8 citations · 22 across the 10 of their papers we have counts for
10 papers
Learning-Accelerated Optimization-based Trajectory Planning for Cooperative Aerial-Ground Handover Missions
Jingshan Chen, Bochen Yu, Henrik Ebel +1
This paper presents a learning-augmented trajectory planning framework for cooperative unmanned aerial vehicle (UAV) and unmanned ground vehicle (UGV) handover missions. While cent…
Excitation of control-affine systems and Koopman error bounds
Philipp Schmitz, Lea Bold, Friedrich M. Philipp +4
The Koopman operator and extended dynamic mode decomposition (EDMD) as a data-driven technique for its approximation have attracted considerable attention as a key tool for modelin…
Efficient Collision-Avoidance Constraints for Ellipsoidal Obstacles in Optimal Control: Application to Path-Following MPC and UAVs
David Leprich, Mario Rosenfelder, Markus Herrmann-Wicklmayr +3
This article proposes a modular optimal control framework for local three-dimensional ellipsoidal obstacle avoidance, exemplarily applied to model predictive path-following control…
Model Predictive Path-Following Control for a Quadrotor
David Leprich, Mario Rosenfelder, Mario Hermle +2
Automating drone-assisted processes is a complex task. Many solutions rely on trajectory generation and tracking, whereas in contrast, path-following control is a particularly prom…
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…
The impact of AI on engineering design procedures for dynamical systems
Kristin M. de Payrebrune, Kathrin Flaßkamp, Tom Ströhla +19
Artificial intelligence (AI) is driving transformative changes across numerous fields, revolutionizing conventional processes and creating new opportunities for innovation. The dev…
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…