{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,10]],"date-time":"2026-02-10T16:51:57Z","timestamp":1770742317671,"version":"3.49.0"},"reference-count":26,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2023,3,28]],"date-time":"2023-03-28T00:00:00Z","timestamp":1679961600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100003141","name":"National Council for Science and Technology, CONACyT, Mexico","doi-asserted-by":"publisher","award":["CB2017-2018-A1-S-26123"],"award-info":[{"award-number":["CB2017-2018-A1-S-26123"]}],"id":[{"id":"10.13039\/501100003141","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Entropy"],"abstract":"<jats:p>This article proposes a decentralized controller for differential mobile robots, providing autonomous navigation and obstacle avoidance by enforcing a formation toward trajectory tracking. The control system relies on dynamic modeling, which integrates evasion forces from obstacles, formation forces, and path-following forces. The resulting control loop can be seen as a dynamic extension of the kinematic model for the differential mobile robot, producing linear and angular velocities fed to the mobile robot\u2019s kinematic model and thus passed to the low-level wheel controller. Using the Lyapunov method, the closed-loop stability is proven for the non-collision case. Experimental and simulated results that support the stability analysis and the performance of the proposed controller are shown.<\/jats:p>","DOI":"10.3390\/e25040582","type":"journal-article","created":{"date-parts":[[2023,3,28]],"date-time":"2023-03-28T07:05:25Z","timestamp":1679987125000},"page":"582","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Bio-Inspired Autonomous Navigation and Formation Controller for Differential Mobile Robots"],"prefix":"10.3390","volume":"25","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0686-5200","authenticated-orcid":false,"given":"Alejandro","family":"Juarez-Lora","sequence":"first","affiliation":[{"name":"Centro de Investigacion en Computacion del Instituto Politecnico Nacional, CIC-IPN, 07738 Ciudad de Mexico, Mexico"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6212-2201","authenticated-orcid":false,"given":"Alejandro","family":"Rodriguez-Angeles","sequence":"additional","affiliation":[{"name":"Centro de Investigacion y de Estudios Avanzados del Instituto Politecnico Nacional, Cinvestav-IPN, 07360 Ciudad de Mexico, Mexico"}]}],"member":"1968","published-online":{"date-parts":[[2023,3,28]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"S\u00e1nchez-Ib\u00e1\u00f1ez, J.R., P\u00e9rez-del-Pulgar, C.J., and Garc\u00eda-Cerezo, A. (2021). Path Planning for Autonomous Mobile Robots: A Review. Sensors, 21.","DOI":"10.3390\/s21237898"},{"key":"ref_2","unstructured":"Arkin, R.C. (1998). Behavior-Based Robotics, MIT Press."},{"key":"ref_3","first-page":"603","article-title":"Multiple vehicle cooperation and collision avoidance in automated vehicles: Survey and an AI-enabled conceptual framework","volume":"13","author":"Muzahid","year":"2023","journal-title":"Sci. Rep. Nat."},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Wesselh\u00f6ft, M., Hinckeldeyn, J., and Kreutzfeldt, J. (2022). Controlling Fleets of Autonomous Mobile Robots with Reinforcement Learning: A Brief Survey. Robotics, 11.","DOI":"10.3390\/robotics11050085"},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Loukatos, D., Petrongonas, E., Manes, K., Kyrtopoulos, I.-V., Dimou, V., and Arvanitis, K.G. (2021). A Synergy of Innovative Technologies towards Implementing an Autonomous DIY Electric Vehicle for Harvester-Assisting Purposes. Machines, 9.","DOI":"10.3390\/machines9040082"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"2708","DOI":"10.1109\/TIE.2021.3070508","article-title":"OpenStreetMap-Based Autonomous Navigation for the Four Wheel-Legged Robot Via 3D-Lidar and CCD Camera","volume":"69","author":"Li","year":"2022","journal-title":"IEEE Trans. Ind. Electron."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"674","DOI":"10.26599\/TST.2021.9010012","article-title":"Deep reinforcement learning based mobile robot navigation: A review","volume":"26","author":"Zhu","year":"2021","journal-title":"Tsinghua Sci. Technol."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"20210762","DOI":"10.1098\/rspa.2021.0762","article-title":"Strategies for guided acoustic wave inspection using mobile robots","volume":"478","author":"Zhang","year":"2022","journal-title":"Proc. R. Soc. Publ."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"100","DOI":"10.1109\/MCOM.2013.6495768","article-title":"MEMS inertial sensors: A tutorial overview","volume":"51","author":"Shaeffer","year":"2013","journal-title":"IEEE Commun. Mag."},{"key":"ref_10","first-page":"6","article-title":"Visual SLAM algorithms: A survey from 2010 to 2016","volume":"9","author":"Taketomi","year":"2017","journal-title":"IPSJ Trans. Comput. Vis. Appl."},{"key":"ref_11","unstructured":"Granlund, G., and Knutsson, H. (2013). Signal Processing for Computer Vision, Springer."},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"De Ponte Muller, F. (2017). Survey on Ranging Sensors and Cooperative Techniques for Relative Positioning of Vehicles. Sensors, 17.","DOI":"10.3390\/s17020271"},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Sand, S., Zhang, S., M\u00fchlegg, M., Falconi, G., Zhu, C., Kr\u00fcger, T., and Nowak, S. (2013, January 25\u201327). Swarm Exploration and Navigation on Mars. Proceedings of the 2013 International Conference on Localization and GNSS (ICL-GNSS), Torino, Italy.","DOI":"10.1109\/ICL-GNSS.2013.6577272"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"847","DOI":"10.1364\/JOSAA.453318","article-title":"Biomimetic Navigation System using a Polarization Sensor and a Binocular Camera","volume":"39","author":"Li","year":"2022","journal-title":"J. Opt. Soc. Am. A. Opt. Image. Sci. Vis."},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Ducatelle, F., Di Caro, G., Pinciroli, C., Mondada, F., and Gambardella, L. (2011, January 25\u201330). Communication assisted navigation in robotic swarms: Self-organization and cooperation. Proceedings of the 2011 IEEE\/RSJ International Conference on Intelligent Robots and Systems, San Francisco, CA, USA.","DOI":"10.1109\/IROS.2011.6094454"},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Zakaria, W.N.W., Mahmood, I.A.-T., Shamsudin, A.U., Rahman, M.A.A., and Tomari, M.R.M. (2022, January 6\u20138). ROS-based SLAM and Path Planning for Autonomous Unmanned Surface Vehicle Navigation System. Proceedings of the 2022 IEEE 5th International Symposium in Robotics and Manufacturing Automation (ROMA), Malacca, Malaysia.","DOI":"10.1109\/ROMA55875.2022.9915665"},{"key":"ref_17","first-page":"1","article-title":"Flocking Control and Pattern Motion in a Modified Cucker-Smale Model","volume":"53","author":"Li","year":"2016","journal-title":"Korean Math. Soc."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"2617","DOI":"10.1109\/TAC.2010.2061070","article-title":"Cucker-Smale Flocking With Inter-Particle Bonding Forces","volume":"55","author":"Park","year":"2018","journal-title":"IEEE Trans. Autom. Control."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"2556","DOI":"10.1109\/TMECH.2016.2580303","article-title":"Implementation Studies of Robot Swarm Navigation Using Potential Functions and Panel Methods","volume":"21","author":"Merheb","year":"2016","journal-title":"IEEE\/ASME Trans. Mechatron."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"487","DOI":"10.1038\/35035023","article-title":"Simulating dynamical features of escape panic","volume":"407","author":"Helbing","year":"2000","journal-title":"Nature"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1287\/trsc.1040.0108","article-title":"Self-organized pedestrian crowd dynamics: Experiments, simulations, and design solutions","volume":"39","author":"Helbing","year":"2005","journal-title":"Transp. Sci."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"27","DOI":"10.1007\/s43684-022-00045-z","article-title":"Multi-agent reinforcement learning for autonomous vehicles: A survey","volume":"2","author":"Dinneweth","year":"2022","journal-title":"Auton. Intell. Syst."},{"key":"ref_23","unstructured":"Canudas de Wit, C., and Siliciano, B. (1997). Theory of Robot Control, Springer. Tercera Edici\u00f3n."},{"key":"ref_24","first-page":"135","article-title":"Bio-inspired decentralized autonomous robot mobile navigation control for multi agent systems","volume":"54","year":"2018","journal-title":"Kibernetica"},{"key":"ref_25","unstructured":"(2020). version R2020a (Standard No. MATLAB)."},{"key":"ref_26","unstructured":"(2018). TurtleBot3 Specifications, ROBOTIS Ltd."}],"container-title":["Entropy"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1099-4300\/25\/4\/582\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T19:05:02Z","timestamp":1760123102000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1099-4300\/25\/4\/582"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,3,28]]},"references-count":26,"journal-issue":{"issue":"4","published-online":{"date-parts":[[2023,4]]}},"alternative-id":["e25040582"],"URL":"https:\/\/doi.org\/10.3390\/e25040582","relation":{},"ISSN":["1099-4300"],"issn-type":[{"value":"1099-4300","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,3,28]]}}}