{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,31]],"date-time":"2025-12-31T18:16:50Z","timestamp":1767205010546,"version":"build-2238731810"},"reference-count":20,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2023,4,6]],"date-time":"2023-04-06T00:00:00Z","timestamp":1680739200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Robot. AI"],"abstract":"<jats:p>Human-robot collaboration with traditional industrial robots is a cardinal step towards agile manufacturing and re-manufacturing processes. These processes require constant human presence, which results in lower operational efficiency based on current industrial collision avoidance systems. The work proposes a novel local and global sensing framework, which discusses a flexible sensor concept comprising a single 2D or 3D LiDAR while formulating occlusion due to the robot body. Moreover, this work extends the previous local global sensing methodology to incorporate local (co-moving) 3D sensors on the robot body. The local 3D camera faces toward the robot occlusion area, resulted from the robot body in front of a single global 3D LiDAR. Apart from the sensor concept, this work also proposes an efficient method to estimate sensitivity and reactivity of sensing and control sub-systems The proposed methodologies are tested with a heavy-duty industrial robot along with a 3D LiDAR and camera. The integrated local global sensing methods allow high robot speeds resulting in process efficiency while ensuring human safety and sensor flexibility.<\/jats:p>","DOI":"10.3389\/frobt.2023.1028411","type":"journal-article","created":{"date-parts":[[2023,4,6]],"date-time":"2023-04-06T01:16:00Z","timestamp":1680743760000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":2,"title":["Flexible sensor concept and an integrated collision sensing for efficient human-robot collaboration using 3D local global sensors"],"prefix":"10.3389","volume":"10","author":[{"given":"Aquib","family":"Rashid","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ibrahim","family":"Alnaser","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mohamad","family":"Bdiwi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Steffen","family":"Ihlenfeldt","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1965","published-online":{"date-parts":[[2023,4,6]]},"reference":[{"key":"B1","volume-title":"Lightweight robots in manual assembly\u2013best to start simply","author":"Bauer","year":"2016"},{"key":"B2","doi-asserted-by":"publisher","first-page":"239","DOI":"10.1016\/j.rcim.2018.11.002","article-title":"Dynamic speed and separation monitoring for collaborative robot applications\u2013concepts and performance","volume":"58","author":"Byner","year":"2019","journal-title":"Robotics Computer-Integrated Manuf."},{"key":"B3","doi-asserted-by":"crossref","DOI":"10.1109\/ROBOT.2010.5509125","article-title":"Multiple depth\/presence sensors: Integration and optimal placement for human\/robot coexistence","author":"Flacco","year":"2010"},{"key":"B4","doi-asserted-by":"crossref","DOI":"10.1109\/ICRA.2012.6225245","article-title":"A depth space approach to human-robot collision avoidance","author":"Flacco","year":"2012"},{"key":"B5","doi-asserted-by":"publisher","first-page":"2280","DOI":"10.1016\/j.patcog.2014.01.005","article-title":"Automatic generation and detection of highly reliable fiducial markers under occlusion","volume":"47","author":"Garrido-Jurado","year":"2014","journal-title":"Pattern Recognit."},{"key":"B6","first-page":"99","volume-title":"Safe, flexible and productive human-robot-collaboration for disassembly of lithium-ion batteries, Recycling of Lithium-Ion Batteries","author":"Gerbers","year":"2018"},{"key":"B7","doi-asserted-by":"publisher","first-page":"731","DOI":"10.5937\/fmet1904731h","article-title":"A strategy for human-robot collaboration in taking products apart for remanufacture","volume":"474","author":"Huang","year":"2019","journal-title":"Fme Trans."},{"key":"B8","volume-title":"Demystifying collaborative industrial robots","year":"2020"},{"key":"B9","doi-asserted-by":"crossref","DOI":"10.1109\/IROS.2007.4399208","article-title":"Fast vision-based minimum distance determination between known and unkown objects","author":"Kuhn","year":"2007"},{"key":"B10","doi-asserted-by":"publisher","first-page":"4027","DOI":"10.1080\/00207543.2019.1578906","article-title":"Human-robot collaboration in disassembly for sustainable manufacturing","volume":"5712","author":"Liu","year":"2019","journal-title":"Int. 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