Identification of Contact Avoidance Zones of Robotic Devices in Human-Robot Collaborative Workspaces

Details

• Personal Author:
  Cheng MH ; Dominguez EG ; Liang C-J ; McKenzie EA Jr.
• Description:
  The objective of this study was to establish a framework for producing indoor maps and locating robotic devices in a manufacturing environment. The framework employs computer vision techniques to construct the map and identify the presence of human workers. It defines the contact avoidance zones around human workers and existing obstacles. Once the location of the robot is identified, the map is used to plan paths to ensure safe human-robot collaboration for mobile and collaborative robots in shared workspaces with humans. The incorporation of avoidance zones into the map allows the robotic devices to anticipate the movements of workers and prevent collisions, this decreases the risk of injuries in collaborative environments. This paper illustrates the implementation of robots evading unforeseen contact with pre-defined contact avoidance zones, employing two distinct examples as demonstration. [Description provided by NIOSH]
• Subjects:
  Automation Manufacturing And Industrial Facilities Occupational Health Safety
• Keywords:
  Author Keywords: Collision Avoidance Collaborative Workspace Emerging Technology Human-robot Interaction Manufacturing Robotics Safety Research Worker Safety
• ISSN:
  2405-8963
• Document Type:
  Text
• Genre:
  Journal Article
• Place as Subject:
  Michigan ; OSHA Region 3 ; OSHA Region 5 ; West Virginia
• CIO:
  National Institute for Occupational Safety and Health (NIOSH)
• Division:
  DSR - Division of Safety Research
• Topic:
  Workplace Safety & Health
• Location:
  North America
• Volume:
  56
• Issue:
  3
• NIOSHTIC Number:
  nn:20069118
• Citation:
  IFAC Pap OnLine 2023 Oct; 56(3):577-582
• Contact Point Address:
  Marvin H. Cheng, National Institute for Occupational Safety and Health, Morgantown, WV 26505 USA
• Email:
  MCheng@cdc.gov
• Federal Fiscal Year:
  2024
• NORA Priority Area:
  Manufacturing
• Peer Reviewed:
  True
• Source Full Name:
  IFAC-PapersOnLine. 3rd Modeling, Estimation and Control Conference: MECC 2023, October 2-5, 2023, Lake Tahoe, Nevada
• Collection(s):
  National Institute for Occupational Safety and Health
• Main Document Checksum:
  urn:sha-512:ba93977d5dbfe7473a348919941b859077a78dd4e79a44827268d4b98d465cce5834a58d2e783ad6dbb301ab678c2dd3d377ae8505cc3f1c91b8253d3692642d
• Download URL:
  https://stacks.cdc.gov/view/cdc/207656/cdc_207656_DS1.pdf
• File Type:
  [PDF - 1014.76 KB ]