{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,4]],"date-time":"2026-05-04T10:45:29Z","timestamp":1777891529029,"version":"3.51.4"},"reference-count":60,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2025,4,9]],"date-time":"2025-04-09T00:00:00Z","timestamp":1744156800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100002322","name":"CAPES","doi-asserted-by":"publisher","award":["001"],"award-info":[{"award-number":["001"]}],"id":[{"id":"10.13039\/501100002322","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>This paper presents an obstacle avoidance technique for a mobile robot in human-robot collaborative (HRC) tasks. The proposed solution uses fuzzy logic rules and a convolutional neural network (CNN) in an integrated approach to detect objects during vehicle movement. The goal is to improve the robot\u2019s navigation autonomously and ensure the safety of people and equipment in dynamic environments. Using this technique, it is possible to provide important references to the robot\u2019s internal control system, guiding it to continuously adjust its velocity and yaw in order to avoid obstacles (humans and moving objects) while following the path planned for its task. The approach aims to improve operational safety without compromising productivity, addressing critical challenges in collaborative robotics. The system was tested in a simulated environment using the Robot Operating System (ROS) and Gazebo to demonstrate the effectiveness of navigation and obstacle avoidance. The results obtained with the application of the proposed technique indicate that the framework allows real-time adaptation and safe interaction between robot and obstacles in complex and changing industrial workspaces.<\/jats:p>","DOI":"10.3390\/s25082387","type":"journal-article","created":{"date-parts":[[2025,4,9]],"date-time":"2025-04-09T07:49:02Z","timestamp":1744184942000},"page":"2387","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":11,"title":["Obstacle Avoidance Technique for Mobile Robots at Autonomous Human-Robot Collaborative Warehouse Environments"],"prefix":"10.3390","volume":"25","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8093-4633","authenticated-orcid":false,"given":"Lucas C.","family":"Sousa","sequence":"first","affiliation":[{"name":"Federal Center for Technological Education Celso Suckow da Fonseca, CEFET, Rio de Janeiro 20271-110, Brazil"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9964-0478","authenticated-orcid":false,"given":"Yago M. R.","family":"Silva","sequence":"additional","affiliation":[{"name":"Instituto de Engenharia de Sistemas e Computadores, Tecnologia e Ci\u00eancia, INESC Technology and Science, 4200-465 Porto, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0749-7956","authenticated-orcid":false,"given":"Vin\u00edcius B.","family":"Schettino","sequence":"additional","affiliation":[{"name":"Federal Center for Technological Education of Minas Gerais, CEFET-MG, Belo Horizonte 30421-169, Brazil"}]},{"ORCID":"https:\/\/orcid.org\/0009-0006-9683-9864","authenticated-orcid":false,"given":"Tatiana M. B.","family":"Santos","sequence":"additional","affiliation":[{"name":"Science Computer Department, Campus da Praia Vermelha, Federal Fluminense University, Niter\u00f3i 24210-240, Brazil"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5671-5588","authenticated-orcid":false,"given":"Alessandro R. L.","family":"Zachi","sequence":"additional","affiliation":[{"name":"Federal Center for Technological Education Celso Suckow da Fonseca, CEFET, Rio de Janeiro 20271-110, Brazil"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0224-9323","authenticated-orcid":false,"given":"Josiel A.","family":"Gouv\u00eaa","sequence":"additional","affiliation":[{"name":"Federal Center for Technological Education Celso Suckow da Fonseca, CEFET, Rio de Janeiro 20271-110, Brazil"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6916-700X","authenticated-orcid":false,"given":"Milena F.","family":"Pinto","sequence":"additional","affiliation":[{"name":"Federal Center for Technological Education Celso Suckow da Fonseca, CEFET, Rio de Janeiro 20271-110, Brazil"}]}],"member":"1968","published-online":{"date-parts":[[2025,4,9]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Ntakolia, C., Moustakidis, S., and Siouras, A. (2023). 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