About this Abstract |
Meeting |
1st World Congress on Artificial Intelligence in Materials and Manufacturing (AIM 2022)
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Symposium
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First World Congress on Artificial Intelligence in Materials and Manufacturing (AIM 2022)
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Presentation Title |
Human-Robot Collaboration for the Application of Speckle Patterns Through Learning from Demonstration Techniques |
Author(s) |
Anesia Delia Auguste, Jennifer Ruddock, Erick Braham, Ezra Ameperosa, James Hardin, Andrew Gillman |
On-Site Speaker (Planned) |
Anesia Delia Auguste |
Abstract Scope |
Industry is incorporating more robotic machines and broadening their scope of use. Artisanal processes, which require human experts, are major challenges to automation because robots are typically actuated in a different manner and have disparate sensor packages than human experts. To explore these limits, we explore integrating human users and robots to teach a robotic system to apply high-quality speckle patterns via spray painting for Digital Image Correlation (DIC). DIC is a non-destructive optical method to measure local deformation in a specimen. The accuracy is dependent on the quality of the artisanal applied speckle pattern. By utilizing learning from demonstration (LfD) techniques like Task-Parameterized Gaussian Mixture Model, which empowers experts with little robotics background to intuitively interact with the robot, we developed generalized spray trajectories based on expert kinesthetic teaching of the robot. Overall, we are combining human intuition with machine precision in order to produce high-quality speckle patterns. |
Proceedings Inclusion? |
Undecided |