{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,30]],"date-time":"2026-04-30T21:14:46Z","timestamp":1777583686173,"version":"3.51.4"},"reference-count":27,"publisher":"MDPI AG","issue":"11","license":[{"start":{"date-parts":[[2022,5,31]],"date-time":"2022-05-31T00:00:00Z","timestamp":1653955200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100012456","name":"National Social Science Foundation of China","doi-asserted-by":"publisher","award":["BIA200191"],"award-info":[{"award-number":["BIA200191"]}],"id":[{"id":"10.13039\/501100012456","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012456","name":"National Social Science Foundation of China","doi-asserted-by":"publisher","award":["21GCYB04"],"award-info":[{"award-number":["21GCYB04"]}],"id":[{"id":"10.13039\/501100012456","id-type":"DOI","asserted-by":"publisher"}]},{"name":"China Association of Higher Education","award":["BIA200191"],"award-info":[{"award-number":["BIA200191"]}]},{"name":"China Association of Higher Education","award":["21GCYB04"],"award-info":[{"award-number":["21GCYB04"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Aiming at the problems of low mapping accuracy, slow path planning efficiency, and high radar frequency requirements in the process of mobile robot mapping and navigation in an indoor environment, this paper proposes a four-wheel drive adaptive robot positioning and navigation system based on ROS. By comparing and analyzing the mapping effects of various 2D-SLAM algorithms (Gmapping, Karto SLAM, and Hector SLAM), the Karto SLAM algorithm is used for map building. By comparing the Dijkstra algorithm with the A* algorithm, the A* algorithm is used for heuristic searches, which improves the efficiency of path planning. The DWA algorithm is used for local path planning, and real-time path planning is carried out by combining sensor data, which have a good obstacle avoidance performance. The mathematical model of four-wheel adaptive robot sliding steering was established, and the URDF model of the mobile robot was established under a ROS system. The map environment was built in Gazebo, and the simulation experiment was carried out by integrating lidar and odometer data, so as to realize the functions of mobile robot scanning mapping and autonomous obstacle avoidance navigation. The communication between the ROS system and STM32 is realized, the packaging of the ROS chassis node is completed, and the ROS chassis node has the function of receiving speed commands and feeding back odometer data and TF transformation, and the slip rate of the four-wheel robot in situ steering is successfully measured, making the chassis pose more accurate. Simulation tests and experimental verification show that the system has a high precision in environment map building and can achieve accurate navigation tasks.<\/jats:p>","DOI":"10.3390\/s22114172","type":"journal-article","created":{"date-parts":[[2022,5,31]],"date-time":"2022-05-31T05:25:42Z","timestamp":1653974742000},"page":"4172","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":72,"title":["Research and Implementation of Autonomous Navigation for Mobile Robots Based on SLAM Algorithm under ROS"],"prefix":"10.3390","volume":"22","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2831-1201","authenticated-orcid":false,"given":"Jianwei","family":"Zhao","sequence":"first","affiliation":[{"name":"School of Mechanical Electronic & Information Engineering, China University of Mining and Technology, Beijing 100089, China"},{"name":"Institute of Artificial Intelligence, University of Science and Technology Beijing, Beijing 100083, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6639-372X","authenticated-orcid":false,"given":"Shengyi","family":"Liu","sequence":"additional","affiliation":[{"name":"School of Mechanical Electronic & Information Engineering, China University of Mining and Technology, Beijing 100089, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jinyu","family":"Li","sequence":"additional","affiliation":[{"name":"School of Mechanical Electronic & Information Engineering, China University of Mining and Technology, Beijing 100089, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2022,5,31]]},"reference":[{"key":"ref_1","first-page":"211","article-title":"Review on Key Common Technologies for Intelligent Applications of Industrial Robots","volume":"41","author":"Lining","year":"2021","journal-title":"J. Vib. Meas. Diagn."},{"key":"ref_2","first-page":"2193","article-title":"Research on Depth Vision Based Mobile Robot Autonomous Navigation in Underground Coal Mine","volume":"45","author":"Hongwei","year":"2020","journal-title":"J. China Coal Soc."},{"key":"ref_3","unstructured":"Dong, J. (2020). Research on SLAM and Navigation for Laser Vision Fusion of Mobile Robot in Indoor Complex Environment. [Master\u2019s Thesis, Harbin Institute of Technology]."},{"key":"ref_4","unstructured":"Maosheng, L., Di, W., and Hao, Y. (2019, January 24\u201325). Deploy Indoor 2D Laser SLAM on a Raspberry Pi-Based Mobile Robot. Proceedings of the 2019 11th International Conference on Intelligent Human-Machine Systems and Cybernetics (IHMSC), Hangzhou, China."},{"key":"ref_5","unstructured":"Peng, W. (2021). Research on SLAM Technology and Path Planning Algorithms for Unmanned Vehicle. [Master\u2019s Thesis, Harbin Institute of Technology]."},{"key":"ref_6","first-page":"76","article-title":"Design and Implementation of Indoor Positioning and Navigation System of Mobile Robot Based on ROS and Lidar","volume":"36","author":"Jiaxin","year":"2018","journal-title":"Mach. Electron."},{"key":"ref_7","unstructured":"Tian, T. (2012). Design and Experiment Research of Four Wheel Independent Drive Chassis. [Master\u2019s Thesis, Chinese Academy of Agricultural Mechanization Sciences]."},{"key":"ref_8","unstructured":"Yunze, L. (2016). Research on SLAM of Indoor Robot Based on Lidar. [Master\u2019s Thesis, South China University of Technology]."},{"key":"ref_9","unstructured":"Wenzhi, L. (2018). Research and Implementation of SLAM and Path Planning Algorithm Based on Lidar. [Master\u2019s Thesis, Harbin Institute of Technology]."},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Hanagi, R.R., Gurav, O.S., and Khandekar, S.A. (2021, January 2\u20134). SLAM using AD* Algorithm with Absolute Odometry. Proceedings of the 2021 6th International Conference for Convergence in Technology (I2CT), Maharashtra, India.","DOI":"10.1109\/I2CT51068.2021.9418118"},{"key":"ref_11","first-page":"75","article-title":"A Survey of Front-end Method for Graph-based Slam Under Large-scale Environment","volume":"47","author":"Zhongli","year":"2015","journal-title":"J. Harbin Inst. Technol."},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Zhang, W., Zhai, G., Yue, Z., Pan, T., and Cheng, R. (2021). Research on Visual Positioning of a Roadheader and Construction of an Environment Map. Appl. Sci., 11.","DOI":"10.3390\/app11114968"},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Johannsson, H., Kaess, M., Fallon, M., and Leonard, J.J. (2013, January 6\u201310). Temporally Scalable Visual SLAM Using a Reduced Pose Graph. Proceedings of the 2013 IEEE International Conference on Robotics and Automation, Karlsruhe, Germany.","DOI":"10.1109\/ICRA.2013.6630556"},{"key":"ref_14","first-page":"13","article-title":"Overview of 3D Lidar SLAM algorithms","volume":"42","author":"Zhiguo","year":"2021","journal-title":"Chin. J. Sci. Instrum."},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Han, D., Li, Y., Song, T., and Liu, Z. (2020). Multi-Objective Optimization of Loop Closure Detection Parameters for Indoor 2D Simultaneous Localization and Mapping. Sensors, 20.","DOI":"10.3390\/s20071906"},{"key":"ref_16","unstructured":"(2020, November 27). SLAM Benchmarking. Available online: http:\/\/ais.informatik.uni-freiburg.de\/slamevaluation\/datasets.php."},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Verma, D., Messon, D., Rastogi, M., and Singh, A. (2021, January 19\u201320). Comparative Study of Various Approaches Of Dijkstra Algorithm. Proceedings of the 2021 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS), Greater Noida, India.","DOI":"10.1109\/ICCCIS51004.2021.9397200"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"507","DOI":"10.1016\/j.procs.2021.01.034","article-title":"A Systematic Literature Review of A* Pathfinding","volume":"179","author":"Foead","year":"2021","journal-title":"Procedia Comput. Sci."},{"key":"ref_19","first-page":"903","article-title":"Mobile Robot Path Planning Based on an Improved A* Algorithm","volume":"40","author":"Zhao","year":"2018","journal-title":"Robot"},{"key":"ref_20","first-page":"346","article-title":"Mobile Robot Path Planning Based on Improved A* Algorithm and Dynamic Window Method","volume":"42","author":"Wang","year":"2020","journal-title":"Robot"},{"key":"ref_21","first-page":"14","article-title":"Path Planning of Greenhouse Robot Based on Fusion of Improved A* Algorithm and Dynamic Window Approach","volume":"52","author":"Cailian","year":"2021","journal-title":"Trans. Chin. Soc. Agric. Mach."},{"key":"ref_22","first-page":"32","article-title":"Kinematics Analysis and Whole Positioning Method of Logistics Robot","volume":"33","author":"Si","year":"2020","journal-title":"J. Hunan Inst. Sci. Technol. (Nat. Sci.)"},{"key":"ref_23","unstructured":"Chengyu, L. (2017). Research on Trajectory Tracking Control of Four-wheel Sliding Steering Robot. [Master\u2019s Thesis, Dalian Maritime University]."},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Song, K., Chiu, Y., and Kang, L. (2018, January 7\u201310). Navigation control design of a mobile robot by integrating obstacle avoidance and LiDAR SLAM. Proceedings of the 2018 IEEE International Conference on Systems, Man, and Cybernetics (SMC), Miyazaki, Japan.","DOI":"10.1109\/SMC.2018.00317"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"96","DOI":"10.1017\/S0263574717000194","article-title":"A safe area search and map building algorithm for a wheeled mobile robot in complex unknown cluttered environments","volume":"36","author":"Savkin","year":"2018","journal-title":"Robotica"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"1182","DOI":"10.1109\/TMECH.2019.2963439","article-title":"Active SLAM for mobile robots with area coverage and obstacle avoidance","volume":"25","author":"Yongbo","year":"2020","journal-title":"IEEE\/ASME Trans. Mechatron."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"5969","DOI":"10.1109\/LRA.2020.3010455","article-title":"Online Exploration and Coverage Planning in Unknown Obstacle-Cluttered Environments","volume":"5","author":"Kan","year":"2020","journal-title":"IEEE Robot. Autom. 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