{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,18]],"date-time":"2026-08-18T05:06:42Z","timestamp":1787029602037,"version":"build-2736575974"},"reference-count":33,"publisher":"MDPI AG","issue":"12","license":[{"start":{"date-parts":[[2014,12,5]],"date-time":"2014-12-05T00:00:00Z","timestamp":1417737600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>This paper presents a performance analysis of two open-source, laser  scanner-based Simultaneous Localization and Mapping (SLAM) techniques (i.e., Gmapping and Hector SLAM) using a Microsoft Kinect to replace the laser sensor. Furthermore, the paper proposes a new system integration approach whereby a Linux virtual machine is used to run the open source SLAM algorithms. The experiments were conducted in two different environments; a small room with no features and a typical office corridor with desks and chairs. Using the data logged from real-time experiments, each SLAM technique was simulated and tested with different parameter settings. The results show that the system is able to achieve real time SLAM operation. The  system implementation offers a simple and reliable way to compare the performance of Windows-based SLAM algorithm with the algorithms typically implemented in a Robot Operating System (ROS). The results also indicate that certain modifications to the default laser scanner-based parameters are able to improve the map accuracy. However, the limited field of view and range of Kinect\u2019s depth sensor often causes the map to be inaccurate, especially in featureless areas, therefore the Kinect sensor is not a direct replacement for a laser scanner, but rather offers a feasible alternative for 2D SLAM tasks.<\/jats:p>","DOI":"10.3390\/s141223365","type":"journal-article","created":{"date-parts":[[2014,12,5]],"date-time":"2014-12-05T10:20:05Z","timestamp":1417774805000},"page":"23365-23387","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":36,"title":["Performance Analysis of the Microsoft Kinect Sensor for 2D Simultaneous Localization and Mapping (SLAM) Techniques"],"prefix":"10.3390","volume":"14","author":[{"given":"Kamarulzaman","family":"Kamarudin","sequence":"first","affiliation":[{"name":"Center of Excellence for Advanced Sensor Technology (CEASTech), Universiti Malaysia Perlis (UniMAP), Taman Muhibbah, Jejawi, 02600 Arau, Perlis, Malaysia"},{"name":"School of Mechatronics Engineering, Universiti Malaysia Perlis (UniMAP), Pauh Putra Campus, 02600 Arau, Perlis, Malaysia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3557-2204","authenticated-orcid":false,"given":"Syed","family":"Mamduh","sequence":"additional","affiliation":[{"name":"Center of Excellence for Advanced Sensor Technology (CEASTech), Universiti Malaysia Perlis (UniMAP), Taman Muhibbah, Jejawi, 02600 Arau, Perlis, Malaysia"},{"name":"School of Mechatronics Engineering, Universiti Malaysia Perlis (UniMAP), Pauh Putra Campus, 02600 Arau, Perlis, Malaysia"},{"name":"School of Microelectronic Engineering, Universiti Malaysia Perlis (UniMAP), Pauh Putra Campus, 02600 Arau, Perlis, Malaysia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ali","family":"Shakaff","sequence":"additional","affiliation":[{"name":"Center of Excellence for Advanced Sensor Technology (CEASTech), Universiti Malaysia Perlis (UniMAP), Taman Muhibbah, Jejawi, 02600 Arau, Perlis, Malaysia"},{"name":"School of Mechatronics Engineering, Universiti Malaysia Perlis (UniMAP), Pauh Putra Campus, 02600 Arau, Perlis, Malaysia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7108-215X","authenticated-orcid":false,"given":"Ammar","family":"Zakaria","sequence":"additional","affiliation":[{"name":"Center of Excellence for Advanced Sensor Technology (CEASTech), Universiti Malaysia Perlis (UniMAP), Taman Muhibbah, Jejawi, 02600 Arau, Perlis, Malaysia"},{"name":"School of Mechatronics Engineering, Universiti Malaysia Perlis (UniMAP), Pauh Putra Campus, 02600 Arau, Perlis, Malaysia"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2014,12,5]]},"reference":[{"key":"ref_1","unstructured":"Hiebert-Treuer, B. (2007). An Introduction to Robot SLAM (Simultaneous Localization And Mapping). [Bachelor's Theses, Middlebury College]."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"JinWoo, C., Sunghwan, A., and Wan Kyun, C. (2005, January 2\u20136). Robust sonar feature detection for the SLAM of mobile robot. Edmonton, Canada.","DOI":"10.1109\/IROS.2005.1545284"},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Mallios, A., Ridao, P., Ribas, D., Maurelli, F., and Petillot, Y. (2010, January 18\u201322). EKF-SLAM for AUV navigation under probabilistic sonar scan-matching. Taipei, Taiwan.","DOI":"10.1109\/IROS.2010.5649246"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"198","DOI":"10.1007\/s11263-010-0361-7","article-title":"RSLAM: A System for Large-Scale Mapping in Constant-Time Using Stereo","volume":"94","author":"Mei","year":"2011","journal-title":"Int. J. Comput. Vis"},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Marks, T.K., Howard, A., Bajracharya, M., Cottrell, G.W., and Matthies, L. (2008, January 19\u201323). Gamma-SLAM: Using stereo vision and variance grid maps for SLAM in unstructured environments. Pasadena, CA, USA.","DOI":"10.1109\/ROBOT.2008.4543781"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"1144","DOI":"10.1016\/j.robot.2012.08.008","article-title":"Real-time 6-DOF multi-session visual SLAM over large-scale environments","volume":"61","author":"McDonald","year":"2013","journal-title":"Robot. Auton. Syst"},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Kohlbrecher, S., von Stryk, O., Meyer, J., and Klingauf, U. (2011, January 1\u20135). A flexible and scalable SLAM system with full 3D motion estimation. Kyoto, Japan.","DOI":"10.1109\/SSRR.2011.6106777"},{"key":"ref_8","unstructured":"Eliazar, A.I., and Parr, R. (1, January 26). DP-SLAM 2.0. New Orleans, LA, USA."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"34","DOI":"10.1109\/TRO.2006.889486","article-title":"Improved techniques for grid mapping with rao-blackwellized particle filters","volume":"23","author":"Grisetti","year":"2007","journal-title":"IEEE Trans. Robot"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"30","DOI":"10.1016\/j.robot.2006.06.007","article-title":"Fast and accurate SLAM with Rao\u2013Blackwellized particle filters","volume":"55","author":"Grisetti","year":"2007","journal-title":"Robot. Auton. Syst"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"110","DOI":"10.12720\/joace.1.2.110-114","article-title":"Fast 3D Map Matching Localisation Algorithm","volume":"1","author":"Pinto","year":"2013","journal-title":"J. Autom. Control Eng"},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Salas-Moreno, R.F., Newcombe, R.A., Strasdat, H., Kelly, P.H.J., and Davison, A.J. (2013, January 23\u201328). SLAM++: Simultaneous Localisation and Mapping at the Level of Objects. Portland, OR, USA.","DOI":"10.1109\/CVPR.2013.178"},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Newcombe, R.A., Izadi, S., Hilliges, O., Molyneaux, D., Kim, D., Davison, A.J., Kohi, P., Shotton, J., Hodges, S., and Fitzgibbon, A. (2011, January 26\u201329). KinectFusion: Real-time dense surface mapping and tracking. Basel, Switzerland.","DOI":"10.1109\/ISMAR.2011.6092378"},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Endres, F., Hess, J., Engelhard, N., Sturm, J., Cremers, D., and Burgard, W. (2012, January 14\u201318). An evaluation of the RGB-D SLAM system. St. Paul, MN, USA.","DOI":"10.1109\/ICRA.2012.6225199"},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Sturm, J., Engelhard, N., Endres, F., Burgard, W., and Cremers, D. (2012, January 7\u201312). A benchmark for the evaluation of RGB-D SLAM systems. Vilamoura, Portugal.","DOI":"10.1109\/IROS.2012.6385773"},{"key":"ref_16","unstructured":"Whelan, T., Kaess, M., Fallon, M., Johannsson, H., Leonard, J., and McDonald, J. (2012, January 9\u201310). Kintinuous: Spatially Extended KinectFusion. Sydney, Australia."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"189","DOI":"10.1007\/s10514-012-9321-0","article-title":"OctoMap: An efficient probabilistic 3D mapping framework based on octrees","volume":"34","author":"Hornung","year":"2013","journal-title":"Auton. Robot"},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Mirowski, P., Palaniappan, R., and Tin Kam, H. (2012, January 23\u201324). Depth camera SLAM on a low-cost WiFi mapping robot. Woburn, MA, USA.","DOI":"10.1109\/TePRA.2012.6215673"},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Oliver, A., Kang, S., Wunsche, B.C., and MacDonald, B. (2012, January 26\u201328). Using the Kinect as a navigation sensor for mobile robotics. Dunedin, New Zealand.","DOI":"10.1145\/2425836.2425932"},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Zug, S., Penzlin, F., Dietrich, A., Tran Tuan, N., and Albert, S. (2012, January 16\u201318). Are laser scanners replaceable by Kinect sensors in robotic applications?. Magdeburg, Germany.","DOI":"10.1109\/ROSE.2012.6402619"},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Kamarudin, K., Mamduh, S.M., Shakaff, A.Y.M., Saad, S.M., Zakaria, A., Abdullah, A.H., and Kamarudin, L.M. (2013, January 8\u201310). Method to Convert Kinect's 3D Depth Data to a 2D Map for Indoor SLAM. Kuala Lumpur, Malaysia.","DOI":"10.1109\/CSPA.2013.6530050"},{"key":"ref_22","unstructured":"PrimeSense The PrimeSense 3D Awareness Sensor. Available online: www.primesense.com."},{"key":"ref_23","unstructured":"Microsoft Kinect for Windows. Available online: http:\/\/www.microsoft.com\/en-us\/kinectforwindows."},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Grisetti, G., Stachniss, C., and Burgard, W. (2005, January 18\u201322). Improving Grid-based SLAM with Rao-Blackwellized Particle Filters by Adaptive Proposals and Selective Resampling. Barcelona, Spain.","DOI":"10.15607\/RSS.2005.I.009"},{"key":"ref_25","unstructured":"ROS.org Gmapping: Package Summary. Available online: http:\/\/wiki.ros.org\/gmapping."},{"key":"ref_26","unstructured":"ROS.org Hector_mapping: Package Summary. Available online: http:\/\/wiki.ros.org\/hector_mapping."},{"key":"ref_27","unstructured":"Murphy, K.P. (December, January 30). Bayesian Map Learning in Dynamic Environments. Denver, CO, USA."},{"key":"ref_28","unstructured":"Doucet, A., Freitas, N.D., Murphy, K.P., and Russell, S.J. (July, January 30). Rao-Blackwellised Particle Filtering for Dynamic Bayesian Networks. Stanford, CA, USA."},{"key":"ref_29","unstructured":"Montemerlo, M., Roy, N., and Thrun, S. (2003, January 27\u201331). Perspectives on standardization in mobile robot programming: The Carnegie Mellon Navigation (CARMEN) Toolkit. Las Vegas, NV, USA."},{"key":"ref_30","unstructured":"Montemerlo, M., Roy, N., Thrun, S., H\u00e4hnel, D., Stachniss, C., and Glover, J. CARMEN\u2014The Carnegie Mellon Robot Navigation Toolkit. Available online: http:\/\/carmen.sourceforge.net\/."},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Doucet, A., de Freitas, N., and Gordon, N. (2001). Sequential Monte Carlo Methods in Practice, Springer.","DOI":"10.1007\/978-1-4757-3437-9"},{"key":"ref_32","unstructured":"Eliazar, A., and Parr, R. (2003, January 9\u201315). DP-SLAM: Fast, robust simultaneous localization and mapping without predetermined landmarks. Acapulco, Mexico."},{"key":"ref_33","unstructured":"Lucas, B.D., and Kanade, T. (1983, January 24\u201328). An iterative image registration technique with an application to stereo vision. Vancouver, Canada."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/14\/12\/23365\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T21:10:30Z","timestamp":1760217030000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/14\/12\/23365"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2014,12,5]]},"references-count":33,"journal-issue":{"issue":"12","published-online":{"date-parts":[[2014,12]]}},"alternative-id":["s141223365"],"URL":"https:\/\/doi.org\/10.3390\/s141223365","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2014,12,5]]}}}