{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,26]],"date-time":"2026-03-26T02:16:07Z","timestamp":1774491367785,"version":"3.50.1"},"reference-count":43,"publisher":"MDPI AG","issue":"22","license":[{"start":{"date-parts":[[2020,11,10]],"date-time":"2020-11-10T00:00:00Z","timestamp":1604966400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100011011","name":"Junta de Andaluc\u00eda","doi-asserted-by":"publisher","award":["UMA18-FEDERJA-090"],"award-info":[{"award-number":["UMA18-FEDERJA-090"]}],"id":[{"id":"10.13039\/501100011011","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003339","name":"Consejo Superior de Investigaciones Cient\u00edficas","doi-asserted-by":"publisher","award":["RTI2018-093421-B-I00"],"award-info":[{"award-number":["RTI2018-093421-B-I00"]}],"id":[{"id":"10.13039\/501100003339","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Reactivity is a key component for autonomous vehicles navigating on natural terrains in order to safely avoid unknown obstacles. To this end, it is necessary to continuously assess traversability by processing on-board sensor data. This paper describes the case study of mobile robot Andabata that classifies traversable points from 3D laser scans acquired in motion of its vicinity to build 2D local traversability maps. Realistic robotic simulations with Gazebo were employed to appropriately adjust reactive behaviors. As a result, successful navigation tests with Andabata using the robot operating system (ROS) were performed on natural environments at low speeds.<\/jats:p>","DOI":"10.3390\/s20226423","type":"journal-article","created":{"date-parts":[[2020,11,10]],"date-time":"2020-11-10T14:10:41Z","timestamp":1605017441000},"page":"6423","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":21,"title":["Reactive Navigation on Natural Environments by Continuous Classification of Ground Traversability"],"prefix":"10.3390","volume":"20","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8940-2465","authenticated-orcid":false,"given":"Jorge L.","family":"Mart\u00ednez","sequence":"first","affiliation":[{"name":"Robotics and Mechatronic Lab, Andaluc\u00eda Tech, Universidad de M\u00e1laga, 29071 M\u00e1laga, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1095-4775","authenticated-orcid":false,"given":"Jes\u00fas","family":"Morales","sequence":"additional","affiliation":[{"name":"Robotics and Mechatronic Lab, Andaluc\u00eda Tech, Universidad de M\u00e1laga, 29071 M\u00e1laga, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2303-1742","authenticated-orcid":false,"given":"Manuel","family":"S\u00e1nchez","sequence":"additional","affiliation":[{"name":"Robotics and Mechatronic Lab, Andaluc\u00eda Tech, Universidad de M\u00e1laga, 29071 M\u00e1laga, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8186-7671","authenticated-orcid":false,"given":"Mariano","family":"Mor\u00e1n","sequence":"additional","affiliation":[{"name":"Robotics and Mechatronic Lab, Andaluc\u00eda Tech, Universidad de M\u00e1laga, 29071 M\u00e1laga, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6064-3927","authenticated-orcid":false,"given":"Antonio J.","family":"Reina","sequence":"additional","affiliation":[{"name":"Robotics and Mechatronic Lab, Andaluc\u00eda Tech, Universidad de M\u00e1laga, 29071 M\u00e1laga, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8174-1331","authenticated-orcid":false,"given":"J. 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Proceedings of the IEEE Intelligent Vehicles Symposium, Washington, DC, USA."},{"key":"ref_4","unstructured":"Chen, L., Yang, J., and Kong, H. (June, January 29). Lidar-histogram for fast road and obstacle detection. Proceedings of the IEEE International Conference on Robotics and Automation, Marina Bay Sands, Singapore."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"1373","DOI":"10.1016\/j.engappai.2013.01.006","article-title":"Terrain traversability analysis methods for unmanned ground vehicles: A survey","volume":"26","author":"Papadakis","year":"2013","journal-title":"Eng. Appl. Artif. Intell."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"91","DOI":"10.1177\/0278364907073777","article-title":"Tradeoffs Between Directed and Autonomous Driving on the Mars Exploration Rovers","volume":"26","author":"Biesiadecki","year":"2007","journal-title":"Int. J. Robot. Res."},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Pan, Y., Xu, X., Wang, Y., Ding, X., and Xiong, R. (2019, January 6\u20138). GPU accelerated real-time traversability mapping. Proceedings of the IEEE International Conference on Robotics and Biomimetics, Dali, China.","DOI":"10.1109\/ROBIO49542.2019.8961816"},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Suger, B., Steder, B., and Burgard, W. (2015, January 26\u201330). Traversability analysis for mobile robots in outdoor environments: A semi-supervised learning approach based on 3D-Lidar data. Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), Seattle, WA, USA.","DOI":"10.1109\/ICRA.2015.7139749"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"220","DOI":"10.1108\/SR-03-2013-644","article-title":"3D traversability awareness for rough terrain mobile robots","volume":"34","author":"Bellone","year":"2014","journal-title":"Sens. Rev."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"48","DOI":"10.1016\/j.robot.2016.07.002","article-title":"Computing an unevenness field from 3D laser range data to obtain traversable region around a mobile robot","volume":"84","author":"Reddy","year":"2016","journal-title":"Robot. Auton. Syst."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"600","DOI":"10.1002\/rob.21657","article-title":"Normal Distributions Transform Traversability Maps: LIDAR-Only Approach for Traversability Mapping in Outdoor Environments","volume":"34","author":"Ahtiainen","year":"2017","journal-title":"J. Field Robot."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"296","DOI":"10.1109\/TITS.2017.2769218","article-title":"Learning traversability from point clouds in challenging scenarios","volume":"19","author":"Bellone","year":"2018","journal-title":"IEEE Trans. Intell. Transp. Syst."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"1695","DOI":"10.1109\/LRA.2018.2801794","article-title":"Learning ground traversability from simulations","volume":"3","author":"Guzzi","year":"2018","journal-title":"IEEE Robot. Autom. Lett."},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Mart\u00ednez, J.L., Mor\u00e1n, M., Morales, J., Robles, A., and S\u00e1nchez, M. (2020). Supervised learning of natural-terrain traversability with synthetic 3D laser scans. Appl. Sci., 10.","DOI":"10.3390\/app10031140"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"940","DOI":"10.1002\/rob.21700","article-title":"Driving on point clouds: Motion planning, trajectory optimization, and terrain assessment in generic nonplanar environments","volume":"34","author":"Krusi","year":"2017","journal-title":"J. Field Robot."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"42","DOI":"10.1002\/rob.21521","article-title":"Terrain classification in complex three-dimensional outdoor environments","volume":"32","author":"Teniente","year":"2015","journal-title":"J. Field Robot."},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Ye, C., and Borenstein, J. (2004, January 2). T-transformation: Traversability Analysis for Navigation on Rugged Terrain. Proceedings of the Defense and Security Symposium, Orlando, FL, USA.","DOI":"10.1117\/12.542576"},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Thrun, S., Montemerlo, M., and Aron, A. (2006, January 16\u201319). Probabilistic Terrain Analysis For High-Speed Desert Driving. Proceedings of the Robotics: Science and Systems II, Philadelphia, PA, USA.","DOI":"10.15607\/RSS.2006.II.021"},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Pang, C., Zhong, X., Hu, H., Tian, J., Peng, X., and Zeng, J. (2018). Adaptive Obstacle Detection for Mobile Robots in Urban Environments Using Downward-Looking 2D LiDAR. Sensors, 18.","DOI":"10.3390\/s18061749"},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Zhang, K., Yang, Y., Fu, M., and Wang, M. (2019). Traversability assessment and trajectory planning of unmanned ground vehicles with suspension systems on rough terrain. Sensors, 19.","DOI":"10.3390\/s19204372"},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Mart\u00ednez, J.L., Mandow, A., Reina, A.J., Cantador, T.J., Morales, J., and Garc\u00eda-Cerezo, A. (2013, January 3\u20137). Navigability analysis of natural terrains with fuzzy elevation maps from ground-based 3D range scans. Proceedings of the IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS), Tokyo, Japan.","DOI":"10.1109\/IROS.2013.6696559"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"101","DOI":"10.1007\/s10846-013-9957-9","article-title":"Improving point cloud accuracy obtained from a moving platform for consistent pile attack pose estimation","volume":"75","author":"Almqvist","year":"2014","journal-title":"J. Intell. Robot. Syst. Theory Appl."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"104","DOI":"10.1016\/j.robot.2016.10.017","article-title":"Continuous mapping and localization for autonomous navigation in rough terrain using a 3D laser scanner","volume":"88","author":"Droeschel","year":"2017","journal-title":"Robot. Auton. Syst."},{"key":"ref_24","unstructured":"Yi, Y., Mengyin, F., Xin, Y., Guangming, X., and Gong, J.W. (2010, January 21\u201324). Autonomous Ground Vehicle Navigation Method in Complex Environment. Proceedings of the IEEE Intelligent Vehicles Symposium, San Diego, CA, USA."},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Mart\u00ednez, J.L., Mor\u00e1n, M., Morales, J., Reina, A.J., and Zafra, M. (2018). Field navigation using fuzzy elevation maps built with local 3D laser scans. Appl. Sci., 8.","DOI":"10.3390\/app8030397"},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"P\u00e9rez-Higueras, N., Jard\u00f3n, A., Rodr\u00edguez, A., and Balaguer, C. (2020). 3D Exploration and Navigation with Optimal-RRT Planners for Ground Robots in Indoor Incidents. Sensors, 20.","DOI":"10.3390\/s20010220"},{"key":"ref_27","unstructured":"Koenig, K., and Howard, A. (October, January 28). Design and use paradigms for Gazebo, an open-source multi-robot simulator. Proceedings of the IEEE-RSJ International Conference on Intelligent Robots and Systems (IROS), Sendai, Japan."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"511","DOI":"10.1007\/s10846-018-0851-3","article-title":"Physics Based Path Planning for Autonomous Tracked Vehicle in Challenging Terrain","volume":"95","author":"Sebastian","year":"2019","journal-title":"J. Intell. Robot. Syst."},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Sch\u00e4fer, H., Hach, A., Proetzsch, M., and Berns, K. (2008, January 19\u201323). 3D Obstacle Detection and Avoidance in Vegetated Off-road Terrain. Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), Pasadena, CA, USA.","DOI":"10.1109\/ROBOT.2008.4543323"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"917","DOI":"10.1177\/0278364902021010841","article-title":"Autonomous rover navigation on unknown terrains: Functions and integration","volume":"21","author":"Lacroix","year":"2002","journal-title":"Int. J. Robot. Res."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/s10514-012-9309-9","article-title":"Autonomous over-the-horizon navigation using LIDAR data","volume":"34","author":"Rekleitis","year":"2013","journal-title":"Auton. Rob."},{"key":"ref_32","unstructured":"Langer, D., Rosenblatt, J., and Hebert, M. (1994, January 8\u201313). An Integrated System for Autonomous Off-Road Navigation. Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), San Diego, CA, USA."},{"key":"ref_33","first-page":"767","article-title":"Global and regional path planners for integrated planning and navigation","volume":"22","author":"Howard","year":"2005","journal-title":"J. Field Robot."},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Pfrunder, A., Borges, P.V.K., Romero, A.R., Catt, G., and Elfes, A. (2017, January 24\u201328). Real-time autonomous ground vehicle navigation in heterogeneous environments using a 3D LiDAR. Proceedings of the IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS), Vancouver, BC, Canada.","DOI":"10.1109\/IROS.2017.8206083"},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"Rohmer, E., Singh, S.P.N., and Freese, M. (2013, January 3\u20137). V-REP: A Versatile and Scalable Robot Simulation Framework. Proceedings of the IEEE International Conference on Intelligent Robots and Systems (IROS), Tokyo, Japan.","DOI":"10.1109\/IROS.2013.6696520"},{"key":"ref_36","unstructured":"Quigley, M., Gerkey, B., Conley, K., Faust, J., Foote, T., Leibs, J., Berger, E., Wheeler, R., and Ng, A. (2009, January 12\u201317). ROS: An open-source robot operating system. Proceedings of the IEEE International Conference on Robotics and Automation: Workshop on Open Source Software (ICRA), Kobe, Japan."},{"key":"ref_37","first-page":"2825","article-title":"Scikit-learn: Machine learning in Python","volume":"12","author":"Pedregosa","year":"2011","journal-title":"J. Mach. Learn. Res."},{"key":"ref_38","unstructured":"Mandow, A., Mart\u00ednez, J.L., Morales, J., Blanco, J.L., Garc\u00eda-Cerezo, A., and Gonz\u00e1lez, J. (November, January 29). Experimental kinematics for wheeled skid-steer mobile robots. Proceedings of the IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS), San Diego, CA, USA."},{"key":"ref_39","doi-asserted-by":"crossref","unstructured":"S\u00e1nchez, M., Mart\u00ednez, J.L., Morales, J., Robles, A., and Mor\u00e1n, M. (2019, January 18\u201320). Automatic generation of labeled 3D point clouds of natural environments with Gazebo. Proceedings of the IEEE International Conference on Mechatronics (ICM), Ilmenau, Germany.","DOI":"10.1109\/ICMECH.2019.8722866"},{"key":"ref_40","doi-asserted-by":"crossref","unstructured":"Mart\u00ednez, J.L., Morales, J., Reina, A.J., Mandow, A., Pequeno-Boter, A., and Garc\u00eda-Cerezo, A. (2015, January 17\u201319). Construction and calibration of a low-cost 3D laser scanner with 360 field of view for mobile robots. Proceedings of the IEEE International Conference on Industrial Technology (ICIT), Seville, Spain.","DOI":"10.1109\/ICIT.2015.7125091"},{"key":"ref_41","doi-asserted-by":"crossref","unstructured":"Rankin, A., Bajracharya, M., Huertas, A., Howard, A., Moghaddam, B., Brennan, S., Ansar, A., Tang, B., Turmon, M., and Matthies, L. (2010, January 7). Stereo-vision-based perception capabilities developed during the Robotics Collaborative Technology Alliances program. Proceedings of the SPIE Defense, Security, and Sensing, Orlando, FL, USA.","DOI":"10.1117\/12.852644"},{"key":"ref_42","doi-asserted-by":"crossref","unstructured":"Reina, A.J., Mart\u00ednez, J.L., Mandow, A., Morales, J., and Garc\u00eda-Cerezo, A. (2014, January 8\u201311). Collapsible Cubes: Removing Overhangs from 3D Point Clouds to Build Local Navigable Elevation Maps. Proceedings of the IEEE\/ASME International Conference on Advanced Intelligent Mechatronics (AIM), Besan\u00e7on, France.","DOI":"10.1109\/AIM.2014.6878213"},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"1238","DOI":"10.1177\/0278364913495721","article-title":"Reinforcement learning in robotics: A survey","volume":"32","author":"Kober","year":"2013","journal-title":"Int. J. Robot. 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