{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,13]],"date-time":"2026-04-13T19:35:42Z","timestamp":1776108942018,"version":"3.50.1"},"reference-count":87,"publisher":"Annual Reviews","issue":"1","license":[{"start":{"date-parts":[[2024,7,10]],"date-time":"2024-07-10T00:00:00Z","timestamp":1720569600000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024,7,10]]},"abstract":"<jats:p>Researchers in human\u2013robot collaboration have extensively studied methods for inferring human intentions and predicting their actions, as this is an important precursor for robots to provide useful assistance. We review contemporary methods for intention inference and human activity prediction. Our survey finds that intentions and goals are often inferred via Bayesian posterior estimation and Markov decision processes that model internal human states as unobserved variables or represent both agents in a shared probabilistic framework. An alternative approach is to use neural networks and other supervised learning approaches to directly map observable outcomes to intentions and to make predictions about future human activity based on past observations. That said, due to the complexity of human intentions, existing work usually reasons about limited domains, makes unrealistic simplifications about intentions, and is mostly constrained to short-term predictions. This state of the art provides opportunity for future research that could include more nuanced models of intents, reason over longer horizons, and account for the human tendency to adapt.<\/jats:p>","DOI":"10.1146\/annurev-control-071223-105834","type":"journal-article","created":{"date-parts":[[2023,11,29]],"date-time":"2023-11-29T16:08:42Z","timestamp":1701274122000},"page":"73-95","source":"Crossref","is-referenced-by-count":35,"title":["Inferring Human Intent and Predicting Human Action in Human\u2013Robot Collaboration"],"prefix":"10.1146","volume":"7","author":[{"given":"Guy","family":"Hoffman","sequence":"first","affiliation":[{"name":"1Sibley School of Mechanical and Aerospace Engineering, Cornell University, Ithaca, New York, USA; email: hoffman@cornell.edu"}]},{"given":"Tapomayukh","family":"Bhattacharjee","sequence":"additional","affiliation":[{"name":"2Department of Computer Science, Cornell University, Ithaca, New York, USA"}]},{"given":"Stefanos","family":"Nikolaidis","sequence":"additional","affiliation":[{"name":"3Thomas Lord Department of Computer Science, University of Southern California, Los Angeles, California, USA"}]}],"member":"22","reference":[{"issue":"2","key":"B1","first-page":"67","article-title":"Collaborative systems (AAAI-94 Presidential Address)","volume":"17","year":"1996","journal-title":"AI Mag"},{"key":"B2","article-title":"Collaboration in human-robot teams","year":"2004","journal-title":"AIAA 1st Intelligent Systems Technical Conference"},{"issue":"5","key":"B3","doi-asserted-by":"crossref","first-page":"952","DOI":"10.1109\/TRO.2007.907483","article-title":"Cost-based anticipatory action selection for human\u2013robot fluency","volume":"23","year":"2007","journal-title":"IEEE Trans. Robot."},{"key":"B4","first-page":"3381","article-title":"Effects of integrated intent recognition and communication on human-robot collaboration","year":"2018","journal-title":"2018 IEEE\/RSJ International Conference on Intelligent Robots and Systems"},{"issue":"4","key":"B5","doi-asserted-by":"crossref","first-page":"259","DOI":"10.1007\/s43154-020-00019-0","article-title":"A survey of mental modeling techniques in human\u2013robot teaming","volume":"1","year":"2020","journal-title":"Curr. Robot. 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Robot."},{"key":"B17","first-page":"157","article-title":"MIND MELD: personalized meta-learning for robot-centric imitation learning","year":"2022","journal-title":"HRI '22: Proceedings of the 2022 ACM\/IEEE International Conference on Human-Robot Interaction"},{"key":"B18","first-page":"6948","article-title":"Model predictive control with Gaussian processes for flexible multi-modal physical human robot interaction","year":"2022","journal-title":"2022 International Conference on Robotics and Automation"},{"key":"B19","first-page":"10238","article-title":"A hierarchical finite-state machine-based task allocation framework for human-robot collaborative assembly tasks","year":"2022","journal-title":"2022 IEEE\/RSJ International Conference on Intelligent Robots and Systems"},{"key":"B20","first-page":"243","article-title":"Resolving conflicts during human-robot co-manipulation","year":"2023","journal-title":"HRI '23: Proceedings of the 2023 ACM\/IEEE International Conference on Human-Robot Interaction"},{"issue":"1","key":"B21","first-page":"2","article-title":"Probabilistic human intent recognition for shared autonomy in assistive robotics","volume":"9","year":"2019","journal-title":"ACM Trans. Human-Robot Interact."},{"issue":"4","key":"B22","doi-asserted-by":"crossref","first-page":"7397","DOI":"10.1109\/LRA.2021.3098950","article-title":"Reconfigurable constraint-based reactive framework for assistive robotics with adaptable levels of autonomy","volume":"6","year":"2021","journal-title":"IEEE Robot. Autom. Lett."},{"key":"B23","first-page":"2747","article-title":"I know what you meant: learning human objectives by (under)estimating their choice set","year":"2021","journal-title":"2021 IEEE International Conference on Robotics and Automation"},{"issue":"2","key":"B24","doi-asserted-by":"crossref","first-page":"2387","DOI":"10.1109\/LRA.2020.2970676","article-title":"People\u2019s adaptive side-by-side model evolved to accompany groups of people by social robots","volume":"5","year":"2020","journal-title":"IEEE Robot. Autom. Lett."},{"key":"B25","first-page":"603","article-title":"Nudging or waiting? 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Human-Robot Interact."},{"key":"B62","first-page":"45","article-title":"Predicting individual human performance in human-robot teaming","year":"2021","journal-title":"2021 30th IEEE International Conference on Robot and Human Interactive Communication"},{"key":"B63","article-title":"Modeling human helpfulness with individual and contextual factors for robot planning","year":"2021","journal-title":"Robotics: Science and Systems XVII"},{"issue":"2","key":"B64","doi-asserted-by":"crossref","first-page":"2178","DOI":"10.1109\/LRA.2022.3143520","article-title":"A dynamic task allocation strategy to mitigate the human physical fatigue in collaborative robotics","volume":"7","year":"2022","journal-title":"IEEE Robot. Autom. 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