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20192026
most citedLearning-based Nonlinear Model Predictive Control of Articulated Soft Robots using Recurrent Neural Networks

16 citations · 44 across the 16 of their papers we have counts for

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9 papers · 1 filter

eess.SY2026

Time-Series Anomaly Detection for Mobile Robots in Automotive Active Safety Testing using an RNN-VAE

Henrik Meyer, Karsten Raguse, Armando Walter Colombo +2

Mobile robots, like the ultra-flat overrunable (UFO) robot platform, used in automotive active safety tests, currently lack self-diagnostic capabilities necessary to detect present…

eess.SY2026

Neural Network-Based Virtual Wheel-Speed Sensor for Enhanced Low-Velocity State Estimation

Hendrik Schäfke, Daniel O. M. Weber, Askar Vagapov +3

Accurate wheel speed information is crucial for vehicle control and state estimation. Conventional sensors suffer from quantization and latency, especially at low velocities, while…

eess.SY2026

Simultaneous State Estimation and Online Model Learning in a Soft Robotic System

Jan-Hendrik Ewering, Max Bartholdt, Simon F. G. Ehlers +3

Operating complex real-world systems, such as soft robots, can benefit from precise predictive control schemes that require accurate state and model knowledge. This knowledge is ty…

eess.SY2025

Dual Iterative Learning Control for Multiple-Input Multiple-Output Dynamics with Validation in Robotic Systems

Jan-Hendrik Ewering, Alessandro Papa, Simon F. G. Ehlers +2

Solving motion tasks autonomously and accurately is a core ability for intelligent real-world systems. To achieve genuine autonomy across multiple systems and tasks, key challenges…

eess.SY2024★ 2 cited

Predictive Energy Management for Recuperation Axles in Refrigerated Trailers

Dennis Bank, Simon F. G. Ehlers, Karl-Philipp Kortmann +3

Refrigerated truck trailers are currently mainly operated with environmentally harmful diesel units; an alternative is to operate the refrigeration unit with electrical energy. How…

eess.SY2024

Efficient Online Inference and Learning in Partially Known Nonlinear State-Space Models by Learning Expressive Degrees of Freedom Offline

Jan-Hendrik Ewering, Björn Volkmann, Simon F. G. Ehlers +2

Intelligent real-world systems critically depend on expressive information about their system state and changing operation conditions, e.g., due to variation in temperature, locati…

eess.SY2024★ 1 cited

Nonlinear Two-Track Model of a Semitrailer with Experimental Validation of Lateral and Vertical Tire Forces

Simon F. G. Ehlers, Zygimantas Ziaukas, Jan-Philipp Kobler +3

As part of the automation of commercial vehicles, the number of assistance systems in this field is continuously increasing. The semitrailer plays an important role for the vehicle…

eess.SY2024★ 6 cited

Reliable State Estimation in a Truck-Semitrailer Combination using an Artificial Neural Network-Aided Extended Kalman Filter

Jan-Hendrik Ewering, Zygimantas Ziaukas, Simon F. G. Ehlers +1

Advanced driver assistance systems are critically dependent on reliable and accurate information regarding a vehicles' driving state. For estimation of unknown quantities, model-ba…

eess.SY2023★ 7 cited

Integrated Model Predictive Control of High-Speed Railway Running Gears with Driven Independently Rotating Wheels

Jan-Hendrik Ewering, Christoph Schwarz, Simon F. G. Ehlers +3

Railway running gears with independently rotating wheels (IRW) can significantly improve wear figures, comfort, and safety in railway transportation, but certain measures for wheel…