{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,10]],"date-time":"2026-06-10T16:00:16Z","timestamp":1781107216650,"version":"3.54.1"},"reference-count":49,"publisher":"MDPI AG","issue":"15","license":[{"start":{"date-parts":[[2022,7,31]],"date-time":"2022-07-31T00:00:00Z","timestamp":1659225600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"JSPS KAKENHI","award":["16H01616"],"award-info":[{"award-number":["16H01616"]}]},{"name":"JSPS KAKENHI","award":["17H06383"],"award-info":[{"award-number":["17H06383"]}]},{"name":"New Energy and Industrial Technology Development Organization (NEDO)","award":["16H01616"],"award-info":[{"award-number":["16H01616"]}]},{"name":"New Energy and Industrial Technology Development Organization (NEDO)","award":["17H06383"],"award-info":[{"award-number":["17H06383"]}]},{"name":"Project on Regional Revitalization Through Advanced Robotics (Kyushu Institute of Technology, Kitakyushu city, Japan)","award":["16H01616"],"award-info":[{"award-number":["16H01616"]}]},{"name":"Project on Regional Revitalization Through Advanced Robotics (Kyushu Institute of Technology, Kitakyushu city, Japan)","award":["17H06383"],"award-info":[{"award-number":["17H06383"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>This study presents an effective artificial neural network (ANN) approach to combine measurements from inertial measurement units (IMUs) and time-of-flight (TOF) measurements from an ultra-wideband (UWB) system with OptiTrack Motion Capture System (OptiT-MCS) data to guarantee the positioning accuracy of motion tracking in indoor environments. The proposed fusion approach unifies the following advantages of both technologies: high data rates from the MCS, and global translational precision from the inertial measurement unit (IMU)\/UWB localization system. Consequently, it leads to accurate position estimates when compared with data from the IMU\/UWB system relative to the OptiT-MCS reference system. The calibrations of the positioning IMU\/UWB and MCS systems are utilized in real-time movement with a diverse set of motion recordings using a mobile robot. The proposed neural network (NN) approach experimentally revealed accurate position estimates, giving an enhancement average mean absolute percentage error (MAPE) of 17.56% and 7.48% in the X and Y coordinates, respectively, and the coefficient of correlation R greater than 99%. Moreover, the experimental results prove that the proposed NN fusion is capable of maintaining high accuracy in position estimates while preventing drift errors from increasing in an unbounded manner, implying that the proposed approach is more effective than the compared approaches.<\/jats:p>","DOI":"10.3390\/s22155737","type":"journal-article","created":{"date-parts":[[2022,8,1]],"date-time":"2022-08-01T23:49:27Z","timestamp":1659397767000},"page":"5737","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":24,"title":["Artificial Neural Network Approach to Guarantee the Positioning Accuracy of Moving Robots by Using the Integration of IMU\/UWB with Motion Capture System Data Fusion"],"prefix":"10.3390","volume":"22","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3608-2023","authenticated-orcid":false,"given":"Ahmed M. M.","family":"Almassri","sequence":"first","affiliation":[{"name":"Graduate School of Life Science and Systems Engineering, Kyushu Institute of Technology (Kyutech), 2-4 Hibikino, Wakamatsu-ku, Kitakyushu 808-0196, Japan"},{"name":"Robotic Innovation Research Center (RIRC), Israa University, Gaza P860, Palestine"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Natsuki","family":"Shirasawa","sequence":"additional","affiliation":[{"name":"Graduate School of Life Science and Systems Engineering, Kyushu Institute of Technology (Kyutech), 2-4 Hibikino, Wakamatsu-ku, Kitakyushu 808-0196, Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Amarbold","family":"Purev","sequence":"additional","affiliation":[{"name":"Graduate School of Life Science and Systems Engineering, Kyushu Institute of Technology (Kyutech), 2-4 Hibikino, Wakamatsu-ku, Kitakyushu 808-0196, Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kaito","family":"Uehara","sequence":"additional","affiliation":[{"name":"Graduate School of Life Science and Systems Engineering, Kyushu Institute of Technology (Kyutech), 2-4 Hibikino, Wakamatsu-ku, Kitakyushu 808-0196, Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wataru","family":"Oshiumi","sequence":"additional","affiliation":[{"name":"Graduate School of Life Science and Systems Engineering, Kyushu Institute of Technology (Kyutech), 2-4 Hibikino, Wakamatsu-ku, Kitakyushu 808-0196, Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Satoru","family":"Mishima","sequence":"additional","affiliation":[{"name":"Graduate School of Life Science and Systems Engineering, Kyushu Institute of Technology (Kyutech), 2-4 Hibikino, Wakamatsu-ku, Kitakyushu 808-0196, Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hiroaki","family":"Wagatsuma","sequence":"additional","affiliation":[{"name":"Graduate School of Life Science and Systems Engineering, Kyushu Institute of Technology (Kyutech), 2-4 Hibikino, Wakamatsu-ku, Kitakyushu 808-0196, Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2022,7,31]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Filippeschi, A., Schmitz, N., Miezal, M., Bleser, G., Ruffaldi, E., and Stricker, D. (2017). Survey of motion tracking methods based on inertial sensors: A focus on upper limb human motion. Sensors, 17.","DOI":"10.3390\/s17061257"},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Peltola, P., Hill, C., and Moore, T. (2016, January 28\u201330). Particle Filter for Context Sensitive Indoor Pedestrian Navigation. Proceedings of the 2016 International Conference on Localization and GNSS (ICL-GNSS), Barcelona, Spain.","DOI":"10.1109\/ICL-GNSS.2016.7533865"},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Schirmer, M., Hartmann, J., Bertel, S., and Echtler, F. (2015, January 24\u201327). Shoe me the way: A Shoe-Based Tactile Interface for Eyes-Free Urban Navigation. Proceedings of the 17th International Conference on Human-Computer Interaction with Mobile Devices and Services, Copenhagen, Denmark.","DOI":"10.1145\/2785830.2785832"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"641","DOI":"10.1080\/17434440.2016.1198694","article-title":"Wearable inertial sensors for human movement analysis","volume":"13","author":"Iosa","year":"2016","journal-title":"Expert Rev. Med. Devices"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"8301","DOI":"10.3390\/s120608301","article-title":"Intelligent lead: A novel HRI sensor for guide robots","volume":"12","author":"Cho","year":"2012","journal-title":"Sensors"},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Jamil, F., Iqbal, N., Ahmad, S., and Kim, D.-H. (2020). Toward accurate position estimation using learning to prediction algorithm in indoor navigation. Sensors, 20.","DOI":"10.3390\/s20164410"},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Zizzo, G., and Ren, L. (2017). Position tracking during human walking using an integrated wearable sensing system. Sensors, 17.","DOI":"10.3390\/s17122866"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"35-es","DOI":"10.1145\/1276377.1276421","article-title":"Practical motion capture in everyday surroundings","volume":"26","author":"Vlasic","year":"2007","journal-title":"ACM Trans. Graph."},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Schall, G., Wagner, D., Reitmayr, G., Taichmann, E., Wieser, M., Schmalstieg, D., and Hofmann-Wellenhof, B. (2009, January 19\u201322). Global Pose Estimation Using Multi-Sensor Fusion for Outdoor Augmented Reality. Proceedings of the 2009 8th IEEE International Symposium on Mixed and Augmented Reality, Orlando, FL, USA.","DOI":"10.1109\/ISMAR.2009.5336489"},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Corrales Ram\u00f3n, J.A., Candelas-Her\u00edas, F.A., and Torres, F. (2008, January 12\u201315). Hybrid Tracking of Human Operators Using IMU\/UWB Data Fusion by a Kalman Filter. Proceedings of the 2008 3rd ACM\/IEEE International Conference on Human-Robot Interaction (HRI), New York, NY, USA.","DOI":"10.1145\/1349822.1349848"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"607","DOI":"10.1177\/0278364907079278","article-title":"Integration of vision and inertial sensors for 3D arm motion tracking in home-based rehabilitation","volume":"26","author":"Tao","year":"2007","journal-title":"Int. J. Robot. Res."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"1793","DOI":"10.1109\/TIM.2011.2181884","article-title":"A factorized quaternion approach to determine the arm motions using triaxial accelerometers with anatomical and sensor constraints","volume":"61","author":"Lee","year":"2012","journal-title":"IEEE Trans. Instrum. Meas."},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Miezal, M., Taetz, B., and Bleser, G. (2016). On inertial body tracking in the presence of model calibration errors. Sensors, 16.","DOI":"10.3390\/s16071132"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"79","DOI":"10.3182\/20140824-6-ZA-1003.02252","article-title":"An optimization-based approach to human body motion capture using inertial sensors","volume":"47","author":"Kok","year":"2014","journal-title":"IFAC Proc. Vol."},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Yao, L., Wu, Y.-W.A., Yao, L., and Liao, Z.Z. (2017, January 18\u201321). An Integrated IMU and UWB Sensor Based Indoor Positioning System. Proceedings of the 2017 International Conference on Indoor Positioning and Indoor Navigation (IPIN), Wikipedia, Japan.","DOI":"10.1109\/IPIN.2017.8115911"},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Hol, J.D., Dijkstra, F., Luinge, H., and Schon, T.B. (2009, January 9\u201311). Tightly Coupled UWB\/IMU Pose Estimation. Proceedings of the 2009 IEEE International Conference on Ultra-Wideband, Vancouver, BC, Canada.","DOI":"10.1109\/ICUWB.2009.5288724"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"1293","DOI":"10.1109\/TVT.2015.2396640","article-title":"Indoor positioning using ultrawideband and inertial measurements","volume":"64","author":"Kok","year":"2015","journal-title":"IEEE Trans. Veh. Technol."},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Alarifi, A., Al-Salman, A., Alsaleh, M., Alnafessah, A., Al-Hadhrami, S., Al-Ammar, M.A., and Al-Khalifa, H.S. (2016). Ultra wideband indoor positioning technologies: Analysis and recent advances. Sensors, 16.","DOI":"10.3390\/s16050707"},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Weber, D., G\u00fchmann, C., and Seel, T. (2020, January 6\u20139). Neural networks versus conventional filters for inertial-sensor-based attitude estimation. Proceedings of the 2020 IEEE 23rd International Conference on Information Fusion (FUSION), Rustenburg, South Africa.","DOI":"10.23919\/FUSION45008.2020.9190634"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"70","DOI":"10.1109\/MSP.2005.1458289","article-title":"Localization via ultra-wideband radios: A look at positioning aspects for future sensor networks","volume":"22","author":"Gezici","year":"2005","journal-title":"IEEE Signal Processing Mag."},{"key":"ref_21","first-page":"1","article-title":"Ultra-wideband positioning systems: Theoretical limits","volume":"10","author":"Zafer","year":"2008","journal-title":"Ranging Algorithms Protoc."},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Barral, V., Escudero, C.J., Garc\u00eda-Naya, J.A., and Maneiro-Catoira, R. (2019). NLOS identification and mitigation using low-cost UWB devices. Sensors, 19.","DOI":"10.3390\/s19163464"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"404","DOI":"10.1109\/JPROC.2008.2008846","article-title":"Ranging with ultrawide bandwidth signals in multipath environments","volume":"97","author":"Dardari","year":"2009","journal-title":"Proc. IEEE"},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Decarli, N., Dardari, D., Gezici, S., and D\u2019Amico, A.A. (2010, January 5\u20137). LOS\/NLOS Detection for UWB Signals: A Comparative Study Using Experimental Data. Proceedings of the IEEE 5th International Symposium on Wireless Pervasive Computing, Modena, Italy.","DOI":"10.1109\/ISWPC.2010.5483704"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"613","DOI":"10.1109\/TAES.2008.4560210","article-title":"Position error bound for UWB localization in dense cluttered environments","volume":"44","author":"Jourdan","year":"2008","journal-title":"IEEE Trans. Aerosp. Electron. Syst."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"61","DOI":"10.1109\/MSP.2012.2183773","article-title":"Robust estimation in signal processing: A tutorial-style treatment of fundamental concepts","volume":"29","author":"Zoubir","year":"2012","journal-title":"IEEE Signal Process. Mag."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"41","DOI":"10.1109\/MSP.2005.1458284","article-title":"Mobile positioning using wireless networks: Possibilities and fundamental limitations based on available wireless network measurements","volume":"22","author":"Gustafsson","year":"2005","journal-title":"IEEE Signal Processing Mag."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"1046","DOI":"10.1109\/TVT.2008.926071","article-title":"Measurement and modeling of ultrawideband TOA-based ranging in indoor multipath environments","volume":"58","author":"Alsindi","year":"2008","journal-title":"IEEE Trans. Veh. Technol."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"1120","DOI":"10.1049\/iet-map:20060273","article-title":"Non-line-of-sight identification in ultra-wideband systems based on received signal statistics","volume":"1","author":"Venkatesh","year":"2007","journal-title":"IET Microw. Antennas Propag."},{"key":"ref_30","unstructured":"Borras, J., Hatrack, P., and Mandayam, N.B. (1998, January 21\u201321). Decision Theoretic Framework for NLOS Identification. Proceedings of the VTC\u201998. 48th IEEE Vehicular Technology Conference. Pathway to Global Wireless Revolution (Cat. No. 98CH36151), Ottawa, ON, Canada."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"1026","DOI":"10.1109\/JSAC.2010.100907","article-title":"NLOS identification and mitigation for localization based on UWB experimental data","volume":"28","author":"Marano","year":"2010","journal-title":"IEEE J. Sel. Areas Commun."},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Maali, A., Mimoun, H., Baudoin, G., and Ouldali, A. (2009, January 18\u201322). A New Low Complexity NLOS Identification Approach Based on UWB Energy Detection. Proceedings of the 2009 IEEE Radio and Wireless Symposium, San Diego, CA, USA.","DOI":"10.1109\/RWS.2009.4957442"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"256","DOI":"10.12720\/ijsps.1.2.256-262","article-title":"Reviews on various inertial measurement unit (IMU) sensor applications","volume":"1","author":"Ahmad","year":"2013","journal-title":"Int. J. Signal Processing Syst."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1109\/CC.2015.7114054","article-title":"Healthcare algorithms by wearable inertial sensors: A survey","volume":"12","author":"Buke","year":"2015","journal-title":"China Commun."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"21","DOI":"10.1186\/1743-0003-9-21","article-title":"A review of wearable sensors and systems with application in rehabilitation","volume":"9","author":"Patel","year":"2012","journal-title":"J. Neuroeng. Rehabil."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"68","DOI":"10.1016\/j.inffus.2016.09.005","article-title":"Multi-sensor fusion in body sensor networks: State-of-the-art and research challenges","volume":"35","author":"Gravina","year":"2017","journal-title":"Inf. Fusion"},{"key":"ref_37","first-page":"2747","article-title":"Wearable Sensing for Solid Biomechanics","volume":"15","author":"Wong","year":"2015","journal-title":"J. Mag."},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"Jim\u00e9nez, A.R., Seco, F., Prieto, J.C., and Guevara, J. (2010, January 11\u201312). Indoor Pedestrian Navigation Using an INS\/EKF Framework for Yaw Drift Reduction and a Foot-Mounted IMU. Proceedings of the 7th Workshop on Positioning, Navigation and Communication, Dresden, Germany.","DOI":"10.1109\/WPNC.2010.5649300"},{"key":"ref_39","doi-asserted-by":"crossref","unstructured":"Ma, X.-f., Su, Z., Zhao, X., Liu, F.-C., and Li, C. (2017). Wearable Indoor Pedestrian Navigation Based on MIMU and Hypothesis Testing. Wearable Sensors and Robots, Springer.","DOI":"10.1007\/978-981-10-2404-7_10"},{"key":"ref_40","doi-asserted-by":"crossref","unstructured":"Renaudin, V., Afzal, M.H., and Lachapelle, G. (2010, January 4\u20136). New Method for Magnetometers Based Orientation Estimation. Proceedings of the IEEE\/ION Position, Location and Navigation Symposium, Indian Wells, CA, USA.","DOI":"10.1109\/PLANS.2010.5507301"},{"key":"ref_41","doi-asserted-by":"crossref","unstructured":"Pham, D.D., and Suh, Y.S. (2016). Pedestrian navigation using foot-mounted inertial sensor and LIDAR. Sensors, 16.","DOI":"10.3390\/s16010120"},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"439","DOI":"10.1109\/TWC.2002.800542","article-title":"Hybrid TDOA\/AOA mobile user location for wideband CDMA cellular systems","volume":"1","author":"Cong","year":"2002","journal-title":"IEEE Trans. Wirel. Commun."},{"key":"ref_43","unstructured":"(2021, June 10). Decawave Company. Decawave Website, 2021. Available online: https:\/\/www.decawave.com\/."},{"key":"ref_44","unstructured":"(2020, August 17). Pozyx Company. Pozyx Website, 2015. Available online: https:\/\/www.pozyx.io\/."},{"key":"ref_45","unstructured":"(2021, June 10). Ubisense Company. Ubisense Website, 2009. Available online: http:\/\/www.ubisense.net\/en\/."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"228","DOI":"10.1109\/TII.2012.2187914","article-title":"Selection of proper neural network sizes and architectures\u2014A comparative study","volume":"8","author":"Hunter","year":"2012","journal-title":"IEEE Trans. Ind. Inform."},{"key":"ref_47","doi-asserted-by":"crossref","unstructured":"L\u00f3pez-Aguilar, K., Benavides-Mendoza, A., Gonz\u00e1lez-Morales, S., Ju\u00e1rez-Maldonado, A., Chi\u00f1as-S\u00e1nchez, P., and Morelos-Moreno, A. (2020). Artificial neural network modeling of greenhouse tomato yield and aerial dry matter. Agriculture, 10.","DOI":"10.3390\/agriculture10040097"},{"key":"ref_48","doi-asserted-by":"crossref","unstructured":"Almassri, A.M., Wan Hasan, W.Z., Ahmad, S.A., Shafie, S., Wada, C., and Horio, K. (2018). Self-calibration algorithm for a pressure sensor with a real-time approach based on an artificial neural network. Sensors, 18.","DOI":"10.3390\/s18082561"},{"key":"ref_49","first-page":"45","article-title":"Min max normalization based data perturbation method for privacy protection","volume":"2","author":"Jain","year":"2011","journal-title":"Int. J. Comput. Commun. Technol."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/22\/15\/5737\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T00:00:21Z","timestamp":1760140821000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/22\/15\/5737"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,7,31]]},"references-count":49,"journal-issue":{"issue":"15","published-online":{"date-parts":[[2022,8]]}},"alternative-id":["s22155737"],"URL":"https:\/\/doi.org\/10.3390\/s22155737","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,7,31]]}}}