Machine Learning for Robotics/Manufacturing Applications:
Teleoperated Robotic Surgery via Transfer Learning:
In austere environments, teleoperated surgical robots could save the lives of critically injured patients if they can perform complex surgical maneuvers under limited communication bandwidth. The bandwidth requirement is reduced by transferring atomic surgical actions (referred to as “surgemes") instead of the low-level kinematic information. While such a policy reduces the bandwidth requirement, it requires accurate recognition of the surgemes. In this work, we demonstrate that transfer learning across surgical tasks can boost the performance of surgeme recognition.
- Glebys Gonzalez, Mythra Balakuntala, Mridul Agarwal, Tomas Low, Bruce Knoth, Andrew W Kirkpatrick, Jessica McKee, Gregory Hager, Vaneet Aggarwal, Yexiang Xue, Richard Voyles, and Juan Wachs, "ASAP: A Semi-Autonomous Precise System for Telesurgery during Communication Delays," IEEE Transactions on Medical Robotics and Bionics, vol. 5, no. 1, pp. 66-78, Feb. 2023, doi: 10.1109/TMRB.2023.3239674
- Mridul Agarwal and Vaneet Aggarwal, "Blind Decision Making: Reinforcement Learning with Delayed Observations," in Proc. ICAPS, Aug 2021.
- Mridul Agarwal, Glebys Gonzalez, Mythra V. Balakuntala, Md Masudur Rahman, Vaneet Aggarwal, Richard M. Voyles, Yexiang Xue, and Juan Wachs, "Dexterous Skill Transfer between Surgical Procedures for Teleoperated Robotic Surgery," in Proc. 30th IEEE International Conference on Robot & Human Interactive Communication (RO-MAN), Aug 2021.
- Md Masudur Rahman, Mythra Varun Balakuntala Srinivasa Mur, Mridul Agarwal, Upinder Kaur, Vishnunandan Lakshmi Venkatesh, Glebys Gonzalez, Natalia Sanchez Tamayo, Yexiang Xue, Richard Voyles, Vaneet Aggarwal, and Juan Wachs, "SARTRES: A Semi-Autonomous Robot TeleopeRation Environment for Surgery," AE-CAI 2020 Special Issue of the Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization Journal (TCIV), Nov 2020, DOI: 10.1080/21681163.2020.1834878.
- Glebys Gonzalez, Mridul Agarwal, Mythra Varun Balakuntala Srinivasa Murthy, Md Masudur Rahman, Upinder Kaur, Juan Wachs, Richard Voyles, Vaneet Aggarwal, and Yexiang Xu, "DESERTS:Delay-Tolerant Semi-Autonomous Robot Teleoperation for Surgery," in Proc. IEEE International Conference on Robotics and Automation (ICRA), May-Jun 2021.
- MMd Masudur Rahman, Natalia Sanchez-Tamayo, Glebys Gonzalez, Mridul Agarwal, Vaneet Aggarwal, Richard Voyles, Yexiang Xue, Juan Wachs, "Transferring Dexterous Surgical Skill Knowledge between Robots for Semi-autonomous Teleoperation," in Proc. IEEE International Conference on Robot and Human Interactive Communication (Ro-Man), Oct 2019.
Machine Learning for Manufacturing:
Today's manufacturing starts with CAD models. The CAD model carries all the geometrical information of the workpiece (e.g., surface position, size, fluctuations etc.) and influences the entire planning for manufacturing processes. Due to the complexity of an engineering CAD model, the manufacturing industry usually decomposes the CAD model into several geometrical features - called the machining features. The machining features serve certain functions of the final product and also require typical machining processes. This CAD model decomposition and feature-recognition processes together are called machining feature identification, which is the focus of our work, where efficient data representation techniques and machine learning approaches are used.
- Xingyu Fu, Fengfeng Zhou, Dheeraj Peddireddy, Zhengyang Kang, Martin Byung-Guk Jun, and Vaneet Aggarwal, "An FEA surrogate model with Boundary Oriented Graph Embedding approach," Accepted to Journal of Computational Design and Engineering, Feb 2023.
- Xingyu Fu, Dheeraj Peddireddy, Vaneet Aggarwal, and Martin Byung-Guk Jun, "Improved Dexel Representation: A 3D CNN Geometry Descriptor for Manufacturing CAD,," IEEE Transactions on Industrial Informatics, vol. 18, no. 9, pp. 5882-5892, Sept. 2022, doi: 10.1109/TII.2021.3136167.
- Dheeraj Peddireddy, Xingyu Fu, Anirudh Shankar, Haobo Wang, Byung Gun Joung, Vaneet Aggarwal, John W. Sutherland, and Martin Byung-Guk Jun, "Identifying Manufacturability and Machining Processes using Deep 3D Convolutional Networks," Journal of Manufacturing Processes, vol. 64, pp. 1336-1348, Apr 2021.
- Dheeraj Peddireddy, Xingyu Fu, Haobo Wang, Byung Gun Joung, Vaneet Aggarwal, John W. Sutherland, and Martin Byung-Guk Jun, "Deep Learning Based Approach for Identifying Conventional Machining Processes from CAD Data ," in Proc. NAMRC, Jun 2020.
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