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Advanced 6D Sensor Development to Support Utilization of Cobot in High-accuracy Inspection

Published

Author(s)

Helen Qiao

Abstract

Collaborative robot, also called Cobot, with the advantages of being safer and more cost-effective, is playing an important role in factory 4.0. Being more flexible, cobot has been deployed in a wide variety of domains, for example, machine tending, material handling, packaging, assembly, drilling, riveting, welding, inspection, three-dimensional (3D) printing, etc. However, Cobots have their challenges in accuracy and rigidity compared with traditional industrial robots. These challenges have become obstacles when implementing cobots in high-accuracy applications. Thus, developing technologies to support cobots to overcome the accuracy challenge is critical to the success of utilizing cobots in these applications. This paper presents an advanced sensor development at the National Institute of Standards and Technology (NIST), to support using a Universal robot (UR) in high-accuracy inspection via accuracy enhancement. The smart target is designed as a motorized target working with a vision-based system to acquire six-dimensional (6D) information (x, y, z, roll, pitch, and yaw) of a robot. Methodologies were developed to support the cobot accuracy enhancement. A use case was built up at the NIST's prognostics and health management lab using real-time sensor feedback and closed-loop control to improve the robot's performance.
Proceedings Title
IEEE Proceedings of 2023 International Conference on Automation Science and Engineering
Conference Dates
August 26-29, 2023
Conference Location
Auckland, NZ
Conference Title
2023 International Conference on Automation Science and Engineering (IEEE CASE 2023)

Keywords

Advanced Sensing, Prognostics and Health Management (PHM), Robot High-accuracy Applications, Cobot, Accuracy Enhancement

Citation

Qiao, H. (2023), Advanced 6D Sensor Development to Support Utilization of Cobot in High-accuracy Inspection, IEEE Proceedings of 2023 International Conference on Automation Science and Engineering, Auckland, NZ, [online], https://doi.org/10.1109/CASE56687.2023.10260671, https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=936489 (Accessed June 14, 2024)

Issues

If you have any questions about this publication or are having problems accessing it, please contact reflib@nist.gov.

Created September 28, 2023, Updated October 4, 2023