{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,28]],"date-time":"2026-02-28T04:30:03Z","timestamp":1772253003474,"version":"3.50.1"},"reference-count":52,"publisher":"MDPI AG","issue":"18","license":[{"start":{"date-parts":[[2020,9,21]],"date-time":"2020-09-21T00:00:00Z","timestamp":1600646400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100002850","name":"Fondo Nacional de Desarrollo Cient\u00edfico y Tecnol\u00f3gico","doi-asserted-by":"publisher","award":["1191188"],"award-info":[{"award-number":["1191188"]}],"id":[{"id":"10.13039\/501100002850","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100010198","name":"Ministerio de Econom\u00eda, Industria y Competitividad, Gobierno de Espa\u00f1a","doi-asserted-by":"publisher","award":["ENE2015-64914-C3-2-R"],"award-info":[{"award-number":["ENE2015-64914-C3-2-R"]}],"id":[{"id":"10.13039\/501100010198","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100010198","name":"Ministerio de Econom\u00eda, Industria y Competitividad, Gobierno de Espa\u00f1a","doi-asserted-by":"publisher","award":["RTI2018-094665-B-I00"],"award-info":[{"award-number":["RTI2018-094665-B-I00"]}],"id":[{"id":"10.13039\/501100010198","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004837","name":"Ministerio de Ciencia e Innovaci\u00f3n","doi-asserted-by":"publisher","award":["PID2019-108377RB-C32"],"award-info":[{"award-number":["PID2019-108377RB-C32"]}],"id":[{"id":"10.13039\/501100004837","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>This work presents the development and implementation of a distributed navigation system based on object recognition algorithms. The main goal is to introduce advanced algorithms for image processing and artificial intelligence techniques for teaching control of mobile robots. The autonomous system consists of a wheeled mobile robot with an integrated color camera. The robot navigates through a laboratory scenario where the track and several traffic signals must be detected and recognized by using the images acquired with its on-board camera. The images are sent to a computer server that performs a computer vision algorithm to recognize the objects. The computer calculates the corresponding speeds of the robot according to the object detected. The speeds are sent back to the robot, which acts to carry out the corresponding manoeuvre. Three different algorithms have been tested in simulation and a practical mobile robot laboratory. The results show an average of 84% success rate for object recognition in experiments with the real mobile robot platform.<\/jats:p>","DOI":"10.3390\/s20185409","type":"journal-article","created":{"date-parts":[[2020,9,21]],"date-time":"2020-09-21T21:01:21Z","timestamp":1600722081000},"page":"5409","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["A Distributed Vision-Based Navigation System for Khepera IV Mobile Robots"],"prefix":"10.3390","volume":"20","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2186-4126","authenticated-orcid":false,"given":"Gonzalo","family":"Farias","sequence":"first","affiliation":[{"name":"Escuela de Ingenier\u00eda El\u00e9ctrica, Pontificia Universidad Cat\u00f3lica de Valpara\u00edso, Av. Brasil 2147, Valpara\u00edso 2362804, Chile"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4478-6626","authenticated-orcid":false,"given":"Ernesto","family":"Fabregas","sequence":"additional","affiliation":[{"name":"Departamento de Inform\u00e1tica y Autom\u00e1tica, Universidad Nacional de Educaci\u00f3n a Distancia, Juan del Rosal 16, 28040 Madrid, Spain"}]},{"given":"Enrique","family":"Torres","sequence":"additional","affiliation":[{"name":"Escuela de Ingenier\u00eda El\u00e9ctrica, Pontificia Universidad Cat\u00f3lica de Valpara\u00edso, Av. Brasil 2147, Valpara\u00edso 2362804, Chile"}]},{"given":"Ga\u00ebtan","family":"Bricas","sequence":"additional","affiliation":[{"name":"The National Institute of Electrical Engineering, Electronics, Computer Science, Fluid Mechanics &amp; Telecommunications and Networks, 31071 Toulouse, France"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7652-5338","authenticated-orcid":false,"given":"Sebasti\u00e1n","family":"Dormido-Canto","sequence":"additional","affiliation":[{"name":"Departamento de Inform\u00e1tica y Autom\u00e1tica, Universidad Nacional de Educaci\u00f3n a Distancia, Juan del Rosal 16, 28040 Madrid, Spain"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2405-8771","authenticated-orcid":false,"given":"Sebasti\u00e1n","family":"Dormido","sequence":"additional","affiliation":[{"name":"Departamento de Inform\u00e1tica y Autom\u00e1tica, Universidad Nacional de Educaci\u00f3n a Distancia, Juan del Rosal 16, 28040 Madrid, Spain"}]}],"member":"1968","published-online":{"date-parts":[[2020,9,21]]},"reference":[{"key":"ref_1","unstructured":"Tang, L., and Yuta, S. (2001, January 21\u201326). Vision based navigation for mobile robots in indoor environment by teaching and playing-back scheme. Proceedings of the 2001 ICRA, IEEE International Conference on Robotics and Automation, Seoul, Korea."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"237","DOI":"10.1109\/34.982903","article-title":"Vision for mobile robot navigation: A survey","volume":"24","author":"DeSouza","year":"2002","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_3","unstructured":"Pomerleau, D. (1998). An autonomous land vehicle in a neural network. Advances in Neural Information Processing Systems, Morgan Kaufmann Publishers Inc."},{"key":"ref_4","unstructured":"Pan, J., Pack, D., Kosaka, A., and Kak, A. (December, January 27). FUZZY-NAV: A vision-based robot navigation architecture using fuzzy inference for uncertainty-reasoning. Proceedings of the World Congress on Neural Networks, Perth, Australia."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"729","DOI":"10.1016\/S0262-8856(98)00067-5","article-title":"Recognition and localization of generic objects for indoor navigation using functionality","volume":"16","author":"Kim","year":"1998","journal-title":"Image Vis. Comput."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"890","DOI":"10.1109\/70.897802","article-title":"Vision-based navigation and environmental representations with an omnidirectional camera","volume":"16","author":"Gaspar","year":"2000","journal-title":"IEEE Trans. Robot. Autom."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"33666","DOI":"10.1109\/ACCESS.2018.2842679","article-title":"Visual homing navigation with Haar-like features in the snapshot","volume":"6","author":"Lee","year":"2018","journal-title":"IEEE Access"},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Witkowski, U., Bolte, P., and Sitte, J. (2018, January 9\u201312). Learning Vision Based Navigation with a Smartphone Mobile Robot. Proceedings of the 2018 IEEE\/ASME International Conference on Advanced Intelligent Mechatronics (AIM), Auckland, New Zealand.","DOI":"10.1109\/AIM.2018.8452691"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.robot.2014.11.009","article-title":"Vision-based topological mapping and localization methods: A survey","volume":"64","author":"Ortiz","year":"2015","journal-title":"Rob. Autom. Syst."},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Fabregas, E., Farias, G., Peralta, E., Vargas, H., and Dormido, S. (2016, January 19\u201322). Teaching control in mobile robotics with V-REP and a Khepera IV library. Proceedings of the 2016 IEEE Conference on Control Applications (CCA), Buenos Aires, Argentina.","DOI":"10.1109\/CCA.2016.7587920"},{"key":"ref_11","first-page":"1729881419839596","article-title":"A review of mobile robots: Concepts, methods, theoretical framework, and applications","volume":"16","author":"Rubio","year":"2019","journal-title":"Int. J. Adv. Rob. Syst."},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Millard, A.G., Joyce, R., Hilder, J.A., Fle\u015feriu, C., Newbrook, L., Li, W., McDaid, L.J., and Halliday, D.M. (2017, January 24\u201328). The Pi-puck extension board: A Raspberry Pi interface for the e-puck robot platform. Proceedings of the 2017 IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS), Vancouver, BC, Canada.","DOI":"10.1109\/IROS.2017.8202233"},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Soares, J.M., Navarro, I., and Martinoli, A. (2015, January 19\u201321). The Khepera IV mobile robot: Performance evaluation, sensory data and software toolbox. Proceedings of the Robot 2015: Second Iberian Robotics Conference, Lisbon, Portugal.","DOI":"10.1007\/978-3-319-27146-0_59"},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Mart\u00ednez, S.I., Rocha, J.A.C., Menchaca, J.L., Berrones, M.G.T., Obando, J.G., Cobos, J.P., and Rocha, E.C. (2014). An Autonomous Navigation Methodology for a Pioneer 3DX Robot. Comp. Tech. App., 5.","DOI":"10.17265\/1934-7332\/2014.02.005"},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Singh, D., Trivedi, E., Sharma, Y., and Niranjan, V. (2018, January 28\u201329). TurtleBot: Design and Hardware Component Selection. Proceedings of the 2018 International Conference on Computing, Power and Communication Technologies (GUCON), Uttar Pradesh, India.","DOI":"10.1109\/GUCON.2018.8675050"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"31665","DOI":"10.1109\/ACCESS.2018.2846554","article-title":"Localization and navigation for autonomous mobile robots using petri nets in indoor environments","volume":"6","author":"Rocha","year":"2018","journal-title":"IEEE Access"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"49248","DOI":"10.1109\/ACCESS.2018.2868848","article-title":"Review of Wheeled Mobile Robots\u2019 Navigation Problems and Application Prospects in Agriculture","volume":"6","author":"Gao","year":"2018","journal-title":"IEEE Access"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"187","DOI":"10.1007\/s11370-016-0194-5","article-title":"An autonomous stereovision-based navigation system (ASNS) for mobile robots","volume":"9","author":"Faisal","year":"2016","journal-title":"Intell. Serv. Robot."},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Kortenkamp, D., Simmons, R., and Brugali, D. (2016). Robotic systems architectures and programming. Springer Handbook of Robotics, Springer.","DOI":"10.1007\/978-3-319-32552-1_12"},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Hsu, S.H., Chan, S.H., Wu, P.T., Xiao, K., and Fu, L.C. (2018, January 1\u20135). Distributed deep reinforcement learning based indoor visual navigation. Proceedings of the 2018 IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS), Madrid, Spain.","DOI":"10.1109\/IROS.2018.8594352"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"661","DOI":"10.1109\/LRA.2015.2509024","article-title":"A machine learning approach to visual perception of forest trails for mobile robots","volume":"1","author":"Giusti","year":"2015","journal-title":"IEEE Rob. Autom. Lett."},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Mosavi, A., and Varkonyi-Koczy, A.R. (2017). Integration of machine learning and optimization for robot learning. Recent Global Research and Education: Technological Challenges, Springer.","DOI":"10.1007\/978-3-319-46490-9_47"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"152941","DOI":"10.1109\/ACCESS.2020.3018026","article-title":"Reinforcement Learning for Position Control Problem of a Mobile Robot","volume":"8","author":"Farias","year":"2020","journal-title":"IEEE Access"},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Lakrouf, M., Larnier, S., Devy, M., and Achour, N. (2017, January 8\u201312). Moving obstacles detection and camera pointing for mobile robot applications. Proceedings of the 3rd International Conference on Mechatronics and Robotics Engineering, Paris, France.","DOI":"10.1145\/3068796.3068816"},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Irawan, A., Yaacob, M.A., Azman, F.A., Daud, M.R., Razali, A.R., and Ali, S.N.S. (2018, January 27). Vision-based Alignment Control for Mini Forklift System in Confine Area Operation. Proceedings of the 2018 International Symposium on Agent, Multi-Agent Systems and Robotics (ISAMSR), Putrajaya, Malaysia.","DOI":"10.1109\/ISAMSR.2018.8540552"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"16","DOI":"10.1016\/j.robot.2012.07.019","article-title":"Real-time traffic sign recognition in three stages","volume":"62","author":"Zaklouta","year":"2014","journal-title":"Rob. Autom. Syst."},{"key":"ref_27","unstructured":"Archana, S., Thejas, G., Ramani, S.K., and Iyengar, S. (2017, January 15\u201316). Image Processing Approaches for Autonomous Navigation of Terrestrial Vehicles in Low Illumination. Proceedings of the 2017 2nd International Conference on Emerging Computation and Information Technologies (ICECIT), Tumakuru, India."},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Zhang, H., Hernandez, D.E., Su, Z., and Su, B. (2018). A low cost vision-based road-following system for mobile robots. Appl. Sci., 8.","DOI":"10.3390\/app8091635"},{"key":"ref_29","first-page":"3212","article-title":"Object detection with deep learning: A review","volume":"30","author":"Zhao","year":"2019","journal-title":"IEEE T. Neur. Net. Lear."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"012114","DOI":"10.1088\/1757-899X\/466\/1\/012114","article-title":"Autonomous mobile robot visual SLAM based on improved CNN method","volume":"Volume 466","author":"Wang","year":"2018","journal-title":"IOP Conference Series: Materials Science and Engineering"},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Girshick, R. (2015, January 7\u201313). Fast R-CNN. Proceedings of the IEEE International Conference on Computer Vision, Santiago, Chile.","DOI":"10.1109\/ICCV.2015.169"},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Redmon, J., Divvala, S., Girshick, R., and Farhadi, A. (2016, January 27\u201330). You only look once: Unified, real-time object detection. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Las Vegas, NV, USA.","DOI":"10.1109\/CVPR.2016.91"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"55885","DOI":"10.1109\/ACCESS.2019.2913916","article-title":"Development of an easy-to-use multi-agent platform for teaching mobile robotics","volume":"7","author":"Farias","year":"2019","journal-title":"IEEE Access"},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Fabregas, E., Farias, G., Peralta, E., S\u00e1nchez, J., and Dormido, S. (2017, January 26\u201328). Two Mobile Robots Platforms for Experimentation: Comparison and Synthesis. Proceedings of the International Conference on Informatics in Control, Automation and Robotics (ICINCO 2017), Madrid, Spain.","DOI":"10.5220\/0006469004390446"},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"Farias, G., Fabregas, E., Peralta, E., Vargas, H., Hermosilla, G., Garcia, G., and Dormido, S. (2018). A neural network approach for building an obstacle detection model by fusion of proximity sensors data. Sensors, 18.","DOI":"10.3390\/s18030683"},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"81","DOI":"10.1016\/j.ifacol.2016.07.157","article-title":"Development of a Khepera IV Library for the V-REP Simulator","volume":"49","author":"Peralta","year":"2016","journal-title":"IFAC-PapersOnLine"},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"9150","DOI":"10.1016\/j.ifacol.2017.08.1721","article-title":"A Khepera IV library for robotic control education using V-REP","volume":"50","author":"Farias","year":"2017","journal-title":"IFAC-PapersOnLine"},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"Farias, G., Torres, E., Fabregas, E., Vargas, H., Dormido-Canto, S., and Dormido, S. (2018, January 17\u201319). Navigation control of the Khepera IV model with OpenCV in V-REP simulator. Proceedings of the 2018 IEEE International Conference on Automation\/XXIII Congress of the Chilean Association of Automatic Control (ICA-ACCA), Concepci\u00f3n, Chile.","DOI":"10.1109\/ICA-ACCA.2018.8609740"},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"258","DOI":"10.1002\/cae.21594","article-title":"JavaVis: An integrated computer vision library for teaching computer vision","volume":"23","author":"Cazorla","year":"2015","journal-title":"Comput. Appl. Eng. Educ."},{"key":"ref_40","unstructured":"Kraiss, K.F. (2019, October 02). LTI Image Processing Library Developer\u2019s Guide. Available online: http:\/\/www.ie.tec.ac.cr\/palvarado\/ltilib-2\/styleguide\/en\/DevelopersGuide.pdf."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"61","DOI":"10.1145\/2184319.2184337","article-title":"Real-time computer vision with OpenCV","volume":"55","author":"Pulli","year":"2012","journal-title":"Commun. ACM"},{"key":"ref_42","unstructured":"Bradski, G., and Kaehler, A. (2008). Learning OpenCV: Computer vision with the OpenCV library, O\u2019Reilly Media Inc."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"179420","DOI":"10.1109\/ACCESS.2019.2959312","article-title":"Vision-Based Real-Time Obstacle Segmentation Algorithm for Autonomous Surface Vehicle","volume":"7","author":"Kim","year":"2019","journal-title":"IEEE Access"},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"315","DOI":"10.1023\/A:1007652114878","article-title":"Cascade generalization","volume":"41","author":"Gama","year":"2000","journal-title":"Machine learning"},{"key":"ref_45","unstructured":"Rojas, R. (2009). AdaBoost and the Super Bowl of Classifiers a Tutorial Introduction to Adaptive Boosting, Freie University. Technical Report."},{"key":"ref_46","unstructured":"Luo, H. (2005, January 20\u201325). Optimization design of cascaded classifiers. Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR\u201905), San Diego, CA, USA."},{"key":"ref_47","unstructured":"Kotsiantis, S.B., Zaharakis, I., and Pintelas, P. (2007). Supervised machine learning: A review of classification techniques. Emerging Artificial Intelligence Applications in Computer Engineering, IOS Press."},{"key":"ref_48","unstructured":"Viola, P., and Jones, M. (2001, January 8\u201314). Rapid object detection using a boosted cascade of simple features. Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2001, Kauai, HI, USA."},{"key":"ref_49","first-page":"172","article-title":"Research and application of open source video server MJPG-streamer","volume":"5","author":"Chen","year":"2012","journal-title":"Electronic Des. Eng."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"29594","DOI":"10.3390\/s151129594","article-title":"Vision sensor-based road detection for field robot navigation","volume":"15","author":"Lu","year":"2015","journal-title":"Sensors"},{"key":"ref_51","doi-asserted-by":"crossref","unstructured":"Wang, X., Yang, M., Zhu, S., and Lin, Y. (2013, January 8\u201313). Regionlets for generic object detection. Proceedings of the IEEE International Conference on Computer Vision, Sydney, Australia.","DOI":"10.1109\/ICCV.2013.10"},{"key":"ref_52","doi-asserted-by":"crossref","unstructured":"Redmon, J., and Farhadi, A. (2017, January 21\u201326). YOLO9000: Better, faster, stronger. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Honolulu, HI, USA.","DOI":"10.1109\/CVPR.2017.690"}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/20\/18\/5409\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T10:12:07Z","timestamp":1760177527000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/20\/18\/5409"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,9,21]]},"references-count":52,"journal-issue":{"issue":"18","published-online":{"date-parts":[[2020,9]]}},"alternative-id":["s20185409"],"URL":"https:\/\/doi.org\/10.3390\/s20185409","relation":{"has-preprint":[{"id-type":"doi","id":"10.20944\/preprints202007.0326.v1","asserted-by":"object"}]},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,9,21]]}}}