6 papers
Reducing the Communication of Distributed Model Predictive Control: Autoencoders and Formation Control
Torben Schiz, Henrik Ebel
Communication remains a key factor limiting the applicability of distributed model predictive control (DMPC) in realistic settings, despite advances in wireless communication. DMPC…
Discovering Antagonists in Networks of Systems: Robot Deployment
Ingeborg Wenger, Peter Eberhard, Henrik Ebel
A contextual anomaly detection method is proposed and applied to the physical motions of a robot swarm executing a coverage task. Using simulations of a swarm's normal behavior, a…
An Online Optimization-Based Trajectory Planning Approach for Cooperative Landing Tasks
Jingshan Chen, Lihan Xu, Henrik Ebel +1
This paper presents a real-time trajectory planning scheme for a heterogeneous multi-robot system (consisting of a quadrotor and a ground mobile robot) for a cooperative landing ta…
Efficient Avoidance of Ellipsoidal Obstacles with Model Predictive Control for Mobile Robots and Vehicles
Mario Rosenfelder, Hendrik Carius, Markus Herrmann-Wicklmayr +3
In real-world applications of mobile robots, collision avoidance is of critical importance. Typically, global motion planning in constrained environments is addressed through high-…
Data-Driven Predictive Control of Nonholonomic Robots Based on a Bilinear Koopman Realization: Data Does Not Replace Geometry
Mario Rosenfelder, Lea Bold, Hannes Eschmann +3
Advances in machine learning and the growing trend towards effortless data generation in real-world systems has led to an increasing interest for data-inferred models and data-base…
Data Publishing in Mechanics and Dynamics: Challenges, Guidelines, and Examples from Engineering Design
Henrik Ebel, Jan van Delden, Timo Lüddecke +15
Data-based methods have gained increasing importance in engineering, especially but not only driven by successes with deep artificial neural networks. Success stories are prevalent…