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508 result(s) for “Incremental Learning” Page 1 of 11
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Incremental Few-Shot Object Detection Via Simple Fine-Tuning Approach
Tae-Min Choi, Jong-Hwan Kim
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Cautious Planning with Incremental Symbolic Perception: Designing Verified Reactive Driving Maneuvers
Disha Kamale, Sofie Haesaert, Cristian Ioan Vasile
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Robust Incremental Smoothing and Mapping (riSAM)
Daniel McGann, John G. Rogers III, Michael Kaess
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Faster-LIO: Lightweight Tightly Coupled Lidar-Inertial Odometry Using Parallel Sparse Incremental Voxels
Chunge Bai, Tao Xiao, Yajie Chen, Haoqian Wang, Fang Zhang, Xiang Gao
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IMODE: Real-Time Incremental Monocular Dense Mapping Using Neural Field
Hidenobu Matsuki, Edgar Sucar, Tristan Laidlow, Kentaro Wada, Raluca Scona, Andrew J Davison
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AdaSfM: From Coarse Global to Fine Incremental Adaptive Structure from Motion
Yu Chen, Zihao Yu, shu song, jianming li, Tianning YU, Gim Hee Lee
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GuILD: Guided Incremental Local Densification for Accelerated Sampling-Based Motion Planning
Rosario Scalise, Aditya Mandalika, Brian Hou, Sanjiban Choudhury, Siddhartha Srinivasa
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Streaming LifeLong Learning with Any-Time Inference
Soumya Banerjee, Vinay Kumar Verma, Vinay Namboodiri
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Explain What You See: Open-Ended Segmentation and Recognition of Occluded 3D Objects
Hamed Ayoobi, Hamidreza Kasaei, Ming Cao, Rineke Verbrugge, Bart Verheij
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SHINE-Mapping: Large-Scale 3D Mapping Using Sparse Hierarchical Implicit Neural Representations
Xingguang Zhong, Yue Pan, Jens Behley, Cyrill Stachniss
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Contact-Based Pose Estimation of Workpieces for Robotic Setups
Yitaek Kim, Aljaz Kramberger, Anders Glent Buch, Christoffer Sloth
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Torque-Limited Manipulation Planning through Contact by Interleaving Graph Search and Trajectory Optimization
Ramkumar Natarajan, Garrison Johnston, Nabil Simaan, Maxim Likhachev, Howie Choset
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A Consistency-Based Loss for Deep Odometry through Uncertainty Propagation
Hamed Damirchi, Rooholla Khorrambakht, Hamid D. Taghirad, Behzad Moshiri
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A Comparative Study of Nonlinear MPC and Differential-Flatness-Based Control for Quadrotor Agile Flight
Sihao Sun, Angel Romero, Philipp Foehn, Elia Kaufmann, Davide Scaramuzza
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DreamWaQ: Learning Robust Quadrupedal Locomotion With Implicit Terrain Imagination via Deep Reinforcement Learning
I Made Aswin Nahrendra, Byeongho Yu, Hyun Myung
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Learning Stabilization Control from Observations by Learning Lyapunov-Like Proxy Models
Milan Ganai, Chiaki Hirayama, Ya-Chien Chang, Sicun Gao
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FSG-Net: A Deep Learning Model for Semantic Robot Grasping through Few-Shot Learning
Leonardo Barcellona, Alberto Bacchin, Alberto Gottardi, Emanuele Menegatti, Stefano Ghidoni
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Sample-Efficient Goal-Conditioned Reinforcement Learning Via Predictive Information Bottleneck for Goal Representation Learning
qiming zou, Einoshin Suzuki
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FOGL: Federated Object Grasping Learning
Seok-Kyu Kang, Changhyun Choi
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Learning from Demonstrations Via Multi-Level and Multi-Attention Domain-Adaptive Meta-Learning
Ziye Hu, Zhongxue Gan, Wei Li, Weikun Guo, Xiang Gao, Jiwei Zhu
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Using Learning Curve Predictions to Learn from Incorrect Feedback
Taylor Kessler Faulkner, Andrea Lockerd Thomaz
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Learning Risk-Aware Costmaps Via Inverse Reinforcement Learning for Off-Road Navigation
Samuel Triest, Mateo Guaman Castro, Parv Maheshwari, Matthew Sivaprakasam, Wenshan Wang, Sebastian Scherer
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Grey-Box Learning of Adaptive Manipulation Primitives for Robotic Assembly
Marco Braun, Sebastian Wrede
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Benchmarking Reinforcement Learning Techniques for Autonomous Navigation
Zifan Xu, Bo Liu, Xuesu Xiao, Anirudh Nair, Peter Stone
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Uncertainty-Guided Active Reinforcement Learning with Bayesian Neural Networks
Xinyang Wu, Mohamed El-Shamouty, Christof Nitsche, Marco F. Huber
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GAN-Based Interactive Reinforcement Learning from Demonstration and Human Evaluative Feedback
Jie Huang, Jiangshan Hao, Rongshun Juan, Randy Gomez, Keisuke Nakamura, Guangliang Li
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Guided Reinforcement Learning � A Review and Evaluation for Efficient and Effective Real-World Robotics
Julian Eßer, Nicolas Bach, Christian Jestel, Oliver Urbann, Sören Kerner
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Learning Stable Dynamics Via Iterative Quadratic Programming
Paul Gesel, Momotaz Begum
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Safeguarding Learning-Based Planners under Motion and Sensing Uncertainties Using Reachability Analysis
Akshay Shetty, Adam Dai, Alexandros Tzikas, Grace Gao
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Sample-Driven Connectivity Learning for Motion Planning
Sihui Li, Neil Dantam
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SEIL: Simulation-augmented Equivariant Imitation Learning
Mingxi Jia, Dian Wang, Guanang Su, David Klee, Xupeng Zhu, Robin Walters, Robert Platt
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Reinforcement Learning for Laser Welding Speed Control Minimizing Bead Width Error
Toshimitsu Kaneko, Gaku Minamoto, Yusuke Hirose, Tetsuo Sakai
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Real World Offline Reinforcement Learning with Realistic Data Source
Gaoyue Zhou, Liyiming Ke, Siddhartha Srinivasa, Abhinav Gupta, Aravind Rajeswaran, Vikash Kumar
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Guiding Reinforcement Learning with Shared Control Templates
Abhishek Padalkar, Gabriel Quere, Franz Steinmetz, Antonin Raffin, Matthias Nieuwenhuisen, João Silvério, Freek Stulp
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Learning Augmented, Multi-Robot Long-Horizon Navigation in Partially Mapped Environments
Abhish Khanal, Gregory Stein
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FewSOL: A Dataset for Few-Shot Object Learning in Robotic Environments
Jishnu Jaykumar P, Yu-Wei Chao, Yu Xiang
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Dexterous Imitation Made Easy: A Learning-Based Framework for Efficient Dexterous Manipulation
Sridhar Pandian Arunachalam, Sneha Silwal, Ben Evans, Lerrel Pinto
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Agile and Versatile Robot Locomotion Via Kernel-Based Residual Learning
Milo Carroll, Zhaocheng Liu, Mohammadreza Kasaei, Zhibin Li
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Learning to Forecast Aleatoric and Epistemic Uncertainties Over Long Horizon Trajectories
Aastha Acharya, Rebecca Russell, Nisar Ahmed
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Minimizing Human Assistance: Augmenting a Single Demonstration for Deep Reinforcement Learning
Abraham George, Alison Bartsch, Amir Barati Farimani
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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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