{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,8]],"date-time":"2026-07-08T15:45:59Z","timestamp":1783525559007,"version":"3.55.0"},"reference-count":47,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2025,12,4]],"date-time":"2025-12-04T00:00:00Z","timestamp":1764806400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Robot. AI"],"abstract":"<jats:p>\n                    Real-time estimation of human action progress is critical for seamless human-robot collaboration yet remains underexplored. With this paper we propose the first real-time application of Open-end Soft-DTW (OS-DTW\n                    <jats:sub>EU<\/jats:sub>\n                    ) and introduce OS-DTW\n                    <jats:sub>WP<\/jats:sub>\n                    , a novel DTW variant that integrates a Windowed-Pearson distance to effectively capture local correlations. This method is embedded in our Proactive Assistance through action-Completion Estimation (PACE) framework, which leverages reinforcement learning to synchronize robotic assistance with human actions by estimating action completion percentages. Experiments on a chair assembly task demonstrate OS-DTW\n                    <jats:sub>WP<\/jats:sub>\n                    \u2019s superiority in capturing local motion patterns and OS-DTW\n                    <jats:sub>EU<\/jats:sub>\n                    \u2019s efficacy in tasks presenting consistent absolute positions. Moreover we validate the PACE framework through user studies involving 12 participants, showing significant improvements in interaction fluency, reduced waiting times, and positive user feedback compared to traditional methods.\n                  <\/jats:p>","DOI":"10.3389\/frobt.2025.1623884","type":"journal-article","created":{"date-parts":[[2025,12,4]],"date-time":"2025-12-04T11:50:33Z","timestamp":1764849033000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":1,"title":["Real-time human progress estimation with online dynamic time warping for collaborative robotics"],"prefix":"10.3389","volume":"12","author":[{"given":"Davide","family":"De Lazzari","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Matteo","family":"Terreran","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Giulio","family":"Giacomuzzo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Siddarth","family":"Jain","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Pietro","family":"Falco","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ruggero","family":"Carli","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Stefano","family":"Ghidoni","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Diego","family":"Romeres","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2025,12,4]]},"reference":[{"key":"B1","first-page":"10341","article-title":"Miniroad: minimal rnn framework for online action detection","volume-title":"Proceedings of the IEEE\/CVF International Conference on Computer Vision (ICCV)","author":"An","year":"2023"},{"key":"B2","doi-asserted-by":"publisher","first-page":"163","DOI":"10.1007\/s41693-022-00072-5","article-title":"Safety, quality, schedule, and cost impacts of ten construction robots","volume":"6","author":"Brosque","year":"2022","journal-title":"Constr. Robot."},{"key":"B3","doi-asserted-by":"publisher","first-page":"1065","DOI":"10.1109\/tase.2013.2274099","article-title":"Optimal subtask allocation for human and robot collaboration within hybrid assembly system","volume":"11","author":"Chen","year":"2013","journal-title":"IEEE Trans. Automation Sci. Eng."},{"key":"B4","doi-asserted-by":"crossref","first-page":"9510","DOI":"10.1109\/ICCV51070.2023.00875","article-title":"Humanmac: masked motion completion for human motion prediction","volume-title":"2023 IEEE\/CVF international conference on computer vision (ICCV)","author":"Chen","year":"2023"},{"key":"B5","doi-asserted-by":"publisher","first-page":"247","DOI":"10.1109\/lra.2021.3124524","article-title":"Long-term trajectory prediction of the human hand and duration estimation of the human action","volume":"7","author":"Cheng","year":"2021","journal-title":"IEEE Robotics Automation Lett."},{"key":"B6","doi-asserted-by":"publisher","first-page":"2602","DOI":"10.1109\/lra.2020.2972874","article-title":"Towards efficient human-robot collaboration with robust plan recognition and trajectory prediction","volume":"5","author":"Cheng","year":"2020","journal-title":"IEEE Robotics Automation Lett."},{"key":"B7","doi-asserted-by":"publisher","first-page":"1136","DOI":"10.1109\/lra.2021.3056370","article-title":"Human-aware robot task planning based on a hierarchical task model","volume":"6","author":"Cheng","year":"2021","journal-title":"IEEE Robotics Automation Lett."},{"key":"B8","doi-asserted-by":"publisher","first-page":"514","DOI":"10.1109\/TPAMI.2024.3466212","article-title":"Infogcn++: learning representation by predicting the future for online skeleton-based action recognition","volume":"47","author":"Chi","year":"2025","journal-title":"IEEE Trans. Pattern Analysis Mach. Intell."},{"key":"B9","first-page":"894","article-title":"Soft-dtw: a differentiable loss function for time-series","volume-title":"International conference on machine learning","author":"Cuturi","year":"2017"},{"key":"B10","doi-asserted-by":"crossref","first-page":"11447","DOI":"10.1109\/ICCV48922.2021.01127","article-title":"Msr-gcn: multi-Scale residual graph convolution networks for human motion prediction","volume-title":"2021 IEEE\/CVF international conference on computer vision (ICCV)","author":"Dang","year":"2021"},{"key":"B11","doi-asserted-by":"crossref","first-page":"6725","DOI":"10.1109\/ICRA55743.2025.11127399","article-title":"Pace: proactive assistance in human-robot collaboration through action-completion estimation","volume-title":"2025 IEEE international conference on robotics and automation (ICRA)","author":"De Lazzari","year":"2025"},{"key":"B12","doi-asserted-by":"publisher","first-page":"348","DOI":"10.1016\/j.robot.2016.09.017","article-title":"Service robotics and human labor: a first technology assessment of substitution and cooperation","volume":"87","author":"Decker","year":"2017","journal-title":"Robotics Aut. Syst."},{"key":"B13","doi-asserted-by":"crossref","first-page":"7085","DOI":"10.1109\/IROS58592.2024.10802728","article-title":"Decaf: a discrete-event based collaborative human-robot framework for furniture assembly","volume-title":"2024 IEEE\/RSJ international conference on intelligent robots and systems (IROS)","author":"Giacomuzzo","year":"2024"},{"key":"B14","doi-asserted-by":"publisher","first-page":"139","DOI":"10.1016\/S0166-4115(08)62386-9","article-title":"Development of nasa-tlx (task load index): results of empirical and theoretical research","volume":"1","author":"Hart","year":"1988","journal-title":"Hum. Ment. workload"},{"key":"B15","doi-asserted-by":"crossref","first-page":"135","DOI":"10.1007\/978-981-15-4095-0_4","article-title":"Deep q-networks","volume-title":"Deep reinforcement learning: fundamentals, research and applications","author":"Huang","year":"2020"},{"key":"B16","doi-asserted-by":"publisher","first-page":"67","DOI":"10.1109\/TASSP.1975.1162641","article-title":"Minimum prediction residual principle applied to speech recognition","volume":"23","author":"Itakura","year":"1975","journal-title":"IEEE Trans. Acoust. Speech, Signal Process."},{"key":"B17","first-page":"1695","article-title":"Spatio-temporal alignments: optimal transport through space and time","volume-title":"Proceedings of the twenty third international conference on artificial intelligence and statistics","author":"Janati","year":"2020"},{"key":"B18","doi-asserted-by":"publisher","first-page":"2231","DOI":"10.1016\/j.patcog.2010.09.022","article-title":"Weighted dynamic time warping for time series classification","volume":"44","author":"Jeong","year":"2011","journal-title":"Pattern Recognit."},{"key":"B19","doi-asserted-by":"publisher","first-page":"99","DOI":"10.1016\/S0004-3702(98)00023-X","article-title":"Planning and acting in partially observable stochastic domains","volume":"101","author":"Kaelbling","year":"1998","journal-title":"Artif. Intell."},{"key":"B20","doi-asserted-by":"publisher","first-page":"21","DOI":"10.1177\/0018720814565188","article-title":"Analyzing the effects of human-aware motion planning on close-proximity human\u2013robot collaboration","volume":"57","author":"Lasota","year":"2015","journal-title":"Hum. factors"},{"key":"B21","volume-title":"Introduction to embedded systems: a cyber-physical systems approach","author":"Lee","year":"2017"},{"key":"B22","first-page":"188","article-title":"Robust task planning for assembly lines with human-robot collaboration","volume-title":"Proceedings of the international symposium on flexible automation 2022 international symposium on flexible automation","author":"Leu","year":"2022"},{"key":"B23","doi-asserted-by":"crossref","first-page":"433","DOI":"10.1109\/IROS40897.2019.8967933","article-title":"Real-time monitoring of human task advancement","volume-title":"2019 IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS)","author":"Maderna","year":"2019"},{"key":"B24","doi-asserted-by":"crossref","first-page":"11094","DOI":"10.1109\/IROS45743.2020.9341131","article-title":"Robust real-time monitoring of human task advancement for collaborative robotics applications","volume-title":"2020 IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS)","author":"Maderna","year":"2020"},{"key":"B25","doi-asserted-by":"publisher","first-page":"137","DOI":"10.1002\/rob.21898","article-title":"Long-duration fully autonomous operation of rotorcraft unmanned aerial systems for remote-sensing data acquisition","volume":"37","author":"Malyuta","year":"2019","journal-title":"J. Field Robotics"},{"key":"B26","doi-asserted-by":"crossref","first-page":"89","DOI":"10.1007\/978-3-031-45725-8_5","article-title":"Partial alignment of time series for action and activity prediction","volume-title":"Computer vision, imaging and computer graphics theory and applications","author":"Manousaki","year":"2023"},{"key":"B27","doi-asserted-by":"crossref","first-page":"474","DOI":"10.1007\/978-3-030-58568-6_28","article-title":"History repeats itself: human motion prediction via motion attention","volume-title":"Computer vision \u2013 ECCV 2020","author":"Mao","year":"2020"},{"key":"B28","first-page":"10181","article-title":"Masked motion predictors are strong 3d action representation learners","volume-title":"Proceedings of the IEEE\/CVF International Conference on Computer Vision","author":"Mao","year":"2023"},{"key":"B29","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1109\/WCSP.2019.8928124","article-title":"Selector-actor-critic and tuner-actor-critic algorithms for reinforcement learning","volume-title":"2019 11th International Conference on Wireless Communications and Signal Processing (WCSP)","author":"Masadeh","year":"2019"},{"key":"B30","doi-asserted-by":"publisher","first-page":"109201","DOI":"10.1016\/j.patcog.2022.109201","article-title":"Deep attentive time warping","volume":"136","author":"Matsuo","year":"2023","journal-title":"Pattern Recognit."},{"key":"B32","doi-asserted-by":"publisher","first-page":"17","DOI":"10.1016\/S0021-9673(98)00021-1","article-title":"Aligning of single and multiple wavelength chromatographic profiles for chemometric data analysis using correlation optimised warping","volume":"805","author":"Nielsen","year":"1998","journal-title":"J. Chromatogr. A"},{"key":"B33","doi-asserted-by":"publisher","first-page":"1","DOI":"10.5555\/3546258.3546526","article-title":"Stable-baselines3: reliable reinforcement learning implementations","volume":"22","author":"Raffin","year":"2021","journal-title":"J. Mach. Learn. Res."},{"key":"B34","doi-asserted-by":"crossref","DOI":"10.1115\/DSCC2015-9850","article-title":"Trust-based optimal subtask allocation and model predictive control for human-robot collaborative assembly in manufacturing","volume-title":"Dynamic Systems and Control Conference","author":"Rahman","year":"2015"},{"key":"B35","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3623387","article-title":"Uhtp: a user-aware hierarchical task planning framework for communication-free, mutually-adaptive human-robot collaboration","volume":"13","author":"Ramachandruni","year":"2023","journal-title":"ACM Trans. Human-Robot Interact."},{"key":"B36","doi-asserted-by":"crossref","first-page":"9690","DOI":"10.1109\/WACV61041.2025.00938","article-title":"Autoregressive adaptive hypergraph transformer for skeleton-based activity recognition","volume-title":"2025 IEEE\/CVF Winter Conference on Applications of Computer Vision (WACV)","author":"Ray","year":"2025"},{"key":"B37","doi-asserted-by":"publisher","first-page":"588","DOI":"10.1109\/TASSP.1979.1163310","article-title":"Two-level dp-matching\u2013a dynamic programming-based pattern matching algorithm for connected word recognition","volume":"27","author":"Sakoe","year":"1979","journal-title":"IEEE Trans. Acoust. Speech, Signal Process."},{"key":"B38","doi-asserted-by":"publisher","first-page":"43","DOI":"10.1109\/TASSP.1978.1163055","article-title":"Dynamic programming algorithm optimization for spoken word recognition","volume":"26","author":"Sakoe","year":"1978","journal-title":"IEEE Trans. Acoust. Speech, Signal Process."},{"key":"B39","doi-asserted-by":"publisher","first-page":"1","DOI":"10.13140\/RG.2.2.22099.07205","article-title":"Xsens mvn: consistent tracking of human motion using inertial sensing","volume":"1","author":"Schepers","year":"2018","journal-title":"Xsens Technol."},{"key":"B40","first-page":"1889","article-title":"Trust region policy optimization","volume-title":"International Conference on Machine Learning","author":"Schulman","year":"2015"},{"key":"B41","article-title":"Proximal policy optimization algorithms","author":"Schulman","year":"2017"},{"key":"B42","doi-asserted-by":"publisher","DOI":"10.5555\/2999325.2999464","article-title":"Practical bayesian optimization of machine learning algorithms","volume":"25","author":"Snoek","year":"2012","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"B44","doi-asserted-by":"publisher","first-page":"231","DOI":"10.1002\/cem.859","article-title":"Correlation optimized warping and dynamic time warping as preprocessing methods for chromatographic data","volume":"18","author":"Tomasi","year":"2004","journal-title":"J. Chemom. A J. Chemom. Soc."},{"key":"B45","doi-asserted-by":"publisher","DOI":"10.5281\/zenodo.11232524","article-title":"Gymnasium (v1.0.0a2)","author":"Towers","year":"2024"},{"key":"B46","doi-asserted-by":"crossref","DOI":"10.1109\/CVPR.2016.552","article-title":"Deep canonical time warping","volume-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)","author":"Trigeorgis","year":"2016"},{"key":"B47","doi-asserted-by":"publisher","first-page":"R737","DOI":"10.1190\/geo2023-0089.1","article-title":"Crosscorrelation-based dynamic time warping and its application in wave equation reflection traveltime inversion","volume":"88","author":"Wang","year":"2023","journal-title":"Geophysics"},{"key":"B48","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v32i1.12328","article-title":"Spatial temporal graph convolutional networks for skeleton-based action recognition","volume":"32","author":"Yan","year":"2018","journal-title":"Proc. AAAI Conf. Artif. Intell."},{"key":"B49","doi-asserted-by":"publisher","first-page":"171","DOI":"10.1016\/j.patcog.2017.09.020","article-title":"Shapedtw: shape dynamic time warping","volume":"74","author":"Zhao","year":"2018","journal-title":"Pattern Recognit."}],"container-title":["Frontiers in Robotics and AI"],"original-title":[],"link":[{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/frobt.2025.1623884\/full","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,12,4]],"date-time":"2025-12-04T11:50:38Z","timestamp":1764849038000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/frobt.2025.1623884\/full"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,12,4]]},"references-count":47,"alternative-id":["10.3389\/frobt.2025.1623884"],"URL":"https:\/\/doi.org\/10.3389\/frobt.2025.1623884","relation":{},"ISSN":["2296-9144"],"issn-type":[{"value":"2296-9144","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,12,4]]},"article-number":"1623884"}}