Mechatronics, Automation, and Control Systems Laboratory
The MACS Lab investigates theories and practice of dynamic systems and controls, to seek better understanding and engineering of the systematic interplay between data, system, and control in machines and automation processes that positively impact our lives.
Research
Control in different time scales: from precision laser-material interaction for aerospace and medical application to process reconfiguration and reclaiming materials.
Robot control and collaborative sensing for systematic fast control under slow e.g. vision feedback.
We were among the 3 teams that achieved the top results in an international benchmark on adaptive regulation.
Objective: to build advisor robots enabling comprehensive part inspections & defect identification of complex metallic components.
Latest Preprints
(2024).
Learning to Detect Slip through Tactile Estimation of the Contact Force Field and its Entropy Properties.
Mechatronics.
(2024).
Agile Surface Inspection Framework for Aerospace Components Using Unsupervised Machine Learning.
Proceedings of ASME/ISCIE International Symposium on Flexible Automation.
(2024).
Effect of Intra-Build Design Parameters on the Fracture Toughness Properties of EBM Ti6Al4V.
Fatigue and Fracture of Engineering Materials and Structures.
(2024).
A Robotic Surface Inspection Framework and Machine-Learning Based Optimal Segmentation For Aerospace and Precision Manufacturing.
Journal of Manufacturing Processes.
(2024).
AIM 2024: Proceedings of 2024 IEEE/ASME International Conference on Advanced Intelligent Mechatronics.
2024 IEEE/ASME International Conference on Advanced Intelligent Mechatronics.
