16 citations · 44 across the 16 of their papers we have counts for
16 papers
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…
Hybrid Machine Learning for Articulation Angle Estimation of Truck-Semitrailer Combinations
Qixuan Zhang, Jonas Boettcher, Simon F. G. Ehlers +1
Accurate articulation angle estimation of trucks with trailers is critical for autonomous driving and advanced driver assistance system (ADAS). Existing methods either require manu…
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…
A Hybrid Autoencoder for Robust Heightmap Generation from Fused Lidar and Depth Data for Humanoid Robot Locomotion
Dennis Bank, Joost Cordes, Thomas Seel +1
Reliable terrain perception is a critical prerequisite for the deployment of humanoid robots in unstructured, human-centric environments. While traditional systems often rely on ma…
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…
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…
Bayesian Inference and Learning in Nonlinear Dynamical Systems: A Framework for Incorporating Explicit and Implicit Prior Knowledge
Björn Volkmann, Jan-Hendrik Ewering, Michael Meindl +2
Accuracy and generalization capabilities are key objectives when learning dynamical system models. To obtain such models from limited data, current works exploit prior knowledge an…
Generalizable and Fast Surrogates: Model Predictive Control of Articulated Soft Robots using Physics-Informed Neural Networks
Tim-Lukas Habich, Aran Mohammad, Simon F. G. Ehlers +3
Soft robots can revolutionize several applications with high demands on dexterity and safety. When operating these systems, real-time estimation and control require fast and accura…
Learning-based Nonlinear Model Predictive Control of Articulated Soft Robots using Recurrent Neural Networks
Hendrik Schäfke, Tim-Lukas Habich, Christian Muhmann +3
Soft robots pose difficulties in terms of control, requiring novel strategies to effectively manipulate their compliant structures. Model-based approaches face challenges due to th…
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…
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…
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…
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…
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…
Traffic Queue Length and Pressure Estimation for Road Networks with Geometric Deep Learning Algorithms
Simon F. G. Ehlers
Due to urbanization and the increase of individual mobility, in most metropolitan areas around the world congestion and inefficient traffic management occur. Highly necessary intel…
Neural-Attention-Based Deep Learning Architectures for Modeling Traffic Dynamics on Lane Graphs
Matthew A. Wright, Simon F. G. Ehlers, Roberto Horowitz
Deep neural networks can be powerful tools, but require careful application-specific design to ensure that the most informative relationships in the data are learnable. In this pap…