Institut für Robotik und intelligente Produktionssysteme

C. Schempp, Y. Zhang, C. Friedrich, B. Hein, QBIT: Quality-Aware Cloud-Based Benchmarking for Robotic Insertion Tasks, arXiv preprint arXiv:2503.07479, “IEEE/RSJ International Conference on Intelligent Robots and Systems, 2025.

C. Friedrich, P. Frank, M. Santin, und M. Haag, „Highly dynamic physical interaction for robotics: design and control of an active remote center of compliance,” arXiv preprint arXiv:2503.07479, IEEE International Conference on Robotics and Automation, S. 1-8., 2025.

C. Hake, C. Friedrich, Automated Generation of Precedence Graphs in Digital Value Chains for Automotive Production, arXiv preprint arXiv:2409.10024, IEEE International Conference on Emerging Technologies and Factory Automation, S. 1-8, 2025.

E. Hirsch, C. Friedrich, Data-driven tool wear prediction in milling, based on a process-integrated single-sensor approach, arXiv preprint arXiv:2412.19950, 2025.

C. Schempp, C. Friedrich, „PIPE: Process Informed Parameter Estimation, a learning based approach to task generalized system identification,” arXiv preprint arXiv:2405.06991, IEEE International Conference on Automation Science and Engineering, 2024.

C. Hake, J. Weigele, B. Krauss, C. Friedrich, F. Reichert, „Evaluation of Artificial Intelligence Methods for Lead Time Prediction in Non-Cyclical Areas of Automotive Production,” Logistics & Supply Chain Management, 2024.

C. Schempp, C. Friedrich, „Robot Agnostic Visual Servoing considering kinematic constraints enabled by a decoupled network trajectory planner structure,” arXiv preprint arXiv:2405.07017, IEEE International Conference on Mechatronics and Machine Vision in Practice, 2024.

M. Friedmann, D. Klüpfel, C. Frech, M. Liu, J. Hauf, G. Li, C. Friedrich, J. Fleischer, „Automated Configuration of Gripper Fingers from a Construction Kit for Robotic Applications,” Machines, 11(8), 804, 2023.

C. Friedrich, R. Gulde, A. Lechler und A. Verl, „Maintenance automation: Concepts for manipulation planning, control and execution,“ IEEE Transactions on Automation Science and Engineering, 20(2) S. 1081-1091, 2022.

L. Berscheid, C. Friedrich, und T. Kröger, „Robot Learning of 6 DoF Grasping using Model-based Adaptive Primitives,” IEEE International Conference Robotics and Automation, Xi’an, China, 2021, S. 4474-4480.