Publications by Mechatronics and Dynamics

Are you looking for publications by Section of Mechatronics, Robotics & System Dynamics? On this page you can find all the publications made by the Section of Mechatronics, Robotics & System Dynamics - Department of Biological & Chemical Engineering, Aarhus University.

Below you can find a list of all the publications, their publishing date, their author(s), and title. The list can be sorted by date, author, and title:

List of Publications

Sortér efter: Dato | Forfatter | Titel

Zhou, Z., Li, L., Wang, R. & Zhang, X. (2020). Experimental Eye-in-hand Calibration for Industrial Mobile Manipulators. I 2020 IEEE International Conference on Mechatronics and Automation, ICMA 2020 (s. 582-587). Artikel 9233585 IEEE. https://doi.org/10.1109/ICMA49215.2020.9233585

Zhou, Z., Li, L., Fürsterling, A., Durocher, H., Mouridsen, J. & Zhang, X. (2022). Learning-based object detection and localization for a mobile robot manipulator in SME production. Robotics and Computer-Integrated Manufacturing, 73, Artikel 102229. https://doi.org/10.1016/j.rcim.2021.102229

Zhou, Z., Li, L. & Zhang, X. (2021). Deep Learning on 3D Object Detection for Automatic Plug-in Charging Using a Mobile Manipulator. I 2021 IEEE International Conference on Robotics and Automation (ICRA) (s. 4148-4154). IEEE. https://doi.org/10.1109/ICRA48506.2021.9561106

Zhou, Z., Yang, X., Wang, H. & Zhang, X. (2022). Digital Twin with Integrated Robot-Human/Environment Interaction Dynamics for an Industrial Mobile Manipulator. Proceedings - IEEE International Conference on Robotics and Automation (ICRA), 5041-5047. https://doi.org/10.1109/ICRA46639.2022.9812004

Zhou, Z., Yang, X., Wang, H. & Zhang, X. (2022). Coupled dynamic modeling and experimental validation of a collaborative industrial mobile manipulator with human-robot interaction. Mechanism and Machine Theory, 176, Artikel 105025. https://doi.org/10.1016/j.mechmachtheory.2022.105025

Zhou, Z., Yang, X. & Zhang, X. (2025). Variable impedance control on contact-rich manipulation of a collaborative industrial mobile manipulator: An imitation learning approach. Robotics and Computer-Integrated Manufacturing, 92, Artikel 102896. https://doi.org/10.1016/j.rcim.2024.102896

Zhang, Z., Chai, X., Si, G. & Zhang, X. (2024). Quantifying Variability in Zebrafish Larvae Locomotor Behavior across Experimental Conditions: A Learning-Based Tracker. Fishes, 9(6), Artikel 193. https://doi.org/10.3390/fishes9060193

Zhang, Z., Sun, T., Wang, Z. & Zhang, X. (2024). Trajectory Planning and Performance Atlases of a New Omnidirectional Conveyor. Actuators, 13(11), Artikel 441. https://doi.org/10.3390/act13110441

Yang, X., Qiang, D., Chen, Z., Wang, H., Zhou, Z. & Zhang, X. (2022). Dynamic Modeling and Digital Twin of a Harmonic Drive Based Collaborative Robot Joint. I 2022 IEEE International Conference on Robotics and Automation, ICRA 2022 (s. 4862-4868). IEEE. https://doi.org/10.1109/ICRA46639.2022.9812458

Yang, X., Zhou, Z., Sørensen, J. H., Christensen, C. B., Ünalan, M. & Zhang, X. (2023). Automation of SME production with a Cobot system powered by learning-based vision. Robotics and Computer-Integrated Manufacturing, 83, Artikel 102564. https://doi.org/10.1016/j.rcim.2023.102564

Yang, X., Zhou, Z., Li, L. & Zhang, X. (2023). Collaborative robot dynamics with physical human–robot interaction and parameter identification with PINN. Mechanism and Machine Theory, 189, Artikel 105439. https://doi.org/10.1016/j.mechmachtheory.2023.105439

Yang, X., Du, Y., Li, L., Zhou, Z. & Zhang, X. (2023). Physics-Informed Neural Network for Model Prediction and Dynamics Parameter Identification of Collaborative Robot Joints. IEEE Robotics and Automation Letters, 8(12), 8462-8469. https://doi.org/10.1109/LRA.2023.3329620

Yang, X. (2024). Towards Physical Interaction Control of Collaborative Industrial Robots Augmented with Scientific Machine Learning for SME Productions. Aarhus University.

Yamaguchi, Y., Langthjem, M. A. & Kosawada, T. (2020). Study on the Self-excited Vibration in Cylindrical Plunge Grinding Process. I Proceedings of the 15th International Conference on Motion and Vibration (MoViC 2020) Japan Society of Mechanical Engineers. https://doi.org/10.1299/jsmeintmovic.2020.15.10021

Wieber, C., Jeppesen, M. R., Finster, K., Melvad, C. & Santl-Temkiv, T. (2024). Micro-PINGUIN: microtiter-plate-based instrument for ice nucleation detection in gallium with an infrared camera. Atmospheric Measurement Techniques, 17(9), 2707–2719. https://doi.org/10.5194/amt-17-2707-2024

Wang, H. & Zhang, X. (2021). Modal Dynamic Modelling and Experimental Validation of a Curved Extensible Continuum Manipulator. 1958-1965. Afhandling præsenteret på 2021 IEEE International Conference on Robotics and Automation (ICRA). https://doi.org/10.1109/ICRA48506.2021.9561914

Wang, H., Zhou, Z., Yang, X. & Zhang, X. (2022). A Switchable Rigid-Continuum Robot Arm: Design and Testing. I 2022 IEEE International Conference on Robotics and Automation, ICRA 2022 (s. 5162-5169). IEEE. https://doi.org/10.1109/ICRA46639.2022.9812074

Ulriksen, M. D., Tcherniak, D., Kirkegaard, P. H. & Damkilde, L. (2016). Operational Modal Analysis and Wavelet Transformation for Damage Identification in Wind Turbine Blades. Structural Health Monitoring, 15(4), 381-388. https://doi.org/10.1177/1475921715586623

Ulriksen, M. D., Jepsen, M. & Bernal, D. (2023). Closed-loop load vectors for structural damage localization. Mechanical Systems and Signal Processing, 196, Artikel 110321. https://doi.org/10.1016/j.ymssp.2023.110321

Ulriksen, M. D. & Bernal, D. (2024). Localization of earthquake-induced structural damage using output feedback eigenstructure assignment. I 18th World Conference on Earthquake Engineering (WCEE2024)

Ulriksen, M. D., Greś, S. & Bernal, D. (2024). Perturbation-invariant eigenvalue assignment for statistical damage localization. Journal of Physics: Conference Series, 2647, Artikel 192017. https://doi.org/10.1088/1742-6596/2647/19/192017

Tabassian, R., Rajabi-Abhari, A., Mahato, M., Yoo, H., Yoon, H. Y., Park, J. Y. & Oh, I. K. (2024). Metal-organic framework-based nanofibrous film for two different modes of triboelectric nanogenerators. SmartMat, 5(5), Artikel e1270. https://doi.org/10.1002/smm2.1270

Si, G., Sun, L., Zhang, Z. & Zhang, X. (2021). Theoretical thermal-mechanical modelling and experimental validation of a three-dimensional (3D) electrothermal microgripper with three fingers. Micromachines, 12(12), Artikel 1512. https://doi.org/10.3390/mi12121512

Si, G., Chen, F. & Zhang, X. (2022). Comparison of the Dynamic Performance of Planar 3-DOF Parallel Manipulators. Machines, 10(4), Artikel 233. https://doi.org/10.3390/machines10040233

Si, G., Ding, M., Zhang, Z. & Zhang, X. (2022). Theoretical thermal-mechanical modelling and experimental validation of a novel 3D three-fingered electrothermal microgripper. Precision Engineering, 77, 205-219. https://doi.org/10.1016/j.precisioneng.2022.05.013

Si, G., Zhou, F., Zhang, Z. & Zhang, X. (2022). Tracking Multiple Zebrafish Larvae Using YOLOv5 and DeepSORT. I 2022 8th International Conference on Automation, Robotics and Applications, ICARA 2022 (s. 228-232). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICARA55094.2022.9738556

Si, G., Zhao, Z., Zhang, Z. & Zhang, X. (2024). Design and Experimental Investigation of a Force Sensor for a 3-D Electrothermal Microgripper. IEEE Sensors Journal, 24(3), 2934-2944. https://doi.org/10.1109/JSEN.2023.3336214

Si, G., Zhang, H., Zhang, Z. & Zhang, X. (2024). Enabling intuitive and effective micromanipulation: A wearable exoskeleton-integrated macro-to-micro teleoperation system with a 3D electrothermal microgripper. Robotics and Autonomous Systems, 181, Artikel 104776. https://doi.org/10.1016/j.robot.2024.104776

Rysgaard, S., Bjerge, K., Boone, W., Frandsen, E., Graversen, M., Thomas Høye, T., Jensen, B., Johnen, G., Antoni Jackowicz-Korczynski, M., Taylor Kerby, J., Kortegaard, S., Mastepanov, M., Melvad, C., Schmidt Mikkelsen, P., Mortensen, K., Nørgaard, C., Poulsen, E., Riis, T., Sørensen, L. & Røjle Christensen, T. (2022). A mobile observatory powered by sun and wind for near real time measurements of atmospheric, glacial, terrestrial, limnic and coastal oceanic conditions in remote off-grid areas. HardwareX, 12, Artikel e00331. https://doi.org/10.1016/j.ohx.2022.e00331

Rajabi-Abhari, A., Yoo, H., Kim, J.-S., Yoon, H. Y., Park, J. Y., Yan, N., Tabassian, R. & Oh, I.-K. (2024). Reversibly Compressible Silanated Cellulose Nanofibril Aerogel for Triboelectric Taekwondo Scoring Sensors. Small, 20(50), Artikel 2405664. https://doi.org/10.1002/smll.202405664

Qian, F., Ding, H., Liu, T., Wu, Z., Zhang, X. & Iqbal, A. (2025). An adaptive active vibration control for flexible beam systems under unknown deterministic disturbances. Mechanical Systems and Signal Processing, 228, Artikel 112447. https://doi.org/10.1016/j.ymssp.2025.112447

Poulsen, E., Eggertsen, M., Jepsen, E. H., Melvad, C. & Rysgaard, S. (2022). Lightweight drone-deployed autonomous ocean profiler for repeated measurements in hazardous areas – Example from glacier fronts in NE Greenland. HardwareX, 11, Artikel e00313. https://doi.org/10.1016/j.ohx.2022.e00313

Pedersen, S. S., B. Madsen, N., Escalona, J. & Balling, O. (2021). Multibody Models for Tower Vibrations With an Unbalanced Rotor. I 17th International Conference on Multibody Systems, Nonlinear Dynamics, and Control (MSNDC) (Bind 9). Artikel V009T09A017 American Society of Mechanical Engineers (ASME). https://doi.org/10.1115/DETC2021-72182

Nguyen, V. H., Oh, S., Mahato, M., Tabassian, R., Yoo, H., Lee, S. G., Garai, M., Kim, K. J. & Oh, I. K. (2024). Functionally antagonistic polyelectrolyte for electro-ionic soft actuator. Nature Communications, 15(1), Artikel 435. https://doi.org/10.1038/s41467-024-44719-z

Mula, B. B., Escalona, J., Lambert, R., Ling, R. & Balling, O. (2023). On the definition and effect of optimum gear microgeometry modifications for the gearbox of an offshore 10-MW wind turbine. Wind Energy, 26(7), 717-740. https://doi.org/10.1002/we.2825

Matsuura, K., Mukai, K. & Langthjem, M. A. (2023). Computational and Experimental Study on the Mechanism of Ring Tone. International Journal of Computational Methods and Experimental Measurements, 11(1), 9-16. https://doi.org/10.18280/ijcmem.110102

Mahato, M., Hwang, W. J., Tabassian, R., Oh, S., Nguyen, V. H., Nam, S., Kim, J. S., Yoo, H., Taseer, A. K., Lee, M. J., Zhang, H., Song, T. E. & Oh, I. K. (2022). A Dual-Responsive Magnetoactive and Electro–Ionic Soft Actuator Derived from a Nickel-Based Metal–Organic Framework. Advanced Materials, 34(35), Artikel 2203613. https://doi.org/10.1002/adma.202203613

Mahato, M., Garai, M., Nguyen, V. H., Oh, S., Nam, S., Zeng, X., Yoo, H., Tabassian, R. & Oh, I. K. (2023). Polysulfonated covalent organic framework as active electrode host for mobile cation guests in electrochemical soft actuator. Science Advances, 9(50), Artikel eadk9752. https://doi.org/10.1126/sciadv.adk9752

Ma, P., Xia, R., Wang, X., Zhang, X., Królczyk, G., Gardoni, P. & Li, Z. (2022). An active control method for vibration reduction of a single-link flexible manipulator. Journal of Low Frequency Noise Vibration and Active Control, 41(4), 1497-1506. https://doi.org/10.1177/14613484221094982

Lu, H., Rui, X. & Zhang, X. (2023). Transfer matrix method for linear vibration analysis of flexible multibody systems. Journal of Sound and Vibration, 549, Artikel 117565. https://doi.org/10.1016/j.jsv.2023.117565

L. Jensen, C. S., B. E. Pedersen, R., Mula, B. B., Escalona, J. & Balling, O. (2022). On the Combination of Geometrically Nonlinear Models and Substructuring for Multibody Simulation of Wind Turbine Blades. I 18th International Conference on Multibody Systems, Nonlinear Dynamics, and Control (MSNDC) Artikel DETC2022-90948, V009T09A011 American Society of Mechanical Engineers (ASME). https://doi.org/10.1115/DETC2022-90948

Li, L., Yang, X., Wang, R. & Zhang, X. (2024). Automatic Robot Hand-Eye Calibration Enabled by Learning-Based 3D Vision. Journal of Intelligent and Robotic Systems: Theory and Applications, 110(3), Artikel 130. https://doi.org/10.1007/s10846-024-02166-4

Li, L. & Zhang, X. (2025). A robust assessment method of point cloud quality for enhancing 3D robotic scanning. Robotics and Computer-Integrated Manufacturing, 92, Artikel 102863. https://doi.org/10.1016/j.rcim.2024.102863

Langthjem, M. A. (2022). On the stability of a doubly infinite vortex array. Theoretical and Computational Fluid Dynamics, 36(3), 369-385. https://doi.org/10.1007/s00162-022-00604-3

Langthjem, M. A. & Jensen, H. M. (2022). Propagating buckles in undersea pipelines – A model problem. International Journal of Solids and Structures, 257, Artikel 111555. https://doi.org/10.1016/j.ijsolstr.2022.111555

Langthjem, M. A., Imura, M. & Yamaguchi, K. (2023). The unbalanced rotating cylinder partially filled with fluid; multiple scales analysis of a forced Korteweg–de Vries–Burgers equation. Journal of Engineering Mathematics, 140, Artikel 1. https://doi.org/10.1007/s10665-023-10259-6, https://doi.org/10.1007/s10665-023-10259-6

Jensen, A. M. D., Schoerghofer-Queiroz, A., Ulriksen, M. D., Tcherniak, D., Damkilde, L., Talasila, P., Larsen, P. G. & Abbiati, G. (2024). Digital twin as a service for damage prognosis of offshore wind turbine foundations. I W. Desmet, B. Pluymers, D. Moens & J. del Fresno Zarza (red.), Proceedings of ISMA 2024 - International Conference on Noise and Vibration Engineering and USD 2024 - International Conference on Uncertainty in Structural Dynamics (s. 4127-4141). KU Leuven, Departement Werktuigkunde.

Hudert, M. M., Elvebakken, M. F., Meagher, M., Mangliar, L., Zhang, X. & Esterle, L. (2022). Deep learning enhanced robotic fabrication of timber-to-timber connections with densified hardwood nails. I Proceedings of the IASS 2022 Symposium affiliated with APCS 2022 conference: Innovation - Sustainability - Legacy (s. 1740-1748)

Høye, T. T., Dyrmann, M., Kjær, C., Nielsen, J., Bruus, M., Mielec, C. L., Vesterdal, M. S., Bjerge, K., Madsen, S. A., Jeppesen, M. R. & Melvad, C. (2022). Accurate image-based identification of macroinvertebrate specimens using deep learning — How much training data is needed? PeerJ, 10, Artikel e13837. https://doi.org/10.7717/peerj.13837

Helal, I. B. I., Du, Y., Wang, H. & Zhang, X. (2024). Dynamic Modelling of a Continuum Robot Arm with Five 3-DoF Segments. I X. Rui & C. Liu (red.), Proceedings of the 2nd International Conference on Mechanical Systems (s. 477-493). Springer. https://doi.org/10.1007/978-981-99-8048-2_30

Viser resultater 1 til 50 ud af 65

Næste

Back to the main page

Revideret 19.12.2023

AU Engineering