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Andreas Völz

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2020 – today

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2024
[j9]
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Maximilian Pierer von Esch, Andreas Völz, Knut Graichen:
Sensitivity-based distributed model predictive control: synchronous and asynchronous execution compared to ADMM. Autom. 72(2): 91-106 (2024)
[j8]
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Julian Dahlmann, Andreas Völz, Knut Graichen:
Ein Konzept zum automatisierten Rangieren von Fahrzeugen mit Anhängern. Autom. 72(4): 354-368 (2024)
[j7]
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Maximilian Pierer von Esch, Daniel Landgraf, Matthias Steffel, Andreas Völz, Knut Graichen:
Distributed Stochastic Optimal Control of Nonlinear Systems Based on ADMM. IEEE Control. Syst. Lett. 8: 424-429 (2024)
[j6]
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Julian Dahlmann, Andreas Völz, Markus Lukassek, Knut Graichen:
Local Predictive Optimization of Globally Planned Motions for Truck-Trailer Systems. IEEE Trans. Control. Syst. Technol. 32(5): 1555-1568 (2024)
[c22]
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Tim Göller, Andreas Völz, Knut Graichen:
A Programming by Demonstration Approach for Robotic Manipulation with Model Predictive Interaction Control. CCTA 2024: 799-804
[c21]
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Tim Göller, Daniel Brohm, Andreas Völz, Knut Graichen:
DMP-Based Path Planning for Model Predictive Interaction Control. ECC 2024: 128-133
[i3]
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Lars Ullrich, Andreas Völz, Knut Graichen:
Robust Meta-Learning of Vehicle Yaw Rate Dynamics via Conditional Neural Processes. CoRR abs/2407.06605 (2024)
[i2]
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  - journals/corr/abs-2407-09261
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Daniel Landgraf, Andreas Völz, Knut Graichen:
A software framework for stochastic model predictive control of nonlinear continuous-time systems (GRAMPC-S). CoRR abs/2407.09261 (2024)
2023
[j5]
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  - journals/arc/LandgrafVBSSG23
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Daniel Landgraf, Andreas Völz, Felix Berkel, Kevin Schmidt, Thomas Specker, Knut Graichen:
Probabilistic prediction methods for nonlinear systems with application to stochastic model predictive control. Annu. Rev. Control. 56: 100905 (2023)
[j4]
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Tobias Gold, Andreas Völz, Knut Graichen:
Model Predictive Interaction Control for Robotic Manipulation Tasks. IEEE Trans. Robotics 39(1): 76-89 (2023)
[c20]
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  - conf/cdc/UllrichVG23
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Lars Ullrich, Andreas Völz, Knut Graichen:
Robust Meta-Learning of Vehicle Yaw Rate Dynamics via Conditional Neural Processes. CDC 2023: 322-327
[c19]
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  - conf/iros/DioVG23
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Maximilian Dio, Andreas Völz, Knut Graichen:
Cooperative Dual-Arm Control for Heavy Object Manipulation Based on Hierarchical Quadratic Programming. IROS 2023: 643-648
[c18]
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Arash Jalilian, Norman Schwarz, Andreas Völz, Robert Ritschel:
Cascaded Disturbance Compensation for MPC-based Autonomous Vehicle Guidance. MED 2023: 932-937
2022
[c17]
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Tobias Gold, Ralf Römer, Andreas Völz, Knut Graichen:
Catching Objects with a Robot Arm using Model Predictive Control. ACC 2022: 1915-1920
[c16]
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Julian Dahlmann, Andreas Völz, Tomas Szabo, Knut Graichen:
A Numerical Approach for Solving the Inversion Problem for n-Trailer Systems. ACC 2022: 2018-2024
[c15]
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Daniel Landgraf, Andreas Völz, Knut Graichen:
Nonlinear Model Predictive Control with Latent Force Models. ACC 2022: 4979-4984
[c14]
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Julian Dahlmann, Andreas Völz, Tomas Szabo, Knut Graichen:
Trajectory Optimization for Truck-Trailer Systems Based on Predictive Path-Following Control. CCTA 2022: 37-42
[c13]
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Daniel Burk, Andreas Völz, Knut Graichen:
Improving the Performance of Distributed Model Predictive Control by Applying Graph Partitioning Methods. ICSTCC 2022: 104-110
2021
[c12]
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  - conf/cdc/VolzG21
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Andreas Völz, Knut Graichen:
Gradient-based nonlinear model predictive control for systems with state-dependent mass matrix. CDC 2021: 1012-1017
[c11]
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Tobias Gold, Martin Rohrmüller, Andreas Völz, Knut Graichen:
Model Predictive Interaction Control for Force Closure Grasping. CDC 2021: 1018-1023
[c10]
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  - conf/eucc/LukassekVSG21
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Markus Lukassek, Andreas Völz, Tomas Szabo, Knut Graichen:
Model Predictive Path-Following Control for General n-Trailer Systems with an Arbitrary Guidance Point. ECC 2021: 1335-1340
[c9]
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  - conf/eucc/BurkVG21
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Daniel Burk, Andreas Völz, Knut Graichen:
Towards Asynchronous ADMM for Distributed Model Predictive Control of Nonlinear Systems. ECC 2021: 1957-1962
2020
[j3]
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  - journals/at/VolzG20
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Andreas Völz, Knut Graichen:
Prädiktive Pfadfolgeregelung für die kollisionsfreie Bewegungsplanung von Robotern. Autom. 68(7): 557-570 (2020)
[c8]
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Daniel Burk, Andreas Völz, Knut Graichen:
Distributed Optimization with ALADIN for Non-convex Optimal Control Problems. CDC 2020: 4387-4392
[c7]
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Daniel Burk, Andreas Völz, Knut Graichen:
Neighbor Approximations for Distributed Optimal Control of Nonlinear Networked Systems. ECC 2020: 1238-1243
[c6]
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Tobias Gold, Andreas Völz, Knut Graichen:
Model Predictive Position and Force Trajectory Tracking Control for Robot-Environment Interaction. IROS 2020: 7397-7402
[c5]
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  - conf/med/LukassekVSG20
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Markus Lukassek, Andreas Völz, Tomas Szabo, Knut Graichen:
Model Predictive Control for Agricultural Machines with Implements. MED 2020: 387-392
[i1]
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  - journals/corr/abs-2010-12315
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Daniel Burk, Andreas Völz, Knut Graichen:
A Modular Framework for Distributed Model Predictive Control of Nonlinear Continuous-Time Systems (GRAMPC-D). CoRR abs/2010.12315 (2020)

2010 – 2019

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2019
[j2]
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  - journals/ral/VolzG19
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Andreas Völz, Knut Graichen:
A Predictive Path-Following Controller for Continuous Replanning With Dynamic Roadmaps. IEEE Robotics Autom. Lett. 4(4): 3963-3970 (2019)
[c4]
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Daniel Burk, Andreas Völz, Knut Graichen:
Towards a Modular Framework for Distributed Model Predictive Control of Nonlinear Neighbor-Affine Systems. CDC 2019: 5279-5284
2018
[c3]
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  - conf/iros/VolzG18
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Andreas Völz, Knut Graichen:
An Optimization-Based Approach to Dual-Arm Motion Planning with Closed Kinematics. IROS 2018: 8346-8351
2017
[c2]
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  - conf/aimech/VolzG17
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Andreas Völz, Knut Graichen:
Composition of dynamic roadmaps for dual-arm motion planning. AIM 2017: 1242-1248
2016
[j1]
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Andreas Völz, Knut Graichen:
Gradientenbasierte stochastische modellprädiktive Regelung unter Verwendung der Unscented-Transformation. Autom. 64(8): 658-670 (2016)
2015
[c1]
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  - conf/eucc/VolzG15
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Andreas Völz, Knut Graichen:
Stochastic model predictive control of nonlinear continuous-time systems using the unscented transformation. ECC 2015: 3365-3370

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