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1808 result(s) for “Model Learning for Control” Page 1 of 37
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Social Navigation in Crowded Environments with Model Predictive Control and Deep Learning-Based Human Trajectory Prediction
Viet-Anh Le, Behdad Chalaki, Vaishnav Tadiparthi, Hossein Nourkhiz Mahjoub, Jovin D'sa, Ehsan Moradi-Pari
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Adaptive Stochastic Nonlinear Model Predictive Control with Look-Ahead Deep Reinforcement Learning for Autonomous Vehicle Motion Control
Baha Zarrouki, Chenyang Wang, Johannes Betz
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Bird's-Eye-View Trajectory Planning of Multiple Robots using Continuous Deep Reinforcement Learning and Model Predictive Control
Kristian Ceder, Ze Zhang, Adam Burman, Ilya Kuangaliyev, Krister Mattsson, Gabriel Nyman, Arvid Petersén, Lukas Wisell, Knut Akesson
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Safe Imitation Learning of Nonlinear Model Predictive Control for Flexible Robots
Shamil Mamedov, Rudolf Reiter, Seyed Mahdi Basiri Azad, Ruan Matthys Viljoen, Joschka Boedecker, Moritz Diehl, Jan Swevers
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Collision-Free Robot Navigation in Crowded Environments Using Learning Based Convex Model Predictive Control
ZhuangLei Wen, Mingze Dong, xiai chen
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Unsupervised Multiple Proactive Behavior Learning of Mobile Robots for Smooth and Safe Navigation
Arthicha Srisuchinnawong, Jonas Baech, Marek Piotr Hyzy, Tsampikos Kounalakis, Evangelos Boukas, Poramate Manoonpong
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Diff-Control: A Stateful Diffusion-Based Policy for Imitation Learning
Xiao Liu, Yifan Zhou, Fabian Clemens Weigend, Shubham Sonawani, Shuhei Ikemoto, Heni Ben Amor
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Human-Robot Interaction Control for Multi-Mode Exosuit with Reinforcement Learning
Kaizhen Huang, Jiajun XU, Tianyi Zhang, Mengcheng Zhao, Aihong Ji, Guoli Song, Y.F. Li
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Reinforcement Learning Control for Autonomous Hydraulic Material Handling Machines with Underactuated Tools
Filippo Alberto Spinelli, Pascal Arturo Egli, Julian Nubert, Fang Nan, Thilo Bleumer, Patrick Goegler, Stephan Brockes, Ferdinand Hofmann, Marco Hutter
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Adaptive Trajectory Database Learning for Nonlinear Control with Hybrid Gradient Optimization
Kuan-Yu Tseng, Mengchao Zhang, Kris Hauser, Geir E. Dullerud
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Learning a Tracking Controller for Rolling μbots
Logan Beaver, Sokolich Max, Suhail Alsalehi, Ron Weiss, Sambeeta Das, Calin Belta
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Torque Ripple Reduction in Quasi-Direct Drive Motors through Angle-Based Repetitive Learning Observer and Model Predictive Torque Controller
Hefei Zhang, Xiaohu Zhang, Jinyu Cheng, Jiangtao Hu, Chao Ji, Yu Wang, Yutong Jiang, Zhen Han, Wei Gao, Shiwu Zhang
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HeteroLight: A General and Efficient Learning Approach for Heterogeneous Traffic Signal Control
YIFENG ZHANG, Peizhuo LI, Mingfeng Fan, Guillaume Adrien Sartoretti
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Neural ODE-Based Imitation Learning (NODE-IL): Data-Efficient Imitation Learning for Long-Horizon Multi-Skill Robot Manipulation
Shiyao Zhao, Yucheng Xu, Mohammadreza Kasaei, Mohsen Khadem, Zhibin (Alex) Li
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A Contact Model Based on Denoising Diffusion to Learn Variable Impedance Control for Contact-Rich Manipulation
Masashi Okada, Mayumi Komatsu, Tadahiro Taniguchi
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Real-Time Constrained Tracking Control of Redundant Manipulators Using a Koopman - Zeroing Neural Network Framework
Chandan Kumar Sah, Rajpal Singh, Jishnu Keshavan
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Guiding Reinforcement Learning with Incomplete System Dynamics
Shuyuan Wang
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Biased-MPPI: Informing Sampling-Based Model Predictive Control by Fusing Ancillary Controllers
Elia Trevisan, Javier Alonso-Mora
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Driving from Vision through Differentiable Optimal Control
Flavia Sofia Acerbo, Jan Swevers, Tinne Tuytelaars, Son Tong
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Rocket Landing Control with Random Annealing Jump Start Reinforcement Learning
Yuxuan Jiang, Yujie Yang, Zhiqian Lan, Guojian Zhan, Shengbo Eben Li, Qi Sun, Jian Ma, Tianwen Yu, Changwu Zhang
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TinyLidarNet: 2D Lidar-Based End-To-End Deep Learning Model for F1TENTH Autonomous Racing
Mohammed Misbah Zarrar, QiTao Weng, Bakhbyergyen Yerjan, Ahmet Soyyigit, Heechul Yun
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Integrating Online Learning and Connectivity Maintenance for Communication-Aware Multi-Robot Coordination
Yupeng Yang, Yiwei Lyu, Yanze Zhang, Ian Gao, Wenhao Luo
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Data-Efficient Task Generalization via Probabilistic Model-Based Meta Reinforcement Learning
Arjun Bhardwaj, Jonas Rothfuss, Bhavya Sukhija, Yarden As, Marco Hutter, Stelian Coros, Andreas Krause
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Online Adaptation of Learned Vehicle Dynamics Model with Meta-Learning Approach
Yuki Tsuchiya, Thomas Balch, Paul Drews, Guy Rosman
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Contact-Implicit Model Predictive Control for Dexterous In-Hand Manipulation: A Long-Horizon and Robust Approach
Yongpeng Jiang, Mingrui Yu, Xinghao Zhu, Masayoshi Tomizuka, Xiang LI
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UNO Push: Unified Nonprehensile Object Pushing Via Non-Parametric Estimation and Model Predictive Control
Gaotian Wang, Kejia Ren, Kaiyu Hang
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Integrating Model-Based Footstep Planning with Model-Free Reinforcement Learning for Dynamic Legged Locomotion
Ho Jae Lee, Seungwoo Hong, Sangbae Kim
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Model-Based Policy Optimization Using Symbolic World Model
Andrey Gorodetsky, Konstantin Mironov, Aleksandr Panov
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DMFuser: Distilled Multi-Task Learning for End-To-End Transformer-Based Sensor Fusion in Autonomous Driving
Pedram Agand, Mohammad Mahdavian, Manolis Savva, Mo Chen
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MonoForce: Self-Supervised Learning of Physics-informed Model for Predicting Robot-Terrain Interaction
Ruslan Agishev, Karel Zimmermann, Vladimir Kubelka, Martin Pecka, Tomas Svoboda
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Leveraging Demonstrator-Perceived Precision for Safe Interactive Imitation Learning of Clearance-Limited Tasks
Hanbit Oh, Takamitsu Matsubara
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Competitive Multi-Team Behavior in Dynamic Flight Scenarios
Tim Niklas Seyde, Mathias Lechner, Joshua Rountree, Daniela Rus
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Towards Accurate and Robust Dynamics and Reward Modeling for Model-Based Offline Inverse Reinforcement Learning
Gengyu Zhang, Yan Yan
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Stick Roller: Precise In-Hand Stick Rolling with a Sample-Efficient Tactile Model
Yipai Du, Pokuang Zhou, Michael Yu Wang, Wenzhao Lian, Yu She
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A Cascaded Broad Learning System for Manipulator Motion Control
Guoyu Zuo, Shuaifeng Dong, Jiyong Zhou, Shuangyue Yu
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Contact-Rich SE(3) Equivariant Robot Manipulation Task Learning Via Geometric Impedance Control
Joohwan Seo, Nikhil Potu Surya Prakash, Xiang Zhang, Changhao Wang, Jongeun Choi, Masayoshi Tomizuka, Roberto HOROWITZ
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Zero-Shot Transfer of a Tactile-Based Continuous Force Control Policy from Simulation to Robot
Luca Lach, Robert Haschke, Davide Tateo, Jan Peters, Helge Joachim Ritter, JÃolia Borrà s Sol, Carme Torras
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Iterative Reference Learning for Cartesian Impedance Control of Robot Manipulators
Julian Mauricio Salt Ducaju, Bjorn Olofsson, Rolf Johansson
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Task and Domain Adaptive Reinforcement Learning for Robot Control
Yu Tang Liu, Nilaksh Nilaksh, Aamir Ahmad
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Leveraging Symmetry in RL-Based Legged Locomotion Control
Zhi Su, Xiaoyu Huang, Daniel Felipe Ordonez Apraez, Yunfei Li, Zhongyu Li, Qiayuan Liao, Massimiliano Pontil, Claudio Semini, Giulio Turrisi, Yi Wu, Koushil Sreenath
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The Power of Input: Benchmarking Zero-Shot Sim-To-Real Transfer of Reinforcement Learning Control Policies for Quadrotor Control
Alberto Dionigi, Gabriele Costante, Giuseppe Loianno
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OmniDrones: An Efficient and Flexible Platform for Reinforcement Learning in Drone Control
Botian Xu, Feng Gao, Chao Yu, Ruize Zhang, Yi Wu, Yu Wang
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MFC-EQ: Mean-Field Control with Envelope Q-Learning for Moving Decentralized Agents in Formation
Qiushi Lin, Hang Ma
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Uncertainty-Aware Deep Imitation Learning and Deployment for Autonomous Navigation through Crowded Intersections
Zeyu Zhu, Shuai Wang, Huijing Zhao
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Learning-Based Adaptive Control of Quadruped Robots for Active Stabilization on Moving Platforms
Minsung Yoon, Heechan Shin, Jeil Jeong, Sung-eui Yoon
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Gradient-Based Regularization for Action Smoothness in Robotic Control with Reinforcement Learning
Yi Li, Hoang-Giang Cao, Cong-Tinh Dao, Yu-Cheng Chen, I-Chen Wu
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Diffusion Policies for Out-Of-Distribution Generalization in Offline Reinforcement Learning
Suzan Ece Ada, Erhan Oztop, Emre Ugur
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Diffusion Policies for Out-Of-Distribution Generalization in Offline Reinforcement Learning
Suzan Ece Ada, Erhan Oztop, Emre Ugur
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Learning Variable Compliance Control from a Few Demonstrations for Bimanual Robot with Haptic Feedback Teleoperation System
Tatsuya Kamijo, Cristian Camilo Beltran-Hernandez, Masashi Hamaya
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On the Modularity of Elementary Dynamic Actions
Moses Nah, Johannes Lachner, Federico Tessari, Neville Hogan
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