{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,13]],"date-time":"2026-01-13T11:55:44Z","timestamp":1768305344195,"version":"3.49.0"},"reference-count":18,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2026,1,10]],"date-time":"2026-01-10T00:00:00Z","timestamp":1768003200000},"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 an immersive teleoperation framework for service robots that combines real-time 3D human pose estimation with a Virtual Reality (VR) interface to support intuitive, natural robot control. The operator is tracked using MediaPipe for 2D landmark detection and an Intel RealSense D455 RGB-D (Red-Green-Blue plus Depth) camera for depth acquisition, enabling 3D reconstruction of key joints. Joint angles are computed using efficient vector operations and mapped to the kinematic constraints of an anthropomorphic arm on the CHARMIE service robot. A VR-based telepresence interface provides stereoscopic video and head-motion-based view control to improve situational awareness during manipulation tasks. Experiments in real-world object grasping demonstrate reliable arm teleoperation and effective telepresence; however, vision-only estimation remains limited for axial rotations (e.g., elbow and wrist yaw), particularly under occlusions and unfavorable viewpoints. The proposed system provides a practical pathway toward low-cost, sensor-driven, immersive human\u2013robot interaction for service robotics in dynamic environments.<\/jats:p>","DOI":"10.3390\/s26020471","type":"journal-article","created":{"date-parts":[[2026,1,12]],"date-time":"2026-01-12T08:20:37Z","timestamp":1768206037000},"page":"471","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Teleoperation System for Service Robots Using a Virtual Reality Headset and 3D Pose Estimation"],"prefix":"10.3390","volume":"26","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5909-0827","authenticated-orcid":false,"given":"Tiago","family":"Ribeiro","sequence":"first","affiliation":[{"name":"Automation and Robotics Laboratory, Algoritmi Center, University of Minho, 4800-058 Guimaraes, Portugal"}]},{"given":"Eduardo","family":"Fernandes","sequence":"additional","affiliation":[{"name":"Automation and Robotics Laboratory, Algoritmi Center, University of Minho, 4800-058 Guimaraes, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0009-0006-0720-0883","authenticated-orcid":false,"given":"Ant\u00f3nio","family":"Ribeiro","sequence":"additional","affiliation":[{"name":"Automation and Robotics Laboratory, Algoritmi Center, University of Minho, 4800-058 Guimaraes, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0009-0005-7550-1533","authenticated-orcid":false,"given":"Carolina","family":"Lopes","sequence":"additional","affiliation":[{"name":"Automation and Robotics Laboratory, Algoritmi Center, University of Minho, 4800-058 Guimaraes, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6438-1223","authenticated-orcid":false,"given":"Fernando","family":"Ribeiro","sequence":"additional","affiliation":[{"name":"Automation and Robotics Laboratory, Algoritmi Center, University of Minho, 4800-058 Guimaraes, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9475-9020","authenticated-orcid":false,"given":"Gil","family":"Lopes","sequence":"additional","affiliation":[{"name":"LIACC\u2014Laboratory of Artificial Intelligence and Computer Science, Polytechnic Institute of Porto, 4200-072 Porto, Portugal"}]}],"member":"1968","published-online":{"date-parts":[[2026,1,10]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Pisla, D., Bleuler, H., Rodic, A., Vaida, C., and Pisla, A. 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