{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,30]],"date-time":"2025-12-30T08:58:52Z","timestamp":1767085132108,"version":"3.37.3"},"reference-count":56,"publisher":"Springer Science and Business Media LLC","issue":"4","license":[{"start":{"date-parts":[[2021,7,8]],"date-time":"2021-07-08T00:00:00Z","timestamp":1625702400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2021,7,8]],"date-time":"2021-07-08T00:00:00Z","timestamp":1625702400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Complex Intell. Syst."],"published-print":{"date-parts":[[2022,8]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>Remote center of motion (RCM) constraint has attracted many research interests as one of the key challenges for robot-assisted minimally invasive surgery (RAMIS). Although it has been addressed by many studies, few of them treated the motion constraint with an independent workspace solution, which means they rely on the kinematics of the robot manipulator. This makes it difficult to replicate the solutions on other manipulators, which limits their population. In this paper, we propose a novel control framework by incorporating model predictive control (MPC) with the fuzzy approximation to improve the accuracy under the motion constraint. The fuzzy approximation is introduced to manage the kinematic uncertainties existing in the MPC control. Finally, simulations were performed and analyzed to validate the proposed algorithm. By comparison, the results prove that the proposed algorithm achieved success and satisfying performance in the presence of external disturbances.<\/jats:p>","DOI":"10.1007\/s40747-021-00418-6","type":"journal-article","created":{"date-parts":[[2021,7,8]],"date-time":"2021-07-08T20:02:20Z","timestamp":1625774540000},"page":"2883-2895","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["Incorporating model predictive control with fuzzy approximation for robot manipulation under remote center of motion constraint"],"prefix":"10.1007","volume":"8","author":[{"given":"Hang","family":"Su","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2382-6097","authenticated-orcid":false,"given":"Junhao","family":"Zhang","sequence":"additional","affiliation":[]},{"given":"Ziyu","family":"She","sequence":"additional","affiliation":[]},{"given":"Xin","family":"Zhang","sequence":"additional","affiliation":[]},{"given":"Ke","family":"Fan","sequence":"additional","affiliation":[]},{"given":"Xiu","family":"Zhang","sequence":"additional","affiliation":[]},{"given":"Qingsheng","family":"Liu","sequence":"additional","affiliation":[]},{"given":"Giancarlo","family":"Ferrigno","sequence":"additional","affiliation":[]},{"given":"Elena","family":"De Momi","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2021,7,8]]},"reference":[{"key":"418_CR1","first-page":"5","volume":"2020","author":"C Yang","year":"2020","unstructured":"Yang C, Huang D, He W, Cheng L (2020) Neural control of robot manipulators with trajectory tracking constraints and input saturation. IEEE Trans Neural Netw Learn Syst 2020:5","journal-title":"IEEE Trans Neural Netw Learn Syst"},{"key":"418_CR2","first-page":"5","volume":"2020","author":"H Huang","year":"2020","unstructured":"Huang H, Yang C, Chen CP (2020) Optimal robot-environment interaction under broad fuzzy neural adaptive control. IEEE Trans Cybern 2020:5","journal-title":"IEEE Trans Cybern"},{"key":"418_CR3","first-page":"5","volume":"2019","author":"UE Ogenyi","year":"2019","unstructured":"Ogenyi UE, Liu J, Yang C, Ju Z, Liu H (2019) Physical human-robot collaboration: Robotic systems, learning methods, collaborative strategies, sensors, and actuators. IEEE Trans Cybern 2019:5","journal-title":"IEEE Trans Cybern"},{"issue":"1","key":"418_CR4","doi-asserted-by":"publisher","first-page":"209","DOI":"10.1109\/TII.2019.2957768","volume":"17","author":"D Huang","year":"2019","unstructured":"Huang D, Yang C, Pan Y, Cheng L (2019) Composite learning enhanced neural control for robot manipulator with output error constraints. IEEE Trans Ind Inf 17(1):209\u2013218","journal-title":"IEEE Trans Ind Inf"},{"issue":"10","key":"418_CR5","doi-asserted-by":"publisher","first-page":"8608","DOI":"10.1109\/TIE.2019.2950853","volume":"67","author":"H Huang","year":"2019","unstructured":"Huang H, Zhang T, Yang C, Chen CP (2019) Motor learning and generalization using broad learning adaptive neural control. IEEE Trans Ind Electron 67(10):8608\u20138617","journal-title":"IEEE Trans Ind Electron"},{"key":"418_CR6","doi-asserted-by":"publisher","first-page":"191","DOI":"10.1016\/j.ijsu.2017.12.038","volume":"51","author":"J Lei","year":"2018","unstructured":"Lei J, Huang J, Yang X, Zhang Y, Yao K (2018) Minimally invasive surgery versus open hepatectomy for hepatolithiasis: a systematic review and meta analysis. Int J Surg 51:191\u2013198","journal-title":"Int J Surg"},{"issue":"5","key":"418_CR7","doi-asserted-by":"publisher","first-page":"537","DOI":"10.1136\/adc.2004.062760","volume":"90","author":"B Jaffray","year":"2005","unstructured":"Jaffray B (2005) Minimally invasive surgery. Arch Dis Child 90(5):537\u2013542","journal-title":"Arch Dis Child"},{"issue":"4","key":"418_CR8","doi-asserted-by":"publisher","first-page":"238","DOI":"10.5662\/wjm.v5.i4.238","volume":"5","author":"A Buia","year":"2015","unstructured":"Buia A, Stockhausen F, Hanisch E (2015) Laparoscopic surgery: a qualified systematic review. World J Methodol 5(4):238","journal-title":"World J Methodol"},{"issue":"4","key":"418_CR9","first-page":"341","volume":"2","author":"GS Litynski","year":"1998","unstructured":"Litynski GS (1998) Erich m\u00fche and the rejection of laparoscopic cholecystectomy (1985): a surgeon ahead of his time. J Soc Laparoendosc Surg 2(4):341","journal-title":"J Soc Laparoendosc Surg"},{"issue":"388","key":"418_CR10","doi-asserted-by":"publisher","first-page":"1369","DOI":"10.1016\/S0140-6736(16)31738-X","volume":"10052","author":"T Schlich","year":"2016","unstructured":"Schlich T, Tang CL (2016) Patient choice and the history of minimally invasive surgery. The Lancet 10052(388):1369\u20131370","journal-title":"The Lancet"},{"issue":"1","key":"418_CR11","first-page":"89","volume":"5","author":"W Reynolds Jr","year":"2001","unstructured":"Reynolds W Jr (2001) The first laparoscopic cholecystectomy. J Soc Laparoendosc Surg 5(1):89","journal-title":"J Soc Laparoendosc Surg"},{"issue":"3","key":"418_CR12","doi-asserted-by":"publisher","first-page":"242","DOI":"10.1016\/j.suronc.2009.02.007","volume":"18","author":"HR Patel","year":"2009","unstructured":"Patel HR, Linares A, Joseph JV (2009) Robotic and laparoscopic surgery: cost and training. Surg Oncol 18(3):242\u2013246","journal-title":"Surg Oncol"},{"key":"418_CR13","doi-asserted-by":"crossref","unstructured":"Aghakhani N, Geravand M, Shahriari N, Vendittelli M, Oriolo G (2013) Task control with remote center of motion constraint for minimally invasive robotic surgery. In: 2013 IEEE international conference on robotics and automation, IEEE, pp 5807\u20135812","DOI":"10.1109\/ICRA.2013.6631412"},{"key":"418_CR14","doi-asserted-by":"crossref","unstructured":"Taylor RH, Menciassi A, Fichtinger G, Fiorini P, Dario P (2016) Medical robotics and computer-integrated surgery. In: Springer handbook of robotics, pp 1657\u20131684","DOI":"10.1007\/978-3-319-32552-1_63"},{"issue":"2","key":"418_CR15","doi-asserted-by":"publisher","first-page":"1447","DOI":"10.1109\/LRA.2019.2897145","volume":"4","author":"H Su","year":"2019","unstructured":"Su H, Yang C, Ferrigno G, De Momi E (2019) Improved human-robot collaborative control of redundant robot for teleoperated minimally invasive surgery. IEEE Robot Autom Lett 4(2):1447\u20131453","journal-title":"IEEE Robot Autom Lett"},{"key":"418_CR16","unstructured":"Guthart GS, Salisbury JK (2000) The intuitive\/sup tm\/telesurgery system: overview and application. In: Proceedings 2000 ICRA. Millennium Conference. IEEE International Conference on Robotics and Automation. Symposia Proceedings (Cat. No. 00CH37065), IEEE, vol\u00a01, pp 618\u2013621"},{"issue":"3","key":"418_CR17","doi-asserted-by":"publisher","first-page":"279","DOI":"10.1109\/51.391776","volume":"14","author":"RH Taylor","year":"1995","unstructured":"Taylor RH, Funda J, Eldridge B, Gomory K, LaRose D, Talamini M, Kavoussi LL, Anderson J (1995) A telerobotic assistant for laparoscopic surgery. IEEE Eng Med Biol Mag 14(3):279\u2013288","journal-title":"IEEE Eng Med Biol Mag"},{"issue":"4","key":"418_CR18","doi-asserted-by":"publisher","first-page":"182","DOI":"10.3109\/10929089909148172","volume":"4","author":"E Kobayashi","year":"1999","unstructured":"Kobayashi E, Masamune K, Sakuma I, Dohi T, Hashimoto D (1999) A new safe laparoscopic manipulator system with a five-bar linkage mechanism and an optical zoom. Comput Aided Surg 4(4):182\u2013192","journal-title":"Comput Aided Surg"},{"key":"418_CR19","first-page":"5","volume":"2020","author":"J Chen","year":"2020","unstructured":"Chen J, Qiao H (2020) Motor-cortex-like recurrent neural network and multi-tasks learning for the control of musculoskeletal systems. IEEE Trans Cogn Develop Syst 2020:5","journal-title":"IEEE Trans Cogn Develop Syst"},{"key":"418_CR20","first-page":"5","volume":"2020","author":"S Liu","year":"2020","unstructured":"Liu S, Sun M, Feng L, Qiao H, Chen S, Liu Y (2020) Social neighborhood graph and multigraph fusion ranking for multifeature image retrieval. IEEE Trans Neural Netw Learn Syst 2020:5","journal-title":"IEEE Trans Neural Netw Learn Syst"},{"key":"418_CR21","first-page":"6","volume":"2020","author":"J Chen","year":"2020","unstructured":"Chen J, Qiao H (2020) Muscle-synergies-based neuromuscular control for motion learning and generalization of a musculoskeletal system. IEEE Trans Syst Man Cybern Syst 2020:6","journal-title":"IEEE Trans Syst Man Cybern Syst"},{"key":"418_CR22","first-page":"6","volume":"2020","author":"X Huang","year":"2020","unstructured":"Huang X, Wu W, Qiao H (2020) Computational modeling of emotion-motivated decisions for continuous control of mobile robots. IEEE Trans Cogn Develop Syst 2020:6","journal-title":"IEEE Trans Cogn Develop Syst"},{"issue":"3","key":"418_CR23","doi-asserted-by":"publisher","first-page":"601","DOI":"10.1109\/TCDS.2019.2953642","volume":"12","author":"S Zhong","year":"2019","unstructured":"Zhong S, Chen J, Niu X, Fu H, Qiao H (2019) Reducing redundancy of musculoskeletal robot with convex hull vertexes selection. IEEE Trans Cogn Develop Syst 12(3):601\u2013617","journal-title":"IEEE Trans Cogn Develop Syst"},{"key":"418_CR24","doi-asserted-by":"publisher","DOI":"10.1007\/1-4020-2204-2","volume-title":"International symposium on history of machines and mechanisms","author":"M Ceccarelli","year":"2004","unstructured":"Ceccarelli M (2004) International symposium on history of machines and mechanisms. Springer, Berlin"},{"issue":"3","key":"418_CR25","doi-asserted-by":"publisher","first-page":"901","DOI":"10.1007\/s10846-018-0927-0","volume":"95","author":"H Sadeghian","year":"2019","unstructured":"Sadeghian H, Zokaei F, Jazi SH (2019) Constrained kinematic control in minimally invasive robotic surgery subject to remote center of motion constraint. J Intel Robot Syst 95(3):901\u2013913","journal-title":"J Intel Robot Syst"},{"key":"418_CR26","doi-asserted-by":"crossref","unstructured":"Marinho MM, Bernardes MC, B\u00f3 AP (2014) A programmable remote center-of-motion controller for minimally invasive surgery using the dual quaternion framework. In: 5th IEEE RAS\/EMBS international conference on biomedical robotics and biomechatronics, IEEE, pp 339\u2013344","DOI":"10.1109\/BIOROB.2014.6913799"},{"key":"418_CR27","doi-asserted-by":"crossref","unstructured":"Sandoval J, Poisson G, Vieyres P (2017) A new kinematic formulation of the rcm constraint for redundant torque-controlled robots. In: 2017 IEEE\/RSJ international conference on intelligent robots and systems (IROS), IEEE, pp 4576\u20134581","DOI":"10.1109\/IROS.2017.8206326"},{"issue":"2","key":"418_CR28","doi-asserted-by":"publisher","first-page":"362","DOI":"10.1002\/rnc.2891","volume":"24","author":"X Wei","year":"2014","unstructured":"Wei X, Chen N (2014) Composite hierarchical anti-disturbance control for nonlinear systems with dobc and fuzzy control. Int J Robust Nonlinear Control 24(2):362\u2013373","journal-title":"Int J Robust Nonlinear Control"},{"issue":"12","key":"418_CR29","doi-asserted-by":"publisher","first-page":"5296","DOI":"10.1109\/TSMC.2018.2871196","volume":"50","author":"Z Li","year":"2018","unstructured":"Li Z, Xu C, Wei Q, Shi C, Su CY (2018) Human-inspired control of dual-arm exoskeleton robots with force and impedance adaptation. IEEE Trans Syst Man Cybern Syst 50(12):5296\u20135305","journal-title":"IEEE Trans Syst Man Cybern Syst"},{"issue":"4","key":"418_CR30","doi-asserted-by":"publisher","first-page":"1174","DOI":"10.1109\/TNNLS.2017.2665581","volume":"29","author":"W He","year":"2017","unstructured":"He W, Dong Y (2017) Adaptive fuzzy neural network control for a constrained robot using impedance learning. IEEE Trans Neural Netw Learn Syst 29(4):1174\u20131186","journal-title":"IEEE Trans Neural Netw Learn Syst"},{"key":"418_CR31","doi-asserted-by":"publisher","first-page":"326","DOI":"10.1016\/j.automatica.2018.06.051","volume":"96","author":"W He","year":"2018","unstructured":"He W, Meng T, He X, Ge SS (2018) Unified iterative learning control for flexible structures with input constraints. Automatica 96:326\u2013336","journal-title":"Automatica"},{"issue":"2","key":"418_CR32","doi-asserted-by":"publisher","first-page":"693","DOI":"10.1109\/TCST.2017.2669158","volume":"26","author":"W He","year":"2017","unstructured":"He W, Meng T (2017) Adaptive control of a flexible string system with input hysteresis. IEEE Trans Control Syst Technol 26(2):693\u2013700","journal-title":"IEEE Trans Control Syst Technol"},{"key":"418_CR33","unstructured":"Li M, Kapoor A, Taylor RH (2005) A constrained optimization approach to virtual fixtures. In: 2005 IEEE\/RSJ International Conference on Intelligent Robots and Systems, IEEE, pp 1408\u20131413"},{"issue":"2","key":"418_CR34","doi-asserted-by":"publisher","first-page":"235","DOI":"10.1109\/TCST.2005.863650","volume":"14","author":"J Gangloff","year":"2006","unstructured":"Gangloff J, Ginhoux R, de Mathelin M, Soler L, Marescaux J (2006) Model predictive control for compensation of cyclic organ motions in teleoperated laparoscopic surgery. IEEE Trans Control Syst Technol 14(2):235\u2013246","journal-title":"IEEE Trans Control Syst Technol"},{"issue":"5","key":"418_CR35","doi-asserted-by":"publisher","first-page":"527","DOI":"10.1002\/rnc.1608","volume":"21","author":"D Wang","year":"2011","unstructured":"Wang D (2011) Neural network-based adaptive dynamic surface control of uncertain nonlinear pure-feedback systems. Int J Robust Nonlinear Control 21(5):527\u2013541","journal-title":"Int J Robust Nonlinear Control"},{"issue":"6","key":"418_CR36","doi-asserted-by":"publisher","first-page":"740","DOI":"10.1109\/TSMC.2015.2465352","volume":"46","author":"Z Li","year":"2015","unstructured":"Li Z, Deng J, Lu R, Xu Y, Bai J, Su CY (2015) Trajectory-tracking control of mobile robot systems incorporating neural-dynamic optimized model predictive approach. IEEE Trans Syst Man Cybern Syst 46(6):740\u2013749","journal-title":"IEEE Trans Syst Man Cybern Syst"},{"key":"418_CR37","first-page":"8","volume":"2020","author":"Z Li","year":"2020","unstructured":"Li Z, Zhao K, Zhang L, Wu X, Zhang T, Li Q, Li X, Su CY (2020) Human-in-the-loop control of a wearable lower limb exoskeleton for stable dynamic walking. IEEE\/ASME Trans Mechatron 2020:8","journal-title":"IEEE\/ASME Trans Mechatron"},{"key":"418_CR38","volume-title":"Model-based predictive control: a practical approach","author":"JA Rossiter","year":"2003","unstructured":"Rossiter JA (2003) Model-based predictive control: a practical approach. CRC Press, Hoboken"},{"key":"418_CR39","volume-title":"Model predictive control system design and implementation using MATLAB\u00ae","author":"L Wang","year":"2009","unstructured":"Wang L (2009) Model predictive control system design and implementation using MATLAB\u00ae. Springer Science & Business Media, Berlin"},{"key":"418_CR40","doi-asserted-by":"crossref","unstructured":"Katliar M, Drop FM, Teufell H, Diehl M, B\u00fclthoff HH (2018) Real-time nonlinear model predictive control of a motion simulator based on a 8-dof serial robot. In: 2018 European Control Conference (ECC), IEEE, pp 1529\u20131535","DOI":"10.23919\/ECC.2018.8550041"},{"issue":"11","key":"418_CR41","doi-asserted-by":"publisher","first-page":"1341","DOI":"10.1002\/rnc.1758","volume":"21","author":"DQ Mayne","year":"2011","unstructured":"Mayne DQ, Kerrigan EC, Van Wyk E, Falugi P (2011) Tube-based robust nonlinear model predictive control. Int J Robust Nonlinear Control 21(11):1341\u20131353","journal-title":"Int J Robust Nonlinear Control"},{"issue":"2","key":"418_CR42","doi-asserted-by":"publisher","first-page":"146","DOI":"10.1109\/91.227383","volume":"1","author":"LX Wang","year":"1993","unstructured":"Wang LX (1993) Stable adaptive fuzzy control of nonlinear systems. IEEE Trans Fuzzy Syst 1(2):146\u2013155","journal-title":"IEEE Trans Fuzzy Syst"},{"issue":"3","key":"418_CR43","doi-asserted-by":"publisher","first-page":"555","DOI":"10.1109\/TFUZZ.2014.2317511","volume":"23","author":"Z Li","year":"2014","unstructured":"Li Z, Su CY, Li G, Su H (2014) Fuzzy approximation-based adaptive backstepping control of an exoskeleton for human upper limbs. IEEE Trans Fuzzy Syst 23(3):555\u2013566","journal-title":"IEEE Trans Fuzzy Syst"},{"issue":"4","key":"418_CR44","doi-asserted-by":"publisher","first-page":"1512","DOI":"10.1109\/TASE.2018.2874454","volume":"16","author":"C Yang","year":"2018","unstructured":"Yang C, Luo J, Liu C, Li M, Dai SL (2018) Haptics electromyography perception and learning enhanced intelligence for teleoperated robot. IEEE Trans Autom Sci Eng 16(4):1512\u20131521","journal-title":"IEEE Trans Autom Sci Eng"},{"issue":"2","key":"418_CR45","doi-asserted-by":"crossref","first-page":"281","DOI":"10.1109\/TCDS.2018.2866477","volume":"11","author":"C Yang","year":"2018","unstructured":"Yang C, Chen C, Wang N, Ju Z, Fu J, Wang M (2018) Biologically inspired motion modeling and neural control for robot learning from demonstrations. IEEE Trans Cogn Develop Syst 11(2):281\u2013291","journal-title":"IEEE Trans Cogn Develop Syst"},{"issue":"7","key":"418_CR46","doi-asserted-by":"publisher","first-page":"2568","DOI":"10.1109\/TCYB.2018.2828654","volume":"49","author":"C Yang","year":"2018","unstructured":"Yang C, Peng G, Li Y, Cui R, Cheng L, Li Z (2018) Neural networks enhanced adaptive admittance control of optimized robot-environment interaction. IEEE Trans Cybern 49(7):2568\u20132579","journal-title":"IEEE Trans Cybern"},{"issue":"3","key":"418_CR47","doi-asserted-by":"publisher","first-page":"574","DOI":"10.1109\/TFUZZ.2018.2864940","volume":"27","author":"C Yang","year":"2018","unstructured":"Yang C, Jiang Y, Na J, Li Z, Cheng L, Su CY (2018) Finite-time convergence adaptive fuzzy control for dual-arm robot with unknown kinematics and dynamics. IEEE Trans Fuzzy Syst 27(3):574\u2013588","journal-title":"IEEE Trans Fuzzy Syst"},{"issue":"2","key":"418_CR48","doi-asserted-by":"publisher","first-page":"1244","DOI":"10.1109\/TII.2020.2984482","volume":"17","author":"C Zeng","year":"2020","unstructured":"Zeng C, Yang C, Cheng H, Li Y, Dai SL (2020) Simultaneously encoding movement and semg-based stiffness for robotic skill learning. IEEE Trans Ind Inf 17(2):1244\u20131252","journal-title":"IEEE Trans Ind Inf"},{"key":"418_CR49","volume-title":"Linear system theory and design","author":"CT Chen","year":"1999","unstructured":"Chen CT, Shafai B (1999) Linear system theory and design, vol 3. Oxford University Press, New York"},{"issue":"6","key":"418_CR50","doi-asserted-by":"publisher","first-page":"102","DOI":"10.1109\/MCS.2016.2602738","volume":"36","author":"SV Rakovi\u0107","year":"2016","unstructured":"Rakovi\u0107 SV (2016) Model predictive control: classical, robust, and stochastic [bookshelf]. IEEE Control Syst Mag 36(6):102\u2013105","journal-title":"IEEE Control Syst Mag"},{"key":"418_CR51","unstructured":"Levine WS, Gr\u00fcne L, Goebel R, Rakovic SV, Mesbah A, Kolmanovsky I, Di\u00a0Cairano S. Allan DA, Rawlings JB, Sehr MA et\u00a0al (2018) Handbook of model predictive control"},{"issue":"6","key":"418_CR52","doi-asserted-by":"publisher","first-page":"1012","DOI":"10.1109\/TFUZZ.2012.2190048","volume":"20","author":"B Chen","year":"2012","unstructured":"Chen B, Liu XP, Ge SS, Lin C (2012) Adaptive fuzzy control of a class of nonlinear systems by fuzzy approximation approach. IEEE Trans Fuzzy Syst 20(6):1012\u20131021","journal-title":"IEEE Trans Fuzzy Syst"},{"issue":"1","key":"418_CR53","doi-asserted-by":"publisher","first-page":"134","DOI":"10.1109\/TFUZZ.2012.2204065","volume":"21","author":"S Tong","year":"2012","unstructured":"Tong S, Li Y (2012) Adaptive fuzzy output feedback control of mimo nonlinear systems with unknown dead-zone inputs. IEEE Trans Fuzzy Syst 21(1):134\u2013146","journal-title":"IEEE Trans Fuzzy Syst"},{"key":"418_CR54","unstructured":"Hamid UZA, Zamzuri H, Raksincharoensak P, Rahman MAA (2016) Analysis of vehicle collision avoidance using model predictive control with threat assessment. In: 23rd ITS world congress"},{"key":"418_CR55","doi-asserted-by":"crossref","unstructured":"Chen Y, Wang L, Galloway K, Godage I, Simaan N, Barth E (2020) Modal-based kinematics and contact detection of soft robots. Soft Robot","DOI":"10.1089\/soro.2019.0095"},{"issue":"4","key":"418_CR56","doi-asserted-by":"publisher","first-page":"1794","DOI":"10.1109\/TMECH.2020.2995134","volume":"25","author":"S Yu","year":"2020","unstructured":"Yu S, Huang TH, Yang X, Jiao C, Yang J, Chen Y, Yi J, Su H (2020) Quasi-direct drive actuation for a lightweight hip exoskeleton with high backdrivability and high bandwidth. IEEE\/ASME Trans Mechatron 25(4):1794\u20131802","journal-title":"IEEE\/ASME Trans Mechatron"}],"container-title":["Complex &amp; Intelligent Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s40747-021-00418-6.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s40747-021-00418-6\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s40747-021-00418-6.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,9,3]],"date-time":"2024-09-03T18:59:11Z","timestamp":1725389951000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s40747-021-00418-6"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,7,8]]},"references-count":56,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2022,8]]}},"alternative-id":["418"],"URL":"https:\/\/doi.org\/10.1007\/s40747-021-00418-6","relation":{},"ISSN":["2199-4536","2198-6053"],"issn-type":[{"type":"print","value":"2199-4536"},{"type":"electronic","value":"2198-6053"}],"subject":[],"published":{"date-parts":[[2021,7,8]]},"assertion":[{"value":"1 February 2021","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"31 May 2021","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"8 July 2021","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}