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1816 result(s) for “Machine Learning for Robot Control” Page 3 of 37
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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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DecAP : Decaying Action Priors for Accelerated Imitation Learning of Torque-Based Legged Locomotion Policies
Shivam Sood, GE SUN, Peizhuo LI, Guillaume Adrien Sartoretti
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Exploring Constrained Reinforcement Learning Algorithms for Quadrupedal Locomotion
Joonho Lee, Lukas Schroth, Victor Klemm, Marko Bjelonic, Alexander Reske, Marco Hutter
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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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Tube-GAN: A Novel Virtual Tube Generation Method for Unmanned Aerial Swarms Based on Generative Adversarial Network
Shixun Zhai, Kaige Zhang, Bo Nan, Yanwen Sun, qianyi fu
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Active Learning for Forward/Inverse Kinematics of Redundantly-Driven Flexible Tensegrity Manipulator
Yuhei Yoshimitsu, Takayuki Osa, Heni Ben Amor, Shuhei Ikemoto
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Learning to Walk and Fly with Adversarial Motion Priors
Giuseppe L'Erario, Drew Hanover, Angel Romero, Yunlong Song, Gabriele Nava, Paolo Maria Viceconte, Daniele Pucci, Davide Scaramuzza
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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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Competitive Multi-Team Behavior in Dynamic Flight Scenarios
Tim Niklas Seyde, Mathias Lechner, Joshua Rountree, Daniela Rus
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LEEPS: Learning End-To-End Legged Perceptive Parkour Skills on Challenging Terrains
Tangyu Qian, Hao Zhang, Zhangli Zhou, Hao Wang, Cai Mingyu, Zhen Kan
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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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Toward Understanding Key Estimation in Learning Robust Humanoid Locomotion
Zhicheng Wang, Wandi Wei, Ruiqi Yu, Jun Wu, Qiuguo Zhu
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Benchmarking Smoothness and Reducing High-Frequency Oscillations in Continuous Control Policies
Guilherme Henrique Galelli Christmann, Ying-Sheng Luo, Hanjaya Mandala, Wei-Chao Chen
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Distilling Reinforcement Learning Policies for Interpretable Robot Locomotion: Gradient Boosting Machines and Symbolic Regression
Fernando Acero, Zhibin (Alex) Li
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Guiding Reinforcement Learning with Incomplete System Dynamics
Shuyuan Wang
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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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Learning Locomotion for Quadruped Robots Via Distributional Ensemble Actor-Critic
Sicen Li, YiMing Pang, Panju Bai, Jiawei Li, Zhaojin Liu, Shihao Hu, Li-Quan Wang, Gang Wang
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DEAR: Disentangled Environment and Agent Representations for Reinforcement Learning without Reconstruction
Ameya Pore, Riccardo Muradore, Diego Dall'Alba
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Learning Long-Horizon Predictions for Quadrotor Dynamics
Pratyaksh Rao, Alessandro Saviolo, Tommaso Castiglione Ferrari, Giuseppe Loianno
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Enabling Maintainablity of Robot Programs in Assembly by Extracting Compositions of Force and Position-Based Robot Skills from Learning-From-Demonstration Models
Daniel Bargmann, Werner Kraus, Marco F. Huber
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Aligning Learning with Communication in Shared Autonomy
Joshua Hoegerman, Shahabedin Sagheb, Benjamin Christie, Dylan Losey
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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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Language-Guided Pattern Formation for Swarm Robotics with Multi-Agent Reinforcement Learning
Hsu-Shen Liu, So Kuroki, Tadashi Kozuno, Wei-Fang Sun, Chun-Yi Lee
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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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TraKDis: A Transformer-Based Knowledge Distillation Approach for Visual Reinforcement Learning with Application to Cloth Manipulation
Wei Chen, Nicolas Rojas
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Learning Generalizable Manipulation Policy with Adapter-Based Parameter Fine-Tuning
Kai Lu, Kim Tien Ly, William Hebberd, kaichen zhou, Ioannis Havoutis, Andrew Markham
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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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RESPRECT: Speeding-Up Multi-Fingered Grasping with Residual Reinforcement Learning
Federico Ceola, Lorenzo Rosasco, Lorenzo Natale
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DexDribbler: Learning Dexterous Soccer Manipulation Via Dynamic Supervision
Yutong Hu, Kehan Wen, Fisher Yu
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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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Driving from Vision through Differentiable Optimal Control
Flavia Sofia Acerbo, Jan Swevers, Tinne Tuytelaars, Son Tong
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Reducing Performance Variability and Overcoming Limited Spatial Ability: Targeted Training for Remote Robot Teleoperation
Tsung-Chi Lin, Juo-Tung Chen, Chien-Ming Huang
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Working Backwards: Learning to Place by Picking
Oliver Limoyo, Abhisek Konar, Trevor Ablett, Jonathan Kelly, Francois Hogan, Gregory Dudek
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Multi-Task Adaptive Gating Network for Trajectory Distilled Control Prediction
Shoaib Azam, Ville Kyrki
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PA-LOCO: Learning Perturbation-Adaptive Locomotion for Quadruped Robots
Zhiyuan Xiao, Xinyu Zhang, Xiang Zhou, Qingrui Zhang
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MQE: Unleashing the Power of Interaction with Multi-Agent Quadruped Environment
Ziyan Xiong, bo chen, Shiyu Huang, Wei-Wei Tu, Zhaofeng He, Yang Gao
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DRIFT: Deep Reinforcement Learning for Intelligent Floating Platforms Trajectories
Matteo El Hariry, Antoine Richard, Vivek Muralidharan, Matthieu Geist, Miguel A. Olivares-Mendez
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Autonomous Landing on a Moving Platform Using Vision-Based Deep Reinforcement Learning
Pawel Ladosz, Meraj Mammadov, Heejung Shin, Woojae Shin, Hyondong Oh
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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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Neuromorphic Force-Control in an Industrial Task: Validating Energy and Latency Benefits
Camilo Amaya, Evan Eames, Gintautas Palinauskas, Alexander Clifford Perzylo, Yulia Sandamirskaya, Axel von Arnim
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TacLink-Integrated Robot Arm Toward Safe Human-Robot Interaction
Quan Luu, Alessandro Albini, Perla Maiolino, Van Ho
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Preventing Catastrophic Forgetting in Continuous Online Learning for Autonomous Driving
Rui Yang, Zhi Yan, Tao Yang, Tomáï¿1⁄2 Krajník, Yassine Ruichek
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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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Image-Based Deep Reinforcement Learning with Intrinsically Motivated Stimuli: On the Execution of Complex Robotic Tasks
David Patricio Valencia Redrovan, Henry Williams, Yuning Xing, Trevor Gee, Minas Liarokapis, Bruce MacDonald
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IntervenGen: Interventional Data Generation for Robust and Data-Efficient Robot Imitation Learning
Ryan Hoque, Ajay Uday Mandlekar, Caelan Garrett, Ken Goldberg, Dieter Fox
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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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Tactile Active Inference Reinforcement Learning for Efficient Robotic Manipulation Skill Acquisition
Zihao Liu, Xing Liu, Zhengxiong Liu, Yizhai Zhang, Panfeng Huang
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SuFIA: Language-Guided Augmented Dexterity for Robotic Surgical Assistants
Masoud Moghani, Lars Doorenbos, William Panitch, Sean Huver, Mahdi Azizian, Ken Goldberg, Animesh Garg
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Multi-Modal Representation Learning with Tactile Data
Hyung-gun Chi, Jean Mercat, Jose Barreiros, Karthik Ramani, Thomas Kollar
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Insert-One: One-Shot Robust Visual-Force Servoing for Novel Object Insertion with 6-DoF Tracking
Haonan Chang, Abdeslam Boularias, Siddarth Jain
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