Dr.-Ing. Andreas Völz

Chair of Automatic Control

Research associates

Address

Cauerstraße 7-9 91058 Erlangen

03.037, 03

Contact

Email: andreas.voelz@fau.de
Phone: +49 9131 85-61036

Andreas Völz received the M.Sc. degree in communications and computer engineering and the Ph.D. (Dr.-Ing.) degree from Ulm University, Ulm, Germany, in 2014 and 2019, respectively. Since 2019, he has been with the Chair of Automatic Control, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany. His current research interests include optimization-based motion planning and model predictive control with a focus on robotic applications. He is co-developer of the software toolboxes GRAMPC, GRAMPC-D, and GRAMPC-S for nonlinear, distributed, and stochastic model predictive control.

Biography

since 08/2026	Senior Lecturer, Chair of Automatic Control, Friedrich-Alexander-Universität Erlangen-Nürnberg
09/2021 - 07/2026	Lecturer, Chair of Automatic Control, Friedrich-Alexander-Universität Erlangen-Nürnberg
04/2019 - 08/2021	Postdoc, Chair of Automatic Control, Friedrich-Alexander-Universität Erlangen-Nürnberg
10/2014 - 03/2019	Research assistant, Institute of Measurement, Control and Microtechnology, Ulm University
10/2012 - 09/2014	Master of Science in Communications and Computer Engineering, Ulm University
10/2009 - 09/2012	Bachelor of Science in Communications and Computer Engineering, Ulm University

Supervised student theses

Lernbasierte Gangentwicklung und Sim2Real-Transfer für einen humanoiden Roboter
Detection of Metal Parts for Automated Bin Picking
Nonlinear Model Predictive Control for Tail-sitter Unmanned Aerial Vehicles
Development of Benchmarking Framework for Parametrizable Inverse Kinematics Solver
Bewegungsplanung basierend auf Graphen von konvexen Mengen

Motion Prediction and Collision Avoidance based on Reachability Analysis
Kamerabasierte kinematische Kalibrierung für einen 3D-gedruckten humanoiden Roboter
Modeling and identification of the human cardiovascular system for blood pressure estimation
Identifikation der dynamischen Parameter des Roboters KUKA lbr iiwa 7 R800
MPC-basierte Störgrößenkompensation mit zwei Freiheitsgraden zur automatisierten Fahrzeugführung
Fangen sphärischer Objekte mit einem mobilien Zweiarmroboter
Mobile Robot Navigation through Narrow Passages
Analyzing the Effect of Design Choices in Model-based Reinforcement Learning
Reinforcement Learning using Gaussian Processes and Model Predictive Control
Hierarchical Learning and Model Predictive Control
Prädiktive Pfadfolgeregelung für die kollisionsfreie Bewegungsplanung von redundanten Robotern

Bewegungsplanung für Roboterarme mit hierarchischen Dynamic Roadmaps
Automatisches Differenzieren für die numerische Lösung von Optimierungsproblemen
Bewegungsplanung mit Interior Point-Verfahren für Roboter mit geschlossener Kinematik
Schnelle Rasterung von 3D-Modellen in der Robotik
Echtzeitfähige Implementierung einer stochastischen modellprädiktiven Regelung mit Pfadintegralen
Modellprädiktive Regelung eines Roboterarms unter Einbeziehung menschlicher Wahrnehmungssysteme
Modellprädiktive Nachgiebigkeitsregelung von Roboterarmen
Nichtlineare stochastische modellprädiktive Regelung mit Pfadintegralen
Entwicklung eines prädiktiven Planungsverfahrens für die flexible Produktion
Entwicklung eines Praktikumsversuchs zur Programmierung eines Industrieroboters
Vergleich von optimierungsbasierten Verfahren zur Bewegungsplanung in der Robotik
Bewegungsplanung für einen Zweiarmroboter mit geschlossener Kinematik
Erkennung dynamischer Hindernisse für die Bewegungsplanung eines Roboterarms

Publications

2026

Landgraf, D., Völz, A., & Graichen, K. (2026). Recursive feasibility of nonlinear stochastic model predictive control with Gaussian process dynamics. International Journal of Robust and Nonlinear Control, 36, 4957-4970. https://doi.org/10.1002/rnc.70470
Pierer von Esch, M., Völz, A., & Graichen, K. (2026). An overview of sensitivity-based distributed optimization and model predictive control. At-Automatisierungstechnik, 74(3), 182-196. https://doi.org/10.1515/auto-2025-0105
Pierer von Esch, M., Völz, A., & Graichen, K. (2026). Sensitivity-Based Distributed Programming for Non-Convex Optimization. IEEE Transactions on Control of Network Systems, 13(2), 1205-1217. https://doi.org/10.1109/TCNS.2026.3690575
Völz, A., & Graichen, K. (2026). Towards Simulation-Based Motion Planning for Deformable Linear Objects. In Proceedings of the 23rd IFAC World Congress. Busan (Korea).
Völz, A., Wietzke, T., Pierer von Esch, M., Landgraf, D., & Graichen, K. (2026). Nonlinear, distributed, and stochastic model predictive control with GRAMPC-(D/S). At-Automatisierungstechnik, 74(8), 659-671. https://doi.org/10.1515/auto-2026-0037

2025

Dahlmann, J., Völz, A., & Graichen, K. (2025). Global motion planning for multi-trailer vehicles in partially structured environments. Journal of Intelligent & Robotic Systems, 111(4). https://doi.org/10.1007/s10846-025-02330-4
Dio, M., Wahrburg, A., Enayati, N., Graichen, K., & Völz, A. (2025). Time-Optimal Path Parameterization with Viscous Friction and Jerk Constraints based on Reachability Analysis. In Proceedings 2025 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). Hangzhou, CN.
Goller, T., Hopf, V., Völz, A., & Graichen, K. (2025). Fault Handling in Robotic Manipulation Tasks for Model Predictive Interaction Control. IEEE Robotics and Automation Letters, 10(9), 9002-9009. https://doi.org/10.1109/LRA.2025.3592069
Landgraf, D., Völz, A., & Graichen, K. (2025). A software framework for stochastic model predictive control of nonlinear continuous-time systems (GRAMPC-S). Optimization and Engineering. https://doi.org/10.1007/s11081-025-10006-z
Pierer von Esch, M., Nistler, E., Völz, A., & Graichen, K. (2025). Sensitivity-based distributed NMPC: Experimental results for a levitating planar motion system. IEEE Transactions on Control Systems Technology, 33(3), 1110-1118. https://doi.org/10.1109/TCST.2025.3530165
Pierer von Esch, M., Völz, A., & Graichen, K. (2025). A fixed-point iteration scheme for sensitivity-based distributed optimal control. IEEE Transactions on Automatic Control, 70(4), 2778-2785. https://doi.org/10.1109/TAC.2024.3505753
Pierer von Esch, M., Völz, A., & Graichen, K. (2025). Asynchronous sensitivity-based distributed optimal control for nonlinear systems. In Proceedings 2025 American Control Conference (ACC) (pp. 835-842). Denver, CO (USA).
Pierer von Esch, M., Völz, A., & Graichen, K. (2025). Sensitivity-Based Distributed Model Predictive Control for Nonlinear Systems under Inexact Optimization. Optimal Control Applications & Methods, 46, 1538-1558. https://doi.org/10.1002/oca.3277
Rabenstein, G., Völz, A., & Graichen, K. (2025). Cable Manipulation for Contact Shaping Tasks using Elastic Rods. In Proceedings of the IEEE International Conference on Advanced Robotics and Mechatronics (ICARM). Portsmouth.
Santer, P., Völz, A., & Graichen, K. (2025). A Model Predictive Control Approach to Trajectory Tracking with Human-Robot Collision Avoidance. In Proceedings 9th IEEE Conference on Control Technology and Applications (CCTA). San Diego, US.

2024

Dahlmann, J., Graichen, K., & Völz, A. (2024). Ein Konzept zum automatisierten Rangieren von Fahrzeugen mit Anhängern.
Dahlmann, J., Völz, A., Lukassek, M., & Graichen, K. (2024). Local predictive optimization of globally planned motions for truck-trailer systems. IEEE Transactions on Control Systems Technology, 32(5), 1555-1568. https://doi.org/10.1109/TCST.2023.3345169
Dio, M., Graichen, K., & Völz, A. (2024). Time-Optimal Path Parameterization for Cooperative Multi-Arm Robotic Systems with Third-Order Constraints. In 2024 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (pp. 3043-3048). Abu Dhabi, AE: Institute of Electrical and Electronics Engineers Inc..
Goller, T., Brohm, D., Völz, A., & Graichen, K. (2024). DMP-based path planning for model predictive interaction control. In Proceedings of the European Control Conference (pp. 128-133). Stockholm (Sweden).
Goller, T., Völz, A., & Graichen, K. (2024). A Programming by Demonstration Approach for Robotic Manipulation with Model Predictive Interaction Control. In Proceedings of the 2024 IEEE Conference on Control Technology and Applications (CCTA) (pp. 799-804). Newcastle upon Tyne, United Kingdom.
Lukassek, M., Dahlmann, J., Völz, A., & Graichen, K. (2024). Model predictive path-following control for truck–trailer systems with specific guidance points - Design and experimental validation. Mechatronics, 100, 103190. https://doi.org/10.1016/j.mechatronics.2024.103190
Pierer von Esch, M., Landgraf, D., Steffel, M., Völz, A., & Graichen, K. (2024). Distributed Stochastic Optimal Control of Nonlinear Systems based on ADMM. IEEE Control Systems Letters, 8, 424-429. https://doi.org/10.1109/LCSYS.2024.3393411
Pierer von Esch, M., Völz, A., & Graichen, K. (2024). Asynchronous ADMM for Nonlinear Continuous-Time Systems. Optimal Control Applications & Methods.
Pierer von Esch, M., Völz, A., & Graichen, K. (2024). Sensitivity-Based Distributed Model Predictive Control: Synchronous and Asynchronous Execution Compared to ADMM. At-Automatisierungstechnik, 72(2), 91-106. https://doi.org/10.1515/auto-2023-0050

2023

Dio, M., Völz, A., & Graichen, K. (2023). Cooperative dual-arm control for heavy object manipulation based on hierarchical quadratic programming. In Proceedings of the 2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (pp. 643-648). Detroit, US.
Gold, T., Völz, A., & Graichen, K. (2023). Model predictive interaction control for robotic manipulation tasks. IEEE Transactions on Robotics, 39(1), 76-89. https://doi.org/10.1109/TRO.2022.3196607
Jalilian, A., Schwarz, N., Völz, A., & Ritschel, R. (2023). Cascaded Disturbance Compensation for MPC-based Autonomous Vehicle Guidance. In 2023 31st Mediterranean Conference on Control and Automation, MED 2023 (pp. 932-937). Limassol, CYP: Institute of Electrical and Electronics Engineers Inc..
Landgraf, D., Völz, A., Berkel, F., Schmidt, K., Specker, T., & Graichen, K. (2023). Probabilistic prediction methods for nonlinear systems with application to stochastic model predictive control. Annual Reviews in Control, 56, 100905. https://doi.org/10.1016/j.arcontrol.2023.100905
Ullrich, L., Völz, A., & Graichen, K. (2023). Robust meta-learning of vehicle yaw rate dynamics via conditional neural processes. In Proc. 62nd IEEE Conference on Decision and Control (CDC) (pp. 322-327). Marina Bay Sands (Singapore).

2022

Burk, D., Völz, A., & Graichen, K. (2022). A modular framework for distributed model predictive control of nonlinear continuous-time systems (GRAMPC-D). Optimization and Engineering, 23, 771-795. https://doi.org/10.1007/s11081-021-09605-3
Burk, D., Völz, A., & Graichen, K. (2022). Improving the performance of distributed model predictive control by applying graph partitioning methods. In Proceedings of the 26th International Conference on System Theory, Control and Computing (ICSTCC). Sinaia (Romania).
Dahlmann, J., Völz, A., Szabo, T., & Graichen, K. (2022). A Numerical Approach for Solving the Inversion Problem for n-Trailer Systems. In 2022 American Control Conference (ACC) (pp. 2018-2024). Atlanta, GA, US: Institute of Electrical and Electronics Engineers Inc..
Dahlmann, J., Völz, A., Szabo, T., & Graichen, K. (2022). Trajectory optimization for truck-trailer systems based on predictive path-following control. In Proceedings of the 6th IEEE Conference on Control Technology and Applications (CCTA). Trieste (Italy).
Gold, T., Römer, R., Völz, A., & Graichen, K. (2022). Catching objects with a robot arm using model predictive control. In Proceedings 2022 American Control Conference (ACC) (pp. 1915-1920). Atlanta, GA (USA).
Goller, T., Gold, T., Völz, A., & Graichen, K. (2022). Model predictive interaction control based on a path-following formulation. In Proceedings IEEE International Conference on Mechatronics and Automation (ICMA) (pp. 551-556). Guilin (China).
Landgraf, D., Völz, A., & Graichen, K. (2022). Nonlinear model predictive control with latent force models. In Proceedings 2022 American Control Conference (ACC) (pp. 4979-4984). Atlanta, GA (USA).
Landgraf, D., Völz, A., Kontes, G., Graichen, K., & Mutschler, C. (2022). Hierarchical learning for model predictive collision avoidance. In IFAC PapersOnLine (pp. 355-360). Vienna (Austria).

2021

Burk, D., Völz, A., & Graichen, K. (2021). Experimental validation of the open-source DMPC framework GRAMPC-D applied to the remote-accessible robotarium. In Proceedings of the IEEE International Conference on Mechatronics and Automation (ICMA).
Burk, D., Völz, A., & Graichen, K. (2021). Towards asynchronous ADMM for distributed model predictive control of nonlinear systems. In Proceedings European Control Conference (ECC 2021) (pp. 1950-1955).
Gold, T., Rohrmüller, M., Völz, A., & Graichen, K. (2021). Model predictive interaction control for force closure grasping. In Proceedings of the 2021 IEEE Conference on Decision and Control (CDC) (pp. 1018-1023). Austin, TX, USA.
Lukassek, M., Völz, A., Szabo, T., & Graichen, K. (2021). Model predictive path-following control for general n-trailer systems with an arbitrary guidance point. In Proceedings European Control Conference (ECC 2021) (pp. 1329-1334).
Völz, A., & Graichen, K. (2021). Gradient-based nonlinear model predictive control for systems with state-dependent mass matrix. In Proceedings of the 2021 IEEE Conference on Decision and Control (CDC), accepted.

2020

Burk, D., Völz, A., & Graichen, K. (2020). Distributed optimization with ALADIN for non-convex optimal control problems. In 59th IEEE Conference on Decision and Control (CDC 2020).
Burk, D., Völz, A., & Graichen, K. (2020). Neighbor approximations for distributed optimal control of nonlinear networked systems. In Proceedings of the European Control Conference (ECC 2020) (pp. 1238-1243).
Gold, T., Lomakin, A., Goller, T., Völz, A., & Graichen, K. (2020). Towards a Generic Manipulation Framework for Robots based on Model Predictive Interaction Control. In Proceedings of the IEEE International Conference on Mechatronics and Automation (ICMA) (pp. 401 - 407). Beijing, CN.
Gold, T., Völz, A., & Graichen, K. (2020). Model Predictive Interaction Control for Industrial Robots. In Proceedings of the 21st IFAC World Congress (pp. 10026 - 10033). Berlin, DE.
Gold, T., Völz, A., & Graichen, K. (2020). Model Predictive Position and Force Trajectory Tracking Control for Robot-Environment Interaction. In Proceedings of the 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (pp. 7397-7402). Las Vegas, NV, USA, US.
Lukassek, M., Völz, A., Szabo, T., & Graichen, K. (2020). Model predictive control for agricultural machines with implements. In Proceedings 28th Mediterranean Conference on Control and Automation (MED) (pp. 387-392).
Völz, A., & Graichen, K. (2020). Prädiktive Pfadfolgeregelung für die kollisionsfreie Bewegungsplanung von Robotern. At-Automatisierungstechnik, 68(7), 557-570. https://doi.org/10.1515/auto-2020-0048

2019

Burk, D., Völz, A., & Graichen, K. (2019). Towards a modular framework for distributed model predictive control of nonlinear neighbor-affine systems. In 58th IEEE Conference on Decision and Control (CDC 2019) (pp. 5279-5284). Nice (France).
Englert, T., Völz, A., Mesmer, F., Rhein, S., & Graichen, K. (2019). A software framework for embedded nonlinear model predictive control using a gradient-based augmented Lagrangian approach (GRAMPC). Optimization and Engineering, 20(3), 769-809. https://doi.org/10.1007/s11081-018-9417-2
Gold, T., Völz, A., & Graichen, K. (2019). External torque estimation for an industrial robot arm using joint torsion and motor current measurements. In Joint Conference 8th IFAC Symposium on Mechatronic Systems (MECHATRONICS) and 11th IFAC Symposium on Nonlinear Control Systems (NOLCOS) (pp. 879-884). Vienna (Austria).
Völz, A., & Graichen, K. (2019). A predictive path-following controller for continuous replanning with dynamic roadmaps. IEEE Robotics and Automation Letters, 4(4), 3963-3970. https://doi.org/10.1109/LRA.2019.2929990

2018

Völz, A., & Graichen, K. (2018). An optimization-based approach to dual-arm motion planning with closed kinematics. In Proceedings 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (pp. 8346-8351). Madrid (Spain).
Völz, A., & Graichen, K. (2018). Computation of collision distance and gradient using an automatic sphere approximation of the robot model with bounded error. In Proceedings 50th International Symposium on Robotics (ISR) (pp. 322-329). München (Germany).

2017

Völz, A., & Graichen, K. (2017). Composition of dynamic roadmaps for dual-Arm motion planning. In 2017 IEEE International Conference on Advanced Intelligent Mechatronics (AIM) (pp. 1242-1248). München, DE: Institute of Electrical and Electronics Engineers Inc..

2016

Völz, A., & Graichen, K. (2016). Distance metrics for path planning with dynamic roadmaps. In Proceedings of ISR 2016: 47st International Symposium on Robotics (pp. 126-132). München, DE: Berlin / Offenbach: VDE Verlag.
Völz, A., & Graichen, K. (2016). Gradient-based stochastic model predictive control using the unscented transformation Gradientenbasierte stochastische modellprädiktive Regelung unter Verwendung der Unscented-Transformation. At-Automatisierungstechnik, 64(8), 658-670. https://doi.org/10.1515/auto-2016-0035
Völz, A., & Graichen, K. (2016). Gradientenbasierte stochastische modellprädiktive Regelung unter Verwendung der Unscented-Transformation. At-Automatisierungstechnik, 64(8), 658-670. https://doi.org/10.1515/auto-2016-0035

2015

Völz, A., & Graichen, K. (2015). Stochastic model predictive control of nonlinear continuous-time systems using the unscented transformation. In 2015 European Control Conference (ECC) (pp. 3365-3370). Linz, AT: Institute of Electrical and Electronics Engineers Inc..
Völz, A., & Graichen, K. (2015). Stochastische modellprädiktive Regelung unsicherer nichtlinearer Systeme basierend auf der Unscented-Transformation. In Proceedings GMA Fachausschuss 1.40 ``Theoretische Verfahren der Regelungstechnik'' (pp. 293-301). Salzburg (Austria).