7 citations · 7 across the 5 of their papers we have counts for
6 papers
ExoLaN: Physics-Consistent Context-Aware Dynamics Learning for Exoskeletons
Lucas Schulze, Maximilian Schwarz, Jona Hoppe +2
Task-agnostic assistive exoskeleton control based on human intention offers greater flexibility than conventional approaches that rely on predefined tasks or motion patterns. Human…
Embedding Physics Priors in Robot Learning: A Survey
Mattia Piccinini, Lucas Schulze, Alice Plebe +10
The rapid progress of artificial intelligence is reshaping robotics and accelerating the adoption of learning-based approaches. While purely data-driven methods have achieved remar…
Mathematical Foundations of Modeling ETL Process Chains
Levin Maier, Lucas Schulze, Robert Lilow +10
Extract-Transform-Load (ETL) processes are core components of modern data processing infrastructures. The throughput of processed data records can be adjusted by changing the amoun…
Floating-Base Deep Lagrangian Networks
Lucas Schulze, Juliano Decico Negri, Victor Barasuol +4
Grey-box methods for system identification combine deep learning with physics-informed constraints, capturing complex dependencies while improving out-of-distribution generalizatio…
Context-Aware Deep Lagrangian Networks for Model Predictive Control
Lucas Schulze, Jan Peters, Oleg Arenz
Controlling a robot based on physics-consistent dynamic models, such as Deep Lagrangian Networks (DeLaN), can improve the generalizability and interpretability of the resulting beh…
PACC: A Passive-Arm Approach for High-Payload Collaborative Carrying with Quadruped Robots Using Model Predictive Control
Giulio Turrisi, Lucas Schulze, Vivian S. Medeiros +2
In this paper, we introduce the concept of using passive arm structures with intrinsic impedance for robot-robot and human-robot collaborative carrying with quadruped robots. The c…