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1639 result(s) for “Learning Categories and Concepts” Page 2 of 33
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Generating a Terrain-Robustness Benchmark for Legged Locomotion: A Prototype Via Terrain Authoring and Active Learning
Chong Zhang, Lizhi Yang
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Meta-Reinforcement Learning Via Language Instructions
Zhenshan Bing, Alexander Koch, Xiangtong Yao, Kai Huang, Alois Knoll
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Biomimetic Force and Impedance Adaptation Based on Broad Learning System in Stable and Unstable Tasks
Zhenyu Lu, Ning Wang
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Seq2Seq Imitation Learning for Tactile Feedback-Based Manipulation
Wenyan Yang, Alexandre Angleraud, Roel S. Pieters, Joni Pajarinen, Joni-Kristian Kamarainen
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Benchmarking Potential Based Rewards for Learning Humanoid Locomotion
Se Hwan Jeon, Steve Heim, Charles Khazoom, Sangbae Kim
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Using Memory-Based Learning to Solve Tasks with State-Action Constraints
Mrinal Verghese, Christopher Atkeson
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Just Round: Quantized Observation Spaces Enable Memory Efficient Learning of Dynamic Locomotion
Lev Grossman, Brian Plancher
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Comparison of Model-Based and Model-Free Reinforcement Learning for Real-World Dexterous Robotic Manipulation Tasks
David Patricio Valencia Redrovan, John Jia, Raymond Li, Alex Hayashi, Megan Lecchi, Reuel Terezakis, Trevor Gee, Minas Liarokapis, Bruce MacDonald, Henry Williams
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SoLo T-DIRL: Socially-Aware Dynamic Local Planner Based on Trajectory-Ranked Deep Inverse Reinforcement Learning
Yifan Xu, Theodor Chakhachiro, Tribhi Kathuria, Maani Ghaffari
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Automated Action Evaluation for Robotic Imitation Learning Via Siamese Neural Networks
Xiang Chang, Fei Chao, Changjing Shang, Qiang Shen
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Dynamical System-Based Imitation Learning for Visual Servoing Using the Large Projection Formulation
Antonio Paolillo, Paolo Robuffo Giordano, Matteo Saveriano
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Learning Continuous Control Policies for Information-Theoretic Active Perception
Pengzhi Yang, YUHAN LIU, Shumon Koga, Arash Asgharivaskasi, Nikolay Atanasov
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Sim-To-Real: Learning Energy-Efficient Slithering Gaits for a Snake-Like Robot
Zhenshan Bing, Long Cheng, Kai Huang, Alois Knoll
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Demonstration-Bootstrapped Autonomous Practicing Via Multi-Task Reinforcement Learning
Abhishek Gupta, Corey Lynch, Brandon Kinman, Garrett Peake, Sergey Levine, Karol Hausman
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Visuo-Tactile Recognition of Partial Point Clouds Using PointNet and Curriculum Learning
Christopher Parsons, Alessandro Albini, Daniele De Martini, Perla Maiolino
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Generating Stable and Collision-Free Policies through Lyapunov Function Learning
Coulombe Alexandre, Hsiu-Chin Lin
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Learning to Walk by Steering: Perceptive Quadrupedal Locomotion in Dynamic Environments
Mingyo Seo, Ryan Gupta, Yifeng Zhu, Alexy Skoutnev, Luis Sentis, Yuke Zhu
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Option-Aware Adversarial Inverse Reinforcement Learning for Robotic Control
Jiayu Chen, Tian Lan, Vaneet Aggarwal
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Efficient Learning of Locomotion Skills through the Discovery of Diverse Environmental Trajectory Generator Priors
Shikha Surana, Bryan Wei Tern Lim, Antoine Cully
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DiffSRL: Learning Dynamical State Representation for Deformable Object Manipulation with Differentiable Simulation
Sirui Chen, Yunhao Liu, Shang Wen Yao, Jialong LI, Tingxiang Fan, Jia Pan
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Learning Decoupled Multi-touch Force Estimation, Localization and Stretch for Soft Capacitive E-skin
Abu Bakar Dawood, Claudio Coppola, Kaspar Althoefer
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Reinforcement Learning-Based Optimal Multiple Waypoint Navigation
Christos Vlachos, Panagiotis Rousseas, Charalampos Bechlioulis, Kostas Kyriakopoulos
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SHAIL: Safety-Aware Hierarchical Adversarial Imitation Learning for Autonomous Driving in Urban Environments
Arec Jamgochian, Etienne Buehrle, Johannes Fischer, Mykel Kochenderfer
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Learning Generalizable Pivoting Skills
Xiang Zhang, Siddarth Jain, Baichuan Huang, Masayoshi Tomizuka, Diego Romeres
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Model Learning with Backlash Compensation for a Tendon-Driven Surgical Robot
Francesco Cursi, Weibang Bai, Eric Yeatman, Petar Kormushev
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Tumbling Robot Control Using Reinforcement Learning
Andrew Schwartzwald, Matthew Tlachac, Luis Guzman, Athanasios Bacharis, Nikos Papanikolopoulos
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Automating Reinforcement Learning with Example-Based Resets
Jigang Kim, J. hyeon Park, Daesol Cho, H. Jin Kim
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Expanding the Deployment Envelope of Behavior Prediction Via Adaptive Meta-Learning
Boris Ivanovic, James Harrison, Marco Pavone
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Show Me What You Want: Inverse Reinforcement Learning to Automatically Design Robot Swarms by Demonstration
Ilyes Gharbi, Jonas Kuckling, David Garzón Ramos, Mauro Birattari
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Security-Aware Reinforcement Learning under Linear Temporal Logic Specifications
Bohan Cui, Keyi Zhu, Shaoyuan Li, Xiang Yin
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SEER: Safe Efficient Exploration for Aerial Robots Using Learning to Predict Information Gain
Yuezhan Tao, Yuwei Wu, Beiming Li, Fernando Cladera Ojeda, Alex Zhou, Dinesh Thakur, Vijay Kumar
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DeepRING: Learning Roto-Translation Invariant Representation for LiDAR Based Place Recognition
Sha Lu, Xuecheng Xu, Li Tang, Rong Xiong, Yue Wang
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Efficient Learning of High Level Plans from Play
NÃoria Armengol Urpí, Marco Bagatella, Otmar Hilliges, Georg Martius, Stelian Coros
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Developing Cooperative Policies for Multi-Stage Reinforcement Learning Tasks
Jordan Erskine, Christopher Lehnert
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LEMURS: Learning Distributed Multi-Robot Interactions
Eduardo Sebastián, Thai Duong, Nikolay Atanasov, Eduardo Montijano, Carlos Sagues
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Joint Semi-Supervised and Active Learning Via 3D Consistency for 3D Object Detection
Sihwan Hwang, Sanmin Kim, YoungSeok Kim, Dongsuk Kum
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Zero-Shot Policy Transfer with Disentangled Task Representation of Meta-Reinforcement Learning
Zheng Wu, Yichen Xie, Wenzhao Lian, Changhao Wang, Yanjiang Guo, Jianyu Chen, Stefan Schaal, Masayoshi Tomizuka
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Learning and Blending Robot Hugging Behaviors in Time and Space
Drolet Michael, Joseph Campbell, Heni Ben Amor
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Adaptive and Explainable Deployment of Navigation Skills Via Hierarchical Deep Reinforcement Learning
Kyowoon Lee, Seongun Kim, Jaesik Choi
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Enforcing the Consensus between Trajectory Optimization and Policy Learning for Precise Robot Control
Quentin Le Lidec, Wilson Jallet, Ivan Laptev, Cordelia Schmid, Justin Carpentier
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Learning Visual-Audio Representations for Voice-Controlled Robots
Peixin Chang, Shuijing Liu, D. Livingston McPherson, Katherine Driggs-Campbell
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Start State Selection for Control Policy Learning from Optimal Trajectories
Christoph Zelch, Jan Peters, Oskar von Stryk
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Learning-Based Initialization of Trajectory Optimization for Path-Following Problems of Redundant Manipulators
Minsung Yoon, Mincheul Kang, Daehyung Park, Sung-eui Yoon
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Efficiently Learning Small Policies for Locomotion and Manipulation
Shashank Hegde, Gaurav Sukhatme
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Scalable Task-Driven Robotic Swarm Control Via Collision Avoidance and Learning Mean-Field Control
Kai Cui, Mengguang Li, Christian Fabian, Heinz Koeppl
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Active Predictive Coding: Brain-Inspired Reinforcement Learning for Sparse Reward Robotic Control Problems
Alexander Ororbia, Ankur Mali
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Automatic Cell Rotation Method Based on Deep Reinforcement Learning
Huiying Gong, Yujie Zhang, Yaowei Liu, Qili Zhao, Xin Zhao, Mingzhu Sun
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Multifingered Grasping Based on Multimodal Reinforcement Learning
Hongzhuo Liang, Lin Cong, Norman Hendrich, Shuang Li, Fuchun Sun, Jianwei Zhang
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Reinforcement Learning for Safe Robot Control Using Control Lyapunov Barrier Functions
Desong Du, Shaohang Han, Naiming Qi, Haitham Bou Ammar, Jun Wang, Wei Pan
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Self-Supervised Point Cloud Understanding Via Mask Transformer and Contrastive Learning
DI WANG, Zhi-Xin Yang
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