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2020 – today
- 2024
[j20]Annalena Daniels, Tommaso Benciolini, Dirk Wollherr, Marion Leibold:
Adaptive Multi-Model Fault Diagnosis of Dynamic Systems for Motion Tracking. IEEE Access 12: 197540-197556 (2024)- [j19]Michael Fink
, Dirk Wollherr, Marion Leibold:
Stochastic Model Predictive Control With Minimal Constraint Violation Probability for Time-Variant Chance Constraints. IEEE Control. Syst. Lett. 8: 1385-1390 (2024) - [j18]Michael Fink, Tim Brüdigam, Dirk Wollherr, Marion Leibold:
Minimal Constraint Violation Probability in Model Predictive Control for Linear Systems. IEEE Trans. Autom. Control. 69(10): 7043-7050 (2024) - [j17]Yi Ren, Zhehua Zhou, Ziwei Xu, Yang Yang, Guangyao Zhai, Marion Leibold, Fenglei Ni, Zhengyou Zhang, Martin Buss, Yu Zheng:
Enabling Versatility and Dexterity of the Dual-Arm Manipulators: A General Framework Toward Universal Cooperative Manipulation. IEEE Trans. Robotics 40: 2024-2045 (2024) - [j16]Yongchao Wang, Yang Liu, Marion Leibold, Martin Buss, Jinoh Lee:
Hierarchical Incremental MPC for Redundant Robots: A Robust and Singularity-Free Approach. IEEE Trans. Robotics 40: 2128-2148 (2024) - [c19]Tommaso Benciolini, Yuntian Yan, Dirk Wollherr, Marion Leibold:
Combining Belief Function Theory and Stochastic Model Predictive Control for Multi-Modal Uncertainty in Autonomous Driving. ACC 2024: 5042-5048 - [i23]Johannes Teutsch, Sebastian Kerz, Dirk Wollherr, Marion Leibold:
Sampling-based Stochastic Data-driven Predictive Control under Data Uncertainty. CoRR abs/2402.00681 (2024) - [i22]Tommaso Benciolini, Yuntian Yan, Dirk Wollherr, Marion Leibold:
Combining Belief Function Theory and Stochastic Model Predictive Control for Multi-Modal Uncertainty in Autonomous Driving. CoRR abs/2402.00697 (2024) - [i21]Michael Fink, Tim Brüdigam, Dirk Wollherr, Marion Leibold:
Minimal Constraint Violation Probability in Model Predictive Control for Linear Systems. CoRR abs/2402.10538 (2024) - [i20]Tommaso Benciolini, Michael Fink, Nehir Güzelkaya, Dirk Wollherr, Marion Leibold:
Safe and Non-Conservative Trajectory Planning for Autonomous Driving Handling Unanticipated Behaviors of Traffic Participants. CoRR abs/2406.13396 (2024) - [i19]Johannes Teutsch, Christopher Narr, Sebastian Kerz, Dirk Wollherr, Marion Leibold:
Adaptive Stochastic Predictive Control from Noisy Data: A Sampling-based Approach. CoRR abs/2409.01955 (2024) - 2023
- [j15]Tim Brüdigam, Michael Olbrich, Dirk Wollherr, Marion Leibold:
Stochastic Model Predictive Control With a Safety Guarantee for Automated Driving. IEEE Trans. Intell. Veh. 8(1): 22-36 (2023) - [j14]Tommaso Benciolini, Dirk Wollherr, Marion Leibold:
Non-Conservative Trajectory Planning for Automated Vehicles by Estimating Intentions of Dynamic Obstacles. IEEE Trans. Intell. Veh. 8(3): 2463-2481 (2023) - [j13]Zhehua Zhou, Ozgur S. Oguz, Marion Leibold, Martin Buss:
Learning a Low-Dimensional Representation of a Safe Region for Safe Reinforcement Learning on Dynamical Systems. IEEE Trans. Neural Networks Learn. Syst. 34(5): 2513-2527 (2023) - [c18]Ni Dang, Tao Shi, Zengjie Zhang, Wanxin Jin, Marion Leibold, Martin Buss:
Identifying Reaction-Aware Driving Styles of Stochastic Model Predictive Controlled Vehicles by Inverse Reinforcement Learning. ITSC 2023: 2887-2892 - [i18]Johannes Teutsch, Sebastian Kerz, Tim Brüdigam, Dirk Wollherr, Marion Leibold:
Offline Uncertainty Sampling in Data-driven Stochastic MPC. CoRR abs/2304.03088 (2023) - [i17]Johannes Teutsch, Sebastian Ellmaier, Sebastian Kerz, Dirk Wollherr, Marion Leibold:
An Online Adaptation Strategy for Direct Data-driven Control. CoRR abs/2304.03386 (2023) - [i16]Ni Dang, Tao Shi, Zengjie Zhang, Wanxin Jin, Marion Leibold, Martin Buss:
Identifying Reaction-Aware Driving Styles of Stochastic Model Predictive Controlled Vehicles by Inverse Reinforcement Learning. CoRR abs/2308.12069 (2023) - [i15]Annalena Daniels, Michael Fink, Marion Leibold, Dirk Wollherr, Senthold Asseng:
Optimal Control for Indoor Vertical Farms Based on Crop Growth. CoRR abs/2309.07540 (2023) - [i14]Ni Dang, Zengjie Zhang, Jizheng Liu, Marion Leibold, Martin Buss:
Incorporating Target Vehicle Trajectories Predicted by Deep Learning Into Model Predictive Controlled Vehicles. CoRR abs/2310.02843 (2023) - [i13]Tommaso Benciolini, Chen Tang, Marion Leibold, Catherine Weaver, Masayoshi Tomizuka, Wei Zhan:
Active Exploration in Iterative Gaussian Process Regression for Uncertainty Modeling in Autonomous Racing. CoRR abs/2311.01993 (2023) - 2022
- [j12]Khoi Hoang Dinh, Marion Leibold, Dirk Wollherr:
A Fast and Close-to-Optimal Receding Horizon Control for Trajectory Generation in Dynamic Environments. Robotics 11(4): 72 (2022) - [j11]Yongchao Wang, Marion Leibold, Jinoh Lee, Wenyan Ye, Jing Xie, Martin Buss:
Incremental Model Predictive Control Exploiting Time-Delay Estimation for a Robot Manipulator. IEEE Trans. Control. Syst. Technol. 30(6): 2285-2300 (2022) - [c17]Tim Brüdigam, Robert Jacumet, Dirk Wollherr, Marion Leibold:
Safe Stochastic Model Predictive Control. CDC 2022: 1796-1802 - [c16]Michael Fink, Tim Brüdigam, Dirk Wollherr, Marion Leibold:
Constraint Violation Probability Minimization for Norm-Constrained Linear Model Predictive Control. ECC 2022: 839-846 - [i12]Tim Brüdigam, Robert Jacumet, Dirk Wollherr, Marion Leibold, Francesco Borrelli:
Safe Stochastic Model Predictive Control. CoRR abs/2204.06207 (2022) - 2021
- [j10]Tim Brüdigam, Johannes Teutsch, Dirk Wollherr, Marion Leibold, Martin Buss:
Probabilistic model predictive control for extended prediction horizons. Autom. 69(9): 759-770 (2021) - [c15]Tim Brüdigam, Daniel Prader, Dirk Wollherr, Marion Leibold:
Model Predictive Control with Models of Different Granularity and a Non-uniformly Spaced Prediction Horizon. ACC 2021: 3876-3881 - [c14]Tommaso Benciolini, Tim Brüdigam, Marion Leibold:
Multistage Stochastic Model Predictive Control for Urban Automated Driving. ITSC 2021: 417-423 - [c13]Tim Brüdigam, Jie Zhan, Dirk Wollherr, Marion Leibold:
Collision Avoidance with Stochastic Model Predictive Control for Systems with a Twofold Uncertainty Structure. ITSC 2021: 432-438 - [i11]Tim Brüdigam, Alexandre Capone, Sandra Hirche, Dirk Wollherr, Marion Leibold:
Gaussian Process-based Stochastic Model Predictive Control for Overtaking in Autonomous Racing. CoRR abs/2105.12236 (2021) - [i10]Tim Brüdigam, Jie Zhan, Dirk Wollherr, Marion Leibold:
Collision Avoidance with Stochastic Model Predictive Control for Systems with a Twofold Uncertainty Structure. CoRR abs/2106.08463 (2021) - [i9]Tommaso Benciolini, Tim Brüdigam, Marion Leibold:
Multistage Stochastic Model Predictive Control for Urban Automated Driving. CoRR abs/2107.00529 (2021) - [i8]Tim Brüdigam, Daniel Prader, Dirk Wollherr, Marion Leibold:
Model Predictive Control with Models of Different Granularity and a Non-uniformly Spaced Prediction Horizon. CoRR abs/2108.08014 (2021) - [i7]Zhehua Zhou, Ozgur S. Oguz, Yi Ren, Marion Leibold, Martin Buss:
Data Generation Method for Learning a Low-dimensional Safe Region in Safe Reinforcement Learning. CoRR abs/2109.05077 (2021) - [i6]Sebastian Kerz, Johannes Teutsch, Tim Brüdigam, Dirk Wollherr, Marion Leibold:
Data-driven stochastic model predictive control. CoRR abs/2112.04439 (2021) - 2020
- [j9]Rameez Hayat, Marion Leibold, Martin Buss:
Addressing Control Implementation Issues in Robotic Systems Using Adaptive Control. Robotica 38(1): 171-184 (2020) - [j8]Zengjie Zhang, Marion Leibold, Dirk Wollherr:
Integral Sliding-Mode Observer-Based Disturbance Estimation for Euler-Lagrangian Systems. IEEE Trans. Control. Syst. Technol. 28(6): 2377-2389 (2020) - [j7]Zhehua Zhou, Ozgur S. Oguz, Marion Leibold, Martin Buss:
A General Framework to Increase Safety of Learning Algorithms for Dynamical Systems Based on Region of Attraction Estimation. IEEE Trans. Robotics 36(5): 1472-1490 (2020) - [c12]Tim Brüdigam, Fulvio di Luzio, Lucia Pallottino, Dirk Wollherr, Marion Leibold:
Grid-Based Stochastic Model Predictive Control for Trajectory Planning in Uncertain Environments. ITSC 2020: 1-8 - [i5]Tim Brüdigam, Johannes Teutsch, Dirk Wollherr, Marion Leibold:
Combined Robust and Stochastic Model Predictive Control for Models of Different Granularity. CoRR abs/2003.06652 (2020) - [i4]Tim Brüdigam, Victor Gaßmann, Dirk Wollherr, Marion Leibold:
Minimization of Constraint Violation Probability in Model Predictive Control. CoRR abs/2006.02337 (2020) - [i3]Tim Brüdigam, Fulvio di Luzio, Lucia Pallottino, Dirk Wollherr, Marion Leibold:
Grid-Based Stochastic Model Predictive Control for Trajectory Planning in Uncertain Environments. CoRR abs/2007.12430 (2020) - [i2]Tim Brüdigam, Michael Olbrich, Dirk Wollherr, Marion Leibold:
Stochastic Model Predictive Control with a Safety Guarantee for Automated Driving. CoRR abs/2009.09381 (2020) - [i1]Zhehua Zhou, Ozgur S. Oguz, Marion Leibold, Martin Buss:
Learning a Low-dimensional Representation of a Safe Region for Safe Reinforcement Learning on Dynamical Systems. CoRR abs/2010.09555 (2020)
2010 – 2019
- 2018
- [j6]Rameez Hayat, Marion Leibold, Martin Buss:
Robust-Adaptive Controller Design for Robot Manipulators Using the ℋ∞ Approach. IEEE Access 6: 51626-51639 (2018) - [j5]Sotiris Apostolopoulos, Marion Leibold, Martin Buss:
Transitioning Between Underactuated Periodic Orbits: An Optimal Control Approach for Settling Time Reduction. Int. J. Humanoid Robotics 15(6): 1850027:1-1850027:21 (2018) - [c11]Tim Brüdigam, Michael Olbrich, Marion Leibold, Dirk Wollherr:
Combining Stochastic and Scenario Model Predictive Control to Handle Target Vehicle Uncertainty in an Autonomous Driving Highway Scenario. ITSC 2018: 1317-1324 - 2017
- [j4]Sotiris Apostolopoulos, Marion Leibold, Martin Buss:
Energy Efficient and Robust Balancing with Motion Primitive Switching. Int. J. Humanoid Robotics 14(3): 1750009:1-1750009:32 (2017) - [c10]Roman Weiss, Benjamin Grossmann, Marion Leibold, Thomas Schlegl, Dirk Wollherr:
Modeling and nonlinear control of antagonistically actuating pneumatic artificial muscles. AIM 2017: 94-99 - [c9]Yiyong Sun, Zengjie Zhang, Marion Leibold, Rameez Hayat, Dirk Wollherr, Martin Buss:
Protective control for robot manipulator by sliding mode based disturbance reconstruction approach. AIM 2017: 1015-1022 - [c8]Khoi Hoang Dinh, Philipp Weiler, Marion Leibold, Dirk Wollherr:
Fast and close to optimal trajectory generation for articulated robots in reaching motions. AIM 2017: 1221-1227 - [c7]Stefanie Manzinger, Marion Leibold, Matthias Althoff:
Driving strategy selection for cooperative vehicles using maneuver templates. Intelligent Vehicles Symposium 2017: 647-654 - 2016
- [c6]Sotiris Apostolopoulos, Marion Leibold, Martin Buss:
Online motion planning over uneven terrain with walking primitives and regression. ICRA 2016: 3799-3805 - 2015
- [c5]Sotiris Apostolopoulos, Marion Leibold, Martin Buss:
Settling time reduction for underactuated walking robots. IROS 2015: 6402-6408 - 2014
- [j3]Benjamin Passenberg, Marion Leibold, Olaf Stursberg, Martin Buss:
A Globally Convergent, Locally Optimal Min-H Algorithm for Hybrid Optimal Control. SIAM J. Control. Optim. 52(1): 718-746 (2014) - 2013
- [j2]Benjamin Passenberg, Peter E. Caines, Marion Leibold, Olaf Stursberg, Martin Buss:
Optimal Control for Hybrid Systems With Partitioned State Space. IEEE Trans. Autom. Control. 58(8): 2131-2136 (2013) - 2012
- [j1]Sohee Lee, Marion Leibold, Martin Buss, Frank Chongwoo Park:
Rollover Prevention of Mobile Manipulators using Invariance Control and Recursive analytic Zmp Gradients. Adv. Robotics 26(11-12): 1317-1341 (2012) - [c4]Sohee Lee, Marion Leibold, Martin Buss, Frank C. Park:
Online stability compensation of mobile manipulators using recursive calculation of ZMP gradients. ICRA 2012: 850-855 - 2011
- [c3]Michael Steinegger, Benjamin Passenberg, Marion Leibold, Martin Buss:
Trajectory planning for manipulators based on the optimal concatenation of LQ control primitives. CDC/ECC 2011: 2837-2842 - [c2]Benjamin Passenberg, Marion Leibold, Olaf Stursberg, Martin Buss:
The minimum principle for time-varying hybrid systems with state switching and jumps. CDC/ECC 2011: 6723-6729 - [c1]Sebastian Albrecht, Karinne Ramirez-Amaro, Federico Ruiz-Ugalde, David Weikersdorfer, Marion Leibold, Michael Ulbrich, Michael Beetz:
Imitating human reaching motions using physically inspired optimization principles. Humanoids 2011: 602-607
Coauthor Index
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