me Where i\u2019m Gazing: How Shared Attention Gaze Affects Human-Robot Handover Timing. HRI \u201914: Proceedings of the 2014 ACM\/IEEE International Conference on Human-Robot Interaction, Association for Computing Machinery.","DOI":"10.1145\/2559636.2559656"},{"key":"ref_81","doi-asserted-by":"crossref","unstructured":"Kshirsagar, A., Lim, M., Christian, S., and Hoffman, G. (2020). Robot Gaze Behaviors in Human-to-Robot Handovers. IEEE Robot. Autom. Lett.","DOI":"10.1109\/LRA.2020.3015692"},{"key":"ref_82","doi-asserted-by":"crossref","unstructured":"Bestick, A., Pandya, R., Bajcsy, R., and Dragan, A.D. (2018, January 21\u201325). Learning Human Ergonomic Preferences for Handovers. Proceedings of the 2018 IEEE International Conference on Robotics and Automation (ICRA), Brisbane, QLD, Australia.","DOI":"10.1109\/ICRA.2018.8461216"},{"key":"ref_83","doi-asserted-by":"crossref","unstructured":"Rasch, R., Wachsmuth, S., and K\u00f6nig, M. (2018, January 6\u20139). A Joint Motion Model for Human-Like Robot-Human Handover. Proceedings of the 2018 IEEE-RAS 18th International Conference on Humanoid Robots (Humanoids), Beijing, China.","DOI":"10.1109\/HUMANOIDS.2018.8624967"},{"key":"ref_84","doi-asserted-by":"crossref","unstructured":"Huang, C.M., Cakmak, M., and Mutlu, B. (2015). Adaptive Coordination Strategies for Human-Robot Handovers. Robotics: Science and Systems, Springer.","DOI":"10.15607\/RSS.2015.XI.031"},{"key":"ref_85","doi-asserted-by":"crossref","unstructured":"Melchiorre, M., Scimmi, L.S., Mauro, S., and Pastorelli, S. (2018, January 29\u201331). Influence of human limb motion speed in a collaborative hand-over task. Proceedings of the 15th International Conference on Informatics in Control, Automation and Robotics, Porto, Portugal.","DOI":"10.5220\/0006864703490356"},{"key":"ref_86","doi-asserted-by":"crossref","unstructured":"Duarte, N.F., Chatzilygeroudis, K., Santos-Victor, J., and Billard, A. (2020, January 26\u201330). From human action understanding to robot action execution: how the physical properties of handled objects modulate non-verbal cues. Proceedings of the 2020 Joint IEEE 10th International Conference on Development and Learning and Epigenetic Robotics (ICDL-EpiRob), Valparaiso, Chile.","DOI":"10.1109\/ICDL-EpiRob48136.2020.9278084"},{"key":"ref_87","doi-asserted-by":"crossref","unstructured":"Yang, W., Paxton, C., Cakmak, M., and Fox, D. (2020). Human Grasp Classification for Reactive Human-to-Robot Handovers. arXiv.","DOI":"10.1109\/IROS45743.2020.9341004"},{"key":"ref_88","doi-asserted-by":"crossref","unstructured":"Yang, W., Paxton, C., Mousavian, A., Chao, Y.W., Cakmak, M., and Fox, D. (2020). Reactive Human-to-Robot Handovers of Arbitrary Objects. arXiv.","DOI":"10.1109\/ICRA48506.2021.9561170"},{"key":"ref_89","doi-asserted-by":"crossref","first-page":"17","DOI":"10.1109\/LRA.2020.3026970","article-title":"Object-Independent Human-to-Robot Handovers Using Real Time Robotic Vision","volume":"6","author":"Rosenberger","year":"2021","journal-title":"IEEE Robot. Autom. Lett."},{"key":"ref_90","doi-asserted-by":"crossref","unstructured":"Parastegari, S., Noohi, E., Abbasi, B., and \u017defran, M. (2016, January 16\u201321). A fail-safe object handover controller. Proceedings of the 2016 IEEE International Conference on Robotics and Automation (ICRA), Stockholm, Sweden.","DOI":"10.1109\/ICRA.2016.7487346"},{"key":"ref_91","doi-asserted-by":"crossref","unstructured":"Pan, M.K., Croft, E.A., and Niemeyer, G. (2018, January 25\u201328). Exploration of geometry and forces occurring within human-to-robot handovers. Proceedings of the 2018 IEEE Haptics Symposium (HAPTICS), San Francisco, CA, USA.","DOI":"10.1109\/HAPTICS.2018.8357196"},{"key":"ref_92","doi-asserted-by":"crossref","unstructured":"Han, Z., and Yanco, H. (2019, January 11\u201314). The Effects of Proactive Release Behaviors during Human-Robot Handovers. Proceedings of the ACM\/IEEE International Conference on Human-Robot Interaction, Daegu, Korea.","DOI":"10.1109\/HRI.2019.8673085"},{"key":"ref_93","doi-asserted-by":"crossref","unstructured":"Wang, W., Chen, Y., Li, R., and Jia, Y. (2019). Learning and Comfort in Human-Robot Interaction: A Review. Appl. Sci., 9.","DOI":"10.3390\/app9235152"},{"key":"ref_94","doi-asserted-by":"crossref","first-page":"513","DOI":"10.1109\/TRO.2016.2540623","article-title":"Learning physical collaborative robot behaviors from human demonstrations","volume":"32","author":"Rozo","year":"2016","journal-title":"IEEE Trans. Robot."},{"key":"ref_95","unstructured":"Lee, J. (2017). A survey of robot learning from demonstrations for human-robot collaboration. arXiv."},{"key":"ref_96","unstructured":"Fishman, A., Paxton, C., Yang, W., Ratliff, N., and Fox, D. (2019). Trajectory optimization for coordinated human-robot collaboration. arXiv."},{"key":"ref_97","doi-asserted-by":"crossref","first-page":"287","DOI":"10.1016\/j.jmsy.2017.04.009","article-title":"Human motion prediction for human-robot collaboration","volume":"44","author":"Liu","year":"2017","journal-title":"J. Manuf. Syst."},{"key":"ref_98","doi-asserted-by":"crossref","unstructured":"B\u00fctepage, J., Black, M.J., Kragic, D., and Kjellstr\u00f6m, H. (2017, January 21\u201326). Deep Representation Learning for Human Motion Prediction and Classification. Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Honolulu, HI, USA.","DOI":"10.1109\/CVPR.2017.173"},{"key":"ref_99","doi-asserted-by":"crossref","unstructured":"Papageorgiou, X.S., Chalvatzaki, G., Tzafestas, C.S., and Maragos, P. (October, January 28). Hidden markov modeling of human pathological gait using laser range finder for an assisted living intelligent robotic walker. Proceedings of the 2015 IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS), Hamburg, Germany.","DOI":"10.1109\/IROS.2015.7354283"},{"key":"ref_100","doi-asserted-by":"crossref","first-page":"991","DOI":"10.1109\/TRO.2007.904899","article-title":"Affective State Estimation for Human\u2013Robot Interaction","volume":"23","author":"Kulic","year":"2007","journal-title":"IEEE Trans. Robot."},{"key":"ref_101","doi-asserted-by":"crossref","first-page":"421","DOI":"10.1177\/0278364917710318","article-title":"Learning hand-eye coordination for robotic grasping with deep learning and large-scale data collection","volume":"37","author":"Levine","year":"2018","journal-title":"Int. J. Robot. Res."},{"key":"ref_102","unstructured":"Calinon, S., Evrard, P., Gribovskaya, E., Billard, A., and Kheddar, A. (2009, January 22\u201326). Learning collaborative manipulation tasks by demonstration using a haptic interface. Proceedings of the 2009 International Conference on Advanced Robotics, Munich, Germany."},{"key":"ref_103","doi-asserted-by":"crossref","first-page":"1327","DOI":"10.1007\/s10514-018-9705-x","article-title":"A human inspired handover policy using Gaussian Mixture Models and haptic cues","volume":"43","author":"Sidiropoulos","year":"2019","journal-title":"Auton. Robot."},{"key":"ref_104","doi-asserted-by":"crossref","first-page":"1103","DOI":"10.1007\/s10514-017-9674-5","article-title":"Efficient behavior learning in human\u2013robot collaboration","volume":"42","author":"Munzer","year":"2018","journal-title":"Auton. Robot."},{"key":"ref_105","doi-asserted-by":"crossref","first-page":"1023","DOI":"10.1007\/s10514-017-9676-3","article-title":"Human robot cooperation with compliance adaptation along the motion trajectory","volume":"42","author":"Nemec","year":"2018","journal-title":"Auton. Robot."},{"key":"ref_106","doi-asserted-by":"crossref","unstructured":"Rajeswaran, A., Kumar, V., Gupta, A., Vezzani, G., Schulman, J., Todorov, E., and Levine, S. (2017). Learning complex dexterous manipulation with deep reinforcement learning and demonstrations. arXiv.","DOI":"10.15607\/RSS.2018.XIV.049"},{"key":"ref_107","doi-asserted-by":"crossref","unstructured":"Murphy, R.R., and Schreckenghost, D. (2013, January 3\u20136). Survey of metrics for human-robot interaction. Proceedings of the 2013 8th ACM\/IEEE International Conference on Human-Robot Interaction (HRI), Tokyo, Japan.","DOI":"10.1109\/HRI.2013.6483569"},{"key":"ref_108","doi-asserted-by":"crossref","unstructured":"Shi, C., Shiomi, M., Smith, C., Kanda, T., and Ishiguro, H. (2013, January 24\u201328). A Model of Distributional Handing Interaction for a Mobile Robot. Proceedings of the Robotics: Science and Systems, Berlin, Germany.","DOI":"10.15607\/RSS.2013.IX.055"},{"key":"ref_109","doi-asserted-by":"crossref","unstructured":"Koene, A., Endo, S., Remazeilles, A., Prada, M., and Wing, A.M. (2014, January 25\u201329). Experimental testing of the CogLaboration prototype system for fluent Human-Robot object handover interactions. Proceedings of the 23rd IEEE International Symposium on Robot and Human Interactive Communication, Edinburgh, UK.","DOI":"10.1109\/ROMAN.2014.6926261"},{"key":"ref_110","doi-asserted-by":"crossref","first-page":"209","DOI":"10.1109\/THMS.2019.2904558","article-title":"Evaluating Fluency in Human-Robot Collaboration","volume":"49","author":"Hoffman","year":"2019","journal-title":"IEEE Trans. Hum. Mach. Syst."},{"key":"ref_111","doi-asserted-by":"crossref","unstructured":"Gervasi, R., Mastrogiacomo, L., and Franceschini, F. (2020). A conceptual framework to evaluate human-robot collaboration. Int. J. Adv. Manuf. Technol.","DOI":"10.1007\/s00170-020-05363-1"},{"key":"ref_112","doi-asserted-by":"crossref","unstructured":"Ortenzi, V., Cosgun, A., Pardi, T., Chan, W., Croft, E., and Kulic, D. (2020). Object handovers: A review for robotics. arXiv.","DOI":"10.1109\/TRO.2021.3075365"},{"key":"ref_113","doi-asserted-by":"crossref","unstructured":"Choi, Y.S., Chen, T., Jain, A., Anderson, C., Glass, J.D., and Kemp, C.C. (2009, January 14\u201318). Hand it over or set it down: A user study of object delivery with an assistive mobile manipulator. Proceedings of the RO-MAN 2009-The 18th IEEE International Symposium on Robot and Human Interactive Communication, New Delhi, India.","DOI":"10.1109\/ROMAN.2009.5326254"},{"key":"ref_114","unstructured":"Micelli, V., Strabala, K., and Srinivasa, S. Perception and Control Challenges for Effective Human-Robot Handoffs. In Proceedings of RSS 2011 RGB-D Workshop. Available online: https:\/\/www.ri.cmu.edu\/pub_files\/2011\/6\/2011%20-%20Micelli,%20Strabala,%20Srinivasa%20-%20Perception%20and%20Control%20Challenges%20for%20Effective%20Human-Robot%20Handoffs.pdf."},{"key":"ref_115","doi-asserted-by":"crossref","unstructured":"Prada, M., Remazeilles, A., Koene, A., and Endo, S. (2014, January 14\u201318). Implementation and experimental validation of dynamic movement primitives for object handover. Proceedings of the 2014 IEEE\/RSJ International Conference on Intelligent Robots and Systems, Chicago, IL, USA.","DOI":"10.1109\/IROS.2014.6942851"},{"key":"ref_116","doi-asserted-by":"crossref","first-page":"971","DOI":"10.1177\/0278364913488806","article-title":"A human-inspired object handover controller","volume":"32","author":"Chan","year":"2013","journal-title":"Int. J. Robot. Res."},{"key":"ref_117","doi-asserted-by":"crossref","unstructured":"Konstantinova, J., Krivic, S., Stilli, A., Piater, J., and Althoefer, K. (2017). Autonomous object handover using wrist tactile information. Annual Conference Towards Autonomous Robotic Systems, Springer.","DOI":"10.1007\/978-3-319-64107-2_35"},{"key":"ref_118","doi-asserted-by":"crossref","unstructured":"Cakmak, M., Srinivasa, S.S., Lee, M.K., Kiesler, S., and Forlizzi, J. (2011, January 6\u20139). Using spatial and temporal contrast for fluent robot-human hand-overs. Proceedings of the 6th International Conference on Human-Robot Interaction, Lausanne, Switzerland.","DOI":"10.1145\/1957656.1957823"},{"key":"ref_119","doi-asserted-by":"crossref","unstructured":"Bohren, J., Rusu, R.B., Jones, E.G., Marder-Eppstein, E., Pantofaru, C., Wise, M., M\u00f6senlechner, L., Meeussen, W., and Holzer, S. (2011, January 9\u201313). Towards autonomous robotic butlers: Lessons learned with the PR2. Proceedings of the 2011 IEEE International Conference on Robotics and Automation, Shanghai, China.","DOI":"10.1109\/ICRA.2011.5980058"},{"key":"ref_120","doi-asserted-by":"crossref","unstructured":"Grigore, E.C., Eder, K., Pipe, A.G., Melhuish, C., and Leonards, U. (2013, January 3\u20137). Joint action understanding improves robot-to-human object handover. Proceedings of the 2013 IEEE\/RSJ International Conference on Intelligent Robots and Systems, Tokyo, Japan.","DOI":"10.1109\/IROS.2013.6697021"},{"key":"ref_121","doi-asserted-by":"crossref","first-page":"653","DOI":"10.1007\/s12369-014-0241-3","article-title":"An affordance sensitive system for robot to human object handover","volume":"6","author":"Aleotti","year":"2014","journal-title":"Int. J. Soc. Robot."},{"key":"ref_122","doi-asserted-by":"crossref","unstructured":"Cakmak, M., Srinivasa, S.S., Lee, M.K., Forlizzi, J., and Kiesler, S. (2011, January 25\u201330). Human preferences for robot-human hand-over configurations. Proceedings of the 2011 IEEE\/RSJ International Conference on Intelligent Robots and Systems, San Francisco, CA, USA.","DOI":"10.1109\/IROS.2011.6048340"},{"key":"ref_123","doi-asserted-by":"crossref","first-page":"3363","DOI":"10.1007\/s00221-018-5381-5","article-title":"Humans adjust their grip force when passing an object according to the observed speed of the partner\u2019s reaching out movement","volume":"236","author":"Controzzi","year":"2018","journal-title":"Exp. Brain Res."},{"key":"ref_124","doi-asserted-by":"crossref","first-page":"785","DOI":"10.1016\/j.apergo.2010.12.005","article-title":"Physiological and subjective evaluation of a human\u2013robot object hand-over task","volume":"42","author":"Dehais","year":"2011","journal-title":"Appl. Ergon."},{"key":"ref_125","doi-asserted-by":"crossref","unstructured":"Bestick, A., Bajcsy, R., and Dragan, A.D. (2016). Implicitly assisting humans to choose good grasps in robot to human handovers. International Symposium on Experimental Robotics, Springer.","DOI":"10.1007\/978-3-319-50115-4_30"},{"key":"ref_126","unstructured":"Koene, A., Remazeilles, A., Prada, M., Garzo, A., Puerto, M., Endo, S., and Wing, A.M. (2014, January 1\u20134). Relative importance of spatial and temporal precision for user satisfaction in human-robot object handover interactions. Proceedings of the Third International Symposium on New Frontiers in Human-Robot Interaction, London, UK."},{"key":"ref_127","doi-asserted-by":"crossref","unstructured":"Aleotti, J., Micelli, V., and Caselli, S. (2012, January 9\u201313). Comfortable robot to human object hand-over. Proceedings of the 2012 IEEE RO-MAN: The 21st IEEE International Symposium on Robot and Human Interactive Communication, Paris, France.","DOI":"10.1109\/ROMAN.2012.6343845"},{"key":"ref_128","doi-asserted-by":"crossref","unstructured":"Chen, M., Soh, H., Hsu, D., Nikolaidis, S., and Srinivasa, S. (2020). Trust-aware decision making for human-robot collaboration: Model learning and planning. ACM Trans. Hum. Robot. Interact.","DOI":"10.1145\/3359616"},{"key":"ref_129","doi-asserted-by":"crossref","unstructured":"Cooper, S., Fensome, S.F., Kourtis, D., Gow, S., and Dragone, M. (2020, January 7\u20139). An EEG investigation on planning human-robot handover tasks. Proceedings of the 2020 IEEE International Conference on Human-Machine Systems, ICHMS, Rome, Italy.","DOI":"10.1109\/ICHMS49158.2020.9209543"},{"key":"ref_130","doi-asserted-by":"crossref","unstructured":"Meissner, A., Tr\u00fcbswetter, A., Conti-Kufner, A.S., and Schmidtler, J. (2020). Friend or Foe Understanding Assembly Workers\u2019 Acceptance of Human-robot Collaboration. ACM Trans. Hum. Robot. Interact.","DOI":"10.1145\/3399433"},{"key":"ref_131","doi-asserted-by":"crossref","unstructured":"Tang, K.H., Ho, C.F., Mehlich, J., and Chen, S.T. (2020). Assessment of handover prediction models in estimation of cycle times for manual assembly tasks in a human-robot collaborative environment. Appl. Sci., 10.","DOI":"10.3390\/app10020556"},{"key":"ref_132","doi-asserted-by":"crossref","unstructured":"Costanzo, M., De Maria, G., and Natale, C. (2021). Handover Control for Human-Robot and Robot-Robot Collaboration. Front. Robot. AI.","DOI":"10.3389\/frobt.2021.672995"},{"key":"ref_133","doi-asserted-by":"crossref","unstructured":"He, W., Li, J., Yan, Z., and Chen, F. (2021). Bidirectional Human-Robot Bimanual Handover of Big Planar Object With Vertical Posture. IEEE Trans. Autom. Sci. Eng.","DOI":"10.1109\/TASE.2020.3043480"},{"key":"ref_134","doi-asserted-by":"crossref","unstructured":"Melchiorre, M., Scimmi, L.S., Mauro, S., and Pastorelli, S.P. (2021). Vision-based control architecture for human\u00e2\u20ac\u201crobot hand-over applications. Asian J. Control.","DOI":"10.1002\/asjc.2480"},{"key":"ref_135","first-page":"235","article-title":"A human-inspired control strategy: A framework for seamless human-robot handovers","volume":"43","author":"Sutiphotinun","year":"2020","journal-title":"J. Mech. Eng. Res. Dev."},{"key":"ref_136","doi-asserted-by":"crossref","unstructured":"Neranon, P., and Sutiphotinun, T. (2021). A Human-Inspired Control Strategy for Improving Seamless Robot-To-Human Handovers. Appl. Sci., 11.","DOI":"10.3390\/app11104437"},{"key":"ref_137","doi-asserted-by":"crossref","unstructured":"Riccio, F., Capobianco, R., and Nardi, D. (2016, January 15\u201317). Learning human-robot handovers through \u03c0-STAM: Policy improvement with spatio-temporal affordance maps. Proceedings of the IEEE-RAS International Conference on Humanoid Robots, Cancun, Mexico.","DOI":"10.1109\/HUMANOIDS.2016.7803373"},{"key":"ref_138","doi-asserted-by":"crossref","unstructured":"Liu, H., Fang, T., Zhou, T., Wang, Y., and Wang, L. (2018). Deep Learning-based Multimodal Control Interface for Human-Robot Collaboration. Procedia CIRP.","DOI":"10.1016\/j.procir.2018.03.224"},{"key":"ref_139","doi-asserted-by":"crossref","unstructured":"Zhao, X., Chumkamon, S., Duan, S., Rojas, J., and Pan, J. (2018, January 6\u20139). Collaborative Human-Robot Motion Generation Using LSTM-RNN. Proceedings of the IEEE-RAS International Conference on Humanoid Robots, Beijing, China.","DOI":"10.1109\/HUMANOIDS.2018.8625068"},{"key":"ref_140","doi-asserted-by":"crossref","unstructured":"Chen, X., Wang, N., Cheng, H., and Yang, C. (2020). Neural Learning Enhanced Variable Admittance Control for Human-Robot Collaboration. IEEE Access.","DOI":"10.1109\/ACCESS.2020.2969085"},{"key":"ref_141","doi-asserted-by":"crossref","unstructured":"Roveda, L., Maskani, J., Franceschi, P., Abdi, A., Braghin, F., Molinari Tosatti, L., and Pedrocchi, N. (2020). Model-Based Reinforcement Learning Variable Impedance Control for Human-Robot Collaboration. J. Intell. Robot. Syst. Theory Appl.","DOI":"10.1007\/s10846-020-01183-3"},{"key":"ref_142","doi-asserted-by":"crossref","unstructured":"Kshirsagar, A., Hoffman, G., and Biess, A. (2021). Evaluating guided policy search for human-robot handovers. IEEE Robot. Autom. Lett.","DOI":"10.1109\/LRA.2021.3067299"},{"key":"ref_143","unstructured":"Goodfellow, I., Bengio, Y., and Courville, A. (2016). Deep Learning, MIT Press."},{"key":"ref_144","doi-asserted-by":"crossref","first-page":"821","DOI":"10.1080\/01691864.2017.1365009","article-title":"Deep learning in robotics: A review of recent research","volume":"31","author":"Pierson","year":"2017","journal-title":"Adv. Robot."},{"key":"ref_145","doi-asserted-by":"crossref","first-page":"436","DOI":"10.1038\/nature14539","article-title":"Deep Learning","volume":"521","author":"LeCun","year":"2015","journal-title":"Nature"},{"key":"ref_146","doi-asserted-by":"crossref","unstructured":"Halevy, A., Norvig, P., and Pereira, F. (2009). The unreasonable effectiveness of data. IEEE Intell. Syst.","DOI":"10.1109\/MIS.2009.36"},{"key":"ref_147","doi-asserted-by":"crossref","unstructured":"S\u00fcnderhauf, N., Brock, O., Scheirer, W., Hadsell, R., Fox, D., Leitner, J., Upcroft, B., Abbeel, P., Burgard, W., and Milford, M. (2018). The limits and potentials of deep learning for robotics. Int. J. Robot. Res.","DOI":"10.1177\/0278364918770733"},{"key":"ref_148","doi-asserted-by":"crossref","unstructured":"Sutton, R., and Barto, A. (1998). Reinforcement Learning: An Introduction, MIT Press.","DOI":"10.1109\/TNN.1998.712192"},{"key":"ref_149","doi-asserted-by":"crossref","unstructured":"Wiering, M., and van Otterlo, M. (2012). Reinforcement Learning: State-of-the-Art, Elsevier.","DOI":"10.1007\/978-3-642-27645-3"},{"key":"ref_150","doi-asserted-by":"crossref","unstructured":"Kober, J., Bagnell, J.A., and Peters, J. (2013). Reinforcement learning in robotics: A survey. Int. J. Robot. Res.","DOI":"10.1007\/978-3-319-03194-1_2"},{"key":"ref_151","first-page":"1334","article-title":"End-to-End Training of Deep Visuomotor Policies","volume":"17","author":"Levine","year":"2016","journal-title":"J. Mach. Learn. Res."},{"key":"ref_152","doi-asserted-by":"crossref","unstructured":"Zhu, H., Gupta, A., Rajeswaran, A., Levine, S., and Kumar, V. (2019, January 20\u201324). Dexterous manipulation with deep reinforcement learning: Efficient, general, and low-cost. Proceedings of the IEEE International Conference on Robotics and Automation, Montreal, QC, Canada.","DOI":"10.1109\/ICRA.2019.8794102"},{"key":"ref_153","doi-asserted-by":"crossref","unstructured":"Hua, J., Zeng, L., Li, G., and Ju, Z. (2021). Learning for a robot: Deep reinforcement learning, imitation learning, transfer learning. Sensors, 21.","DOI":"10.3390\/s21041278"},{"key":"ref_154","doi-asserted-by":"crossref","unstructured":"Mahler, J., Matl, M., Satish, V., Danielczuk, M., DeRose, B., McKinley, S., and Goldberg, K. (2019). Learning ambidextrous robot grasping policies. Sci. Robot.","DOI":"10.1126\/scirobotics.aau4984"},{"key":"ref_155","doi-asserted-by":"crossref","unstructured":"Lake, B.M., Ullman, T.D., Tenenbaum, J.B., and Gershman, S.J. (2017). Building machines that learn and think like people. Behav. Brain Sci.","DOI":"10.1017\/S0140525X16001837"},{"key":"ref_156","doi-asserted-by":"crossref","unstructured":"Bohg, J., Hausman, K., Sankaran, B., Brock, O., Kragic, D., Schaal, S., and Sukhatme, G.S. (2017). Interactive perception: Leveraging action in perception and perception in action. IEEE Trans. Robot.","DOI":"10.1109\/TRO.2017.2721939"},{"key":"ref_157","first-page":"1","article-title":"A review of robot learning for manipulation: Challenges, representations, and algorithms","volume":"22","author":"Kroemer","year":"2021","journal-title":"J. Mach. Learn. Res."},{"key":"ref_158","unstructured":"Ahmed, O., Tr\u00e4uble, F., Goyal, A., Neitz, A., W\u00fctrich, M., Bengio, Y., Sch\u00f6lkopf, B., and Bauer, S. (2020). CausalWorld: A Robotic Manipulation Benchmark for Causal Structure and Transfer Learning. arXiv."},{"key":"ref_159","first-page":"238","article-title":"The relevance of causation in robotics: A review, categorization, and analysis","volume":"12","year":"2021","journal-title":"J. Behav. Robot."},{"key":"ref_160","doi-asserted-by":"crossref","unstructured":"Weiss, K., Khoshgoftaar, T.M., and Wang, D.D. (2016). A survey of transfer learning. J. Big Data.","DOI":"10.1186\/s40537-016-0043-6"},{"key":"ref_161","unstructured":"Devin, C., Gupta, A., Darrell, T., Abbeel, P., and Levine, S. (June, January 29). Learning modular neural network policies for multi-task and multi-robot transfer. Proceedings of the IEEE International Conference on Robotics and Automation, Singapore."},{"key":"ref_162","doi-asserted-by":"crossref","unstructured":"Hochreiter, S., Younger, A.S., and Conwell, P.R. (2001). Learning to learn using gradient descent. International Conference on Artificial Neural Networks, Springer.","DOI":"10.1007\/3-540-44668-0_13"},{"key":"ref_163","doi-asserted-by":"crossref","unstructured":"Wang, J.X., Kurth-Nelson, Z., Kumaran, D., Tirumala, D., Soyer, H., Leibo, J.Z., Hassabis, D., and Botvinick, M. (2018). Prefrontal cortex as a meta-reinforcement learning system. Nat. 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