9 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…
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…
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…
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…