Publications
2024
Accelerating Laboratory Automation Through Robot Skill Learning For Sample Scraping*
Pizzuto, G., Wang, H., Fakhruldeen, H., Peng, B., Luck, K. S., & Cooper, A. I. (2024). Accelerating Laboratory Automation Through Robot Skill Learning For Sample Scraping*. In 2024 IEEE 20th International Conference on Automation Science and Engineering (CASE) (pp. 2103-2110). IEEE. doi:10.1109/case59546.2024.10711291
Modular, multi-robot integration of laboratories: an autonomous workflow for solid-state chemistry.
Lunt, A. M., Fakhruldeen, H., Pizzuto, G., Longley, L., White, A., Rankin, N., . . . Chong, S. Y. (2024). Modular, multi-robot integration of laboratories: an autonomous workflow for solid-state chemistry.. Chemical science, 15(7), 2456-2463. doi:10.1039/d3sc06206f
Author Correction: Spatial communication systems across languages reflect universal action constraints.
Coventry, K. R., Gudde, H. B., Diessel, H., Collier, J., Guijarro-Fuentes, P., Vulchanova, M., . . . Incel, O. D. (2024). Author Correction: Spatial communication systems across languages reflect universal action constraints.. Nature human behaviour, 8(1), 181. doi:10.1038/s41562-023-01806-3
2023
Spatial communication systems across languages reflect universal action constraints.
Coventry, K. R., Gudde, H. B., Diessel, H., Collier, J., Guijarro-Fuentes, P., Vulchanova, M., . . . Incel, O. D. (2023). Spatial communication systems across languages reflect universal action constraints.. Nature human behaviour, 7(12), 2099-2110. doi:10.1038/s41562-023-01697-4
What is missing in autonomous discovery: open challenges for the community
Maffettone, P. M., Friederich, P., Baird, S. G., Blaiszik, B., Brown, K. A., Campbell, S. I., . . . Sun, S. (n.d.). What is missing in autonomous discovery: open challenges for the community. Digital Discovery, 2(6), 1644-1659. doi:10.1039/d3dd00143a
Go with the flow: deep learning methods for autonomous viscosity estimations.
Walker, M., Pizzuto, G., Fakhruldeen, H., & Cooper, A. I. (2023). Go with the flow: deep learning methods for autonomous viscosity estimations.. Digital discovery, 2(5), 1540-1547. doi:10.1039/d3dd00109a
Modular, Multi-Robot Integration of Laboratories: An Autonomous Solid-State Workflow for Powder X-Ray Diffraction
Leveraging Multi-modal Sensing for Robotic Insertion Tasks in R&D Laboratories
Butterworth, A., Pizzuto, G., Pecyna, L., Cooper, A. I., & Luo, S. (2023). Leveraging Multi-modal Sensing for Robotic Insertion Tasks in R&D Laboratories. In 2023 IEEE 19th International Conference on Automation Science and Engineering (CASE) (pp. 1-8). IEEE. doi:10.1109/case56687.2023.10260414
Leveraging Multi-modal Sensing for Robotic Insertion Tasks in R&D Laboratories
Autonomous biomimetic solid dispensing using a dual-arm robotic manipulator
Jiang, Y., Fakhruldeen, H., Pizzuto, G., Longley, L., He, A., Dai, T., . . . Cooper, A. I. (n.d.). Autonomous biomimetic solid dispensing using a dual-arm robotic manipulator. Digital Discovery, 2(6), 1733-1744. doi:10.1039/d3dd00075c
What is missing in autonomous discovery: Open challenges for the community
2022
Efficient Learning of Inverse Dynamics Models for Adaptive Computed Torque Control
Jorge, D., Pizzuto, G., & Mistry, M. (2022). Efficient Learning of Inverse Dynamics Models for Adaptive Computed Torque Control. In 2022 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS) (pp. 11203-11208). doi:10.1109/IROS47612.2022.9981744
SOLIS: Autonomous Solubility Screening using Deep Neural Networks
Pizzuto, G., De Berardinis, J., Longley, L., Fakhruldeen, H., & Cooper, A. I. (2022). SOLIS: Autonomous Solubility Screening using Deep Neural Networks. In 2022 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS (IJCNN). doi:10.1109/IJCNN55064.2022.9892533
Accelerating Laboratory Automation Through Robot Skill Learning For Sample Scraping
ARChemist: Autonomous Robotic Chemistry System Architecture
Fakhruldeen, H., Pizzuto, G., Glowacki, J., & Cooper, A. I. (2022). ARChemist: Autonomous Robotic Chemistry System Architecture. In 2022 International Conference on Robotics and Automation (ICRA) (pp. 6013-6019). IEEE. doi:10.1109/icra46639.2022.9811996