Forschungsthemen

Robot Grasping for Bin Picking

Sim-To-Real Transfer Learning

Active Learning

Projekte

FLAIROP

Werdegang

Seit 2021	Institut für Fördertechnik und Logistiksysteme (IFL) Wissenschaftlicher Mitarbeiter
2019-2020	Institut für Fördertechnik und Logistiksysteme (IFL) Studentische Hilfskraft
2018-2020	Karlsruher Institut für Technologie (KIT) Studium Maschinenbau (M.Sc.)
2013-2018	Karlsruher Institut für Technologie (KIT) Studium Maschinenbau (B.Sc.)

Vorlesungen

Abschlussarbeiten

Aktuelle Ausschreibungen für Abschlussarbeiten finden sich hier.
Interesse an meinen Forschungsthemen, aber es ist gerade kein Thema ausgeschrieben? Schreibe mir eine kurze Mail, denn es gibt eigentlich immer Themen zu bearbeiten.

Veröffentlichungen

vMF-Contact: Uncertainty-aware Evidential Learning for Probabilistic Contact-grasp in Noisy Clutter
Shi, Y.; Welte, E.; Gilles, M.; Rayyes, R.
2024. arxiv. doi:10.48550/arXiv.2411.03591

MetaMVUC: Active Learning for Sample-Efficient Sim-to-Real Domain Adaptation in Robotic Grasping
Gilles, M.; Furmans, K.; Rayyes, R.
2025. IEEE Robotics and Automation Letters, 10 (4), 3644–3651. doi:10.1109/LRA.2025.3544083

Momentary Depression Severity Prediction in Patients With Acute Depression Who Undergo Sleep Deprivation Therapy: Speech-Based Machine Learning Approach
Hartnagel, L.-M.; Emden, D.; Foo, J. C.; Streit, F.; Witt, S. H.; Frank, J.; Limberger, M. F.; Schmitz, S. E.; Gilles, M.; Rietschel, M.; Hahn, T.; Ebner-Priemer, U. W.; Sirignano, L.
2024. JMIR Mental Health, 11, Art.-Nr.: e64578. doi:10.2196/64578

Linguistic style as a digital marker for depression severity: An ambulatory assessment pilot study in patients with depressive disorder undergoing sleep deprivation therapy
Hartnagel, L.-M.; Ebner-Priemer, U. W.; Foo, J. C.; Streit, F.; Witt, S. H.; Frank, J.; Limberger, M. F.; Horn, A. B.; Gilles, M.; Rietschel, M.; Sirignano, L.
2025. Acta psychiatrica Scandinavica, 151 (3), 348–357. doi:10.1111/acps.13726

Rethinking Resource Competition in Multi-Task Learning: from Shared Parameters to Shared Representation
Mao, D.; Chen, Y.; Wu, Y.; Gilles, M.; Wong, A.
2024. IEEE Access, 12, 128717–128728. doi:10.1109/ACCESS.2024.3429281

MetaGraspNetV2: All-in-One Dataset Enabling Fast and Reliable Robotic Bin Picking via Object Relationship Reasoning and Dexterous Grasping
Gilles, M.; Chen, Y.; Zeng, E. Z.; Wu, Y.; Furmans, K.; Wong, A.; Rayyes, R.
2024. IEEE Transactions on Automation Science and Engineering, 21 (3), 2302–2320. doi:10.1109/TASE.2023.3328964

Continual Learning of Vacuum Grasps from Grasp Outcome for Unsupervised Domain Adaption
Gilles, M.; Rau, V.
2022. 2022 2nd International Conference on Robotics, Automation and Artificial Intelligence (RAAI), 164–171, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/RAAI56146.2022.10092970

Structure SLAM with points, planes and objects
Zhou, B.; Gilles, M.; Meng, Y.
2022. Advanced Robotics, 36 (20), 1060–1075. doi:10.1080/01691864.2022.2123253

MetaGraspNet: A Large-Scale Benchmark Dataset for Scene-Aware Ambidextrous Bin Picking via Physics-based Metaverse Synthesis
Gilles, M.; Chen, Y.; Winter, T. R.; Zhixuan Zeng, E.; Wong, A.
2022. 2022 IEEE 18th International Conference on Automation Science and Engineering (CASE), 220–227, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/CASE49997.2022.9926427

Unsupervised deep learning based ego motion estimation with a downward facing camera
Gilles, M.; Ibrahimpasic, S.
2023. Visual Computer, 39, 785–798. doi:10.1007/s00371-021-02345-6

PiRo : Ein autonomes Kommissioniersystem für inhomogene, chaotische Lager = PiRo : An autonomous picking system for inhomogeneous, chaotic storages
Colling, D.; Dziedzitz, J.; Hopfgarten, P.; Markert, K.; Neubehler, K.; Eberle, F.; Gilles, M.; Jung, M.; Kocabas, A.; Furmans, K.
2017. Logistics journal / Proceedings, 2017. doi:10.2195/lj_Proc_colling_de_201710_01