Al-Okby, M.F.R.; Roddelkopf, T.; Fleischer, H.; Ewald, H.; Thurow, K.: Evaluating a Novel Gas Sensor for Ambient Monitoring in
Automated in Life Science Laboratories. Sensors, 22(1), 2022, 8161view
online
Al-Okby, M.F.R.; Neubert, S.; Roddelkopf, T.; Fleischer, H.; Thurow, K.: Evaluating the IAQ and TOVC Parameter-Based Sensors
for Hazardous Gases Detection and Alarming Systems. Sensors. 22(4), 2022, 1473 view online
Al-Okby, M. F. R.; Neubert, S.; Roddelkopf, T.; Thurow, K.: Mobile Detection and Alarming Systems for Hazardous Gas and Volatile
Chemicals in Laboratories and Industrial Locations.Sensors,21(23), 2021, 8128
(doi:10.3390/s21238128).view online
Burgdorf, S.-J.; Roddelkopf, T.; Thurow, K.: Automated Crystallization Monitoring in Material Development using Computer
Vision and Neuronal Networks. Chemie, Ingenieur, Technik, 2024 (in print)
Duan, C.; Junginger, S.; Thurow, K.;
Liu, H.: Learning Stereo Visual Odometry Approach Based on Optical Flows and Depth Information. Appl. Sci. 2023, 13(10) (doi:
10.3390/app13105842) view online
Huang, J.; Junginger, S.; Liu, H.; Thurow, K.: Correcting of Unexpected Localization Measurement for Indoor Automatic Mobile Robot
Transportation Based on Neural Networks. Transportation Safety and Environment. 2023.(doi:10.1093/tse/tdad019) view online
Huang, J.; Junginger, S.; Liu, H.; Thurow, K.: Indoor Positioning Systems for Mobile Robots: A
Review. Robotics. 2023.R 12(2), pp. 47 (doi:10.3390/robotics/12020047)
view
online
Huang, J.; Junginger, S.; Liu, H.; Thurow, K.: Indoor
Positioning Systems for Mobile Robots. Scholarly Community Encyclopedia. 2023. view online
Jiang, Y.; Fajkruldeen, H.;
Pizzuot, G.; Longley, L.; He, A.; Dai, T.; Clowes, R. Rankin, N.; Cooper, A. I.: Autonomous biomimetic solid dispensing using a dual arm robotic manipulator. Digital Discovery, 2023
(2), pp. 1733-1744. (doi:10.1039/D3DD00075C)
Lunt, A.M.; Fakhruldeen,
H.; Pizzuto, G.; Longley, L.; White, A.; Rankin, N.; Clowes, R.; Alston, B.; Gigli, L.; Day, G.M.; Cooper, A.I.; Chong, S.Y.: Modular, multi-robot integration of laboratories: an autonomous
workflow for solid-state chemistry. Chemical Science, 2024, view online
Maffetone, P. M.;
Friederich P.; ...; Pizzuto, G.; et al: What is missing in autonomous discovery: open challenges for the community. Digital Discovery, 2023 (2), pp. 1644-1659.
(doi:10.1039/D3DD00143A)
Neubert, S.; Roddelkopf, T.; Al-Okby, M. F. R.; Junginger, S.; Thurow, K.: Flexible IoT Gas Sensor Node for
automated Life Science Environments using stationary and mobile Robots.Sensors, 21(21), 2021, 7347 (doi:10.3390/s21217347).view online
Thurow, K.; Neubert, S.: Innovative Sensor Technology for Emergency Detection in Life Science Laboratories. Book Chapter. In:
Deserno, T.: Accident and Emergency Informatics. IOS Book on A&EI, 2022, pp. 62-87 (doi:10.3233/SHTI220008).view online
Walker, M.; Pizzuto, G.; Fakhruldeen, H.; Cooper, A. I.: Go with the flow: deep learning methods for autonomous viscosity
estimations. Digital Discovery, 2023 (2), pp. 1540-1547. (doi:10.1039/D3DD00109A)
Wu, H.; Junginger, S.; Roddelkopf; T.; Liu, H.; Thurow, K.: BLE Beacons for Sample Position Estimation in a Life Science Automation Laboratory.
Transportation Safety and Environment (in print)
(doi:10.1093/tse/tdad033)
Wu, H.; Liu, H.; Roddelkopf, T.; Thurow, K.: BLE Beacon Based Floor Detection in a Multi-Floor Automation Laboratory. Transportation Safety and
Environment. 2023.(doi:10.1093/tse/tdad024). view online
Zhu, Q.; Johal, J.; Widdowson, D.E.; Pang, Z.F.; Li, B.Y.; Kane, C.M.; Kurlin, V.; Day, G.M.; Little, M.A.; Cooper, A.I.: Analogy
Powered by Prediction and Structural Invariants: Computationally Led Discovery of a Mesoporous Hydrogen-Bonded Organic Cage Crystal. Journal of the American Chemical
Society. 144(22), pp: 9893-9901, doi:10.1021/jacs.2c02653 view online
Peer Reviewed Proceedings
Al-Okby, M.F.R.; Roddelkopf, T.; Fleischer, H.; Ewald,
H.; Thurow, K.: Testing and Integration of Commercial Hydrogen Sensor for Ambient Monitoring Application. Proceedings, IEEE 17th International Symposium on Applied Computational
Intelligence and Informatics (SACI), Timisoara (Romania), 2023, May 23-26, pp. 000811-000818. (doi:10.1109/SACI58269.2023.10158643) view online
Al-Okby, M.F.R.; Neubert, S.; Roddelkopf, T.; Thurow, K.; Fleischer, H.: Evaluating of IAQ-index and TVOC as
Measurement Parameters for IoT-based Hazardous Gases Detection and Alarming Systems. Proceedings, IEEE 20th Jubilee World Symposium on Applied Machine Intelligence and
Informatics. March 2-5, 2022 (accepted)
Al-Okby, M.F.R.; Neubert, S.; Roddelkopf, T.; Thurow, K.: Integration and Testing of Novel MOX
Gas Sensors for IoT-based Indoor Air Quality Monitoring. Proceedings, 21st International Symposium on Computational Intelligence and Informatics. Budapest (Hungary), November 18-20,
2021, 173-180. view online
Al-Okby, M.F.R.; Roddelkopf, T.; Neubert, S.; Fleischer, H.; Thurow, K.: Robot-based Environmental Monitoring in Life Science
Laboratories. Proceedings, ICCC 2022, 10th Jubilee IEEE International Conference on Computational Cybernetics and Cyber-Medical Systems. July 6-9 2022, Reykjavik, Iceland
Butterworth, A.; Pizzuto, G.; Pecyna, L.; Cooper, A. I.: Leveraging Multi-modal Sensing for Robotic Insertion Tasks in R&D Laboratories. Proceedings,
2023 IEEE 19th International Conference on Automation Science and Engineering (CASE). Auckland (New Zealand), 2023, pp. 1-8. (doi:10.1109/CASE56687.2023.10260414).
Burgdorf,
S.-J.; Roddelkopf, T.; Cooper, A., Thurow, K.: Computer Vision Based Crystallization Monitoring in Automated Laboratories. Proceedings. The
2023 International Conference on Images, Signals, and Computing (ICISC 2023). 22.-27.05.2023, Chengu (China). 1278302 (doi:1117/12.2692822).
Fakhruldeen, H.; Pizzuto, G.; Głowacki, J.; Cooper, A.I.: ARChemist: Autonomous Robotic Chemistry System Architecture. Proceedings, 2022 International Conference
on Robotics and Automation (ICRA), Philadelphia (PA, USA), pp. 6013-6019. (doi:10.1109/ICRA46639.2022.9811996)
Huang, J.; Thurow, K.; Junginger, S.; Fleischer, H.; Liu, H.; Do, V. Q.: IoT Based Labware Tracking During Mobile Robot Transportation.
Proceedings,IEEE International Conference on Control, Automation and Information (ICCAIS 2023), 27.-29.11.2023, Hanoi (VN), presented
Pizzuto, G.; De Berardinis, J.; Longley, L.; Fakhruldeen, H.; Cooper, A. I.: SOLIS: Autonomous Solubility screening using Deep Neural Networks. Proceedings,
2022 International Joint Conference in Neural Networks (IJCNN), Padua (It) 2022, pp.1-7. (doi:10.1109/IJCNN55064.2022.9892533