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This paper proposes a method that enables a robot to classify a terrain in various outdoor environments using terrain information that it recognizes without the assistance of a user; then, it creates a three-dimensional (3D) semantic map. The proposed self-supervised learning system stores data on the appearance of the ground data using image features extracted by observing the movement of humans and vehicles while the robot is stopped. It learns about the surrounding environment using a support vector machine with the stored data, which is divided into terrains where people or vehicles have moved and other regions. This makes it possible to learn which terrain an object can travel on using a self-supervised learning and image-processing methods. Then the robot can recognize the current environment and simultaneously build a 3D map using the RGB-D iterative closest point algorithm with a RGB-D sensor (Kinect). To complete the 3D semantic map, it adds semantic terrain information to the map. <\/jats:p>","DOI":"10.1155\/2014\/394942","type":"journal-article","created":{"date-parts":[[2014,4,7]],"date-time":"2014-04-07T23:06:04Z","timestamp":1396911964000},"page":"394942","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":0,"title":["Self-Supervised Sensor Learning and Its Application: Building 3D Semantic Maps Using Terrain Classification"],"prefix":"10.1177","volume":"10","author":[{"given":"Chuho","family":"Yi","sequence":"first","affiliation":[{"name":"Future IT R&D Lab, LG Electronics, Seoul 137-724, Republic of Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Donghui","family":"Song","sequence":"additional","affiliation":[{"name":"Department of HCI and Robotics, University of Science and Technology, Daejeon 305-350, Republic of Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5746-9596","authenticated-orcid":false,"given":"Jungwon","family":"Cho","sequence":"additional","affiliation":[{"name":"Department of Computer Education, Jeju National University, Jeju 690-756, Republic of Korea"},{"name":"Department of Mathematics and Computer Science, Salisbury University, Salisbury, MD 21801, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"179","published-online":{"date-parts":[[2014,4,6]]},"reference":[{"issue":"1","key":"B1-2014-394942","first-page":"18","volume":"2","author":"Yi C.","year":"2012","journal-title":"Smart Computing Review"},{"issue":"3","key":"B2-2014-394942","first-page":"321","volume":"7","author":"Li X.","year":"2013","journal-title":"International Journal of Smart Home"},{"first-page":"708","volume-title":"Proceedings of the IEEE International Conference on Intelligent Robots and Systems","author":"Talukder A.","key":"B3-2014-394942"},{"key":"B4-2014-394942","doi-asserted-by":"publisher","DOI":"10.1109\/ACVMOT.2005.111"},{"key":"B5-2014-394942","doi-asserted-by":"publisher","DOI":"10.1109\/TRO.2005.855994"},{"key":"B6-2014-394942","doi-asserted-by":"publisher","DOI":"10.1002\/rob.20279"},{"key":"B7-2014-394942","doi-asserted-by":"publisher","DOI":"10.1109\/ROBOT.2006.1641763"},{"volume-title":"Proceedings of the NASA Science Technology Conference","author":"Christopher A. 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