• Medientyp: E-Artikel
  • Titel: Flexible sensor concept and an integrated collision sensing for efficient human-robot collaboration using 3D local global sensors
  • Beteiligte: Rashid, Aquib; Alnaser, Ibrahim; Bdiwi, Mohamad; Ihlenfeldt, Steffen
  • Erschienen: Frontiers Media SA, 2023
  • Erschienen in: Frontiers in Robotics and AI, 10 (2023)
  • Sprache: Nicht zu entscheiden
  • DOI: 10.3389/frobt.2023.1028411
  • ISSN: 2296-9144
  • Schlagwörter: Artificial Intelligence ; Computer Science Applications
  • Entstehung:
  • Anmerkungen:
  • Beschreibung: <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>
  • Zugangsstatus: Freier Zugang