Research Analyzer

ICRA 2023

1655 papers · 0 AI summaries · 2023

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1013 result(s) for “Learning from Experience” Page 5 of 21
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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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Data-Efficient Learning of Natural Language to Linear Temporal Logic Translators for Robot Task Specification
Jiayi Pan, Glen Chou, Dmitry Berenson
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Robotic Control Using Model Based Meta Adaption
Karam Daaboul, Joel Ikels, Johann Marius Zöllner
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Tumbling Robot Control Using Reinforcement Learning
Andrew Schwartzwald, Matthew Tlachac, Luis Guzman, Athanasios Bacharis, Nikos Papanikolopoulos
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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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Ultra-Low Power Deep Learning-Based Monocular Relative Localization Onboard Nano-Quadrotors
Stefano Bonato, Stefano Carlo Lambertenghi, Elia Cereda, Alessandro Giusti, Daniele Palossi
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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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Developing Cooperative Policies for Multi-Stage Reinforcement Learning Tasks
Jordan Erskine, Christopher Lehnert
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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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Learning Visual-Audio Representations for Voice-Controlled Robots
Peixin Chang, Shuijing Liu, D. Livingston McPherson, Katherine Driggs-Campbell
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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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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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Adaptive Risk-Tendency: Nano Drone Navigation in Cluttered Environments with Distributional Reinforcement Learning
Cheng Liu, Erik-Jan van Kampen, Guido de Croon
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Explainable Action Advising for Multi-Agent Reinforcement Learning
Yue Guo, Joseph Campbell, Simon Stepputtis, Ruiyu Li, Dana Hughes, Fei Fang, Katia Sycara
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Self-Supervised Point Cloud Understanding Via Mask Transformer and Contrastive Learning
DI WANG, Zhi-Xin Yang
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Experimental Validation of Functional Iterative Learning Control on a One-Link Flexible Arm
Sjoerd Drost, Pietro Pustina, Franco Angelini, Alessandro De Luca, Gerwin Smit, Cosimo Della Santina
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Conflict-Constrained Multi-Agent Reinforcement Learning Method for Parking Trajectory Planning
Siyuan Chen, Meiling Wang, Yi Yang, Wenjie Song
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Slice Transformer and Self-Supervised Learning for 6DoF Localization in 3D Point Cloud Maps
Muhammad Ibrahim, Naveed Akhtar, Saeed Anwar, michael wise, Ajmal Mian
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RLAfford: End-to-End Affordance Learning for Robotic Manipulation
Yiran Geng, boshi an, Haoran Geng, Yuanpei Chen, Yaodong Yang, Hao Dong
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Reinforcement Learning Control of a Reconfigurable Planar Cable Driven Parallel Manipulator
Adhiti Raman Thothathri, Ameya Salvi, Matthias Schmid, Venkat Krovi
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Augmented Reality-Assisted Robot Learning Framework for Minimally Invasive Surgery Task
Junling Fu, Maria Chiara Palumbo, Elisa Iovene, Qingsheng liu, Ilaria Burzo, Alberto Redaelli, Giancarlo Ferrigno, Elena De Momi
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Learning Exploration Strategies to Solve Real-World Marble Runs
Alisa Allaire, Christopher Atkeson
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GIDP: Learning a Good Initialization and Inducing Descriptor Post-Enhancing for Large-Scale Place Recognition
Zhaoxin Fan, Zhenbo Song, Jun He, Hongyan Liu
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Deep Predictive Model Learning with Parametric Bias: Handling Modeling Difficulties and Temporal Model Changes
Kento Kawaharazuka, Kei Okada, Masayuki Inaba
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Deep Reinforcement Learning for Autonomous Driving Using High-Level Heterogeneous Graph Representations
Maximilian Schier, Christoph Reinders, Bodo Rosenhahn
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Toward Fine Contact Interactions: Learning to Control Normal Contact Force with Limited Information
Jinda Cui, Jiawei Xu, David Saldaña, Jeff Trinkle
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Learning Modular Robot Visual-Motor Locomotion Policies
Julian Whitman, Howie Choset
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NOCaL: Calibration-Free Semi-Supervised Learning of Odometry and Camera Intrinsics
Ryan Griffiths, Jack Naylor, Donald Dansereau
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Self-Improving Safety Performance of Reinforcement Learning Based Driving with Black-Box Verification Algorithms
Resul Dagdanov, Halil Durmuş, Nazim Kemal Ure
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DriveIRL: Drive in Real Life with Inverse Reinforcement Learning
Tung Phan-Minh, Forbes Howington, Ting-Sheng Chu, Momchil Tomov, Robert Beaudoin, Sang Uk Lee, Nanxiang Li, Caglayan Dicle, Samuel Findler, Francisco Suárez-Ruiz, Bo Yang, Sammy Omari, Eric Wolff
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Sim-To-Real Policy and Reward Transfer with Adaptive Forward Dynamics Model
Rongshun Juan, Hao Ju, Jie Huang, Randy Gomez, Keisuke Nakamura, Guangliang Li
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Efficient Planning of Multi-Robot Collective Transport Using Graph Reinforcement Learning with Higher Order Topological Abstraction
Steve Paul, Wenyuan Li, Brian Smyth, Yuzhou Chen, Yulia Gel, Souma Chowdhury
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Unsupervised Learning of Depth and Pose Based on Monocular Camera and Inertial Measurement Unit (IMU)
Yanbo Wang, Hanwen Yang, Jianwei Cai, Guangming Wang, Jingchuan Wang, YI Huang
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Sim-And-Real Reinforcement Learning for Manipulation: A Consensus-Based Approach
Wenxing Liu, Hanlin Niu, Wei Pan, Guido Herrmann, Joaquin Carrasco
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Efficient Preference-Based Reinforcement Learning Using Learned Dynamics Models
Yi Liu, Gaurav Datta, Ellen Novoseller, Daniel Brown
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Multimodal Time Series Learning of Robots Based on Distributed and Integrated Modalities: Verification with a Simulator and Actual Robots
Hideyuki Ichiwara, Hiroshi Ito, Kenjiro Yamamoto, Hiroki Mori, Tetsuya Ogata
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RTAW: An Attention Inspired Reinforcement Learning Method for Multi-Robot Task Allocation in Warehouse Environments
Aakriti Agrawal, Amrit Singh Bedi, Dinesh Manocha
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Learning State Conditioned Linear Mappings for Low-Dimensional Control of Robotic Manipulators
Michael Przystupa, Kerrick Johnstonbaugh, Zichen Zhang, Laura Petrich, Masood Dehghan, Faezeh Haghverd, Martin Jagersand
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Online Safety Property Collection and Refinement for Safe Deep Reinforcement Learning in Mapless Navigation
Luca Marzari, Enrico Marchesini, Alessandro Farinelli
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Learning Perceptual Hallucination for Multi-Robot Navigation in Narrow Hallways
Jin Park, Xuesu Xiao, Garrett Warnell, Harel Yedidsion, Peter Stone
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Meta Reinforcement Learning for Optimal Design of Legged Robots
Alvaro Belmonte-Baeza, joonho lee, Giorgio Valsecchi, Marco Hutter
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ARiADNE: A Reinforcement Learning Approach Using Attention-Based Deep Networks for Exploration
Yuhong Cao, Tianxiang Hou, Yizhuo Wang, Xian Yi, Guillaume Adrien Sartoretti
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Learning Food Picking without Food: Fracture Anticipation by Breaking Reusable Fragile Objects
Rinto Yagawa, Reina Ishikawa, Masashi Hamaya, Kazutoshi Tanaka, Atsushi Hashimoto, Hideo Saito
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CPG-RL: Learning Central Pattern Generators for Quadruped Locomotion
Guillaume Bellegarda, Auke Ijspeert
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