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ICRA 2024

2337 papers · 0 AI summaries · 2024

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2291 result(s) for “Learning to plan” Page 3 of 46
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CrossVideo: Self-Supervised Cross-Modal Contrastive Learning for Point Cloud Video Understanding
Yunze Liu, Changxi Chen, Zifan Wang, Li Yi
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Generalizing Cooperative Eco-driving via Multi-residual Task Learning
Vindula Jayawardana, Sirui Li, Cathy Wu, Yashar Farid, Kentaro Oguchi
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Adaptive Robot-Human Handovers with Preference Learning
Gojko Perovic, Francesco Iori, Angela Mazzeo, Marco Controzzi, Egidio Falotico
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Learning Active Manipulation to Target Shapes with Model-Free, Long-Horizon Deep Reinforcement Learning
Matias Sivertsvik, Kirill Sumskiy, Ekrem Misimi
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MOSAIC: Learning Unified Multi-Sensory Object Property Representations for Robot Learning via Interactive Perception
Gyan Tatiya, Jonathan Francis, Ho-Hsiang Wu, Yonatan Bisk, Jivko Sinapov
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Learning Needle Pick-And-Place without Expert Demonstrations
Rokas Bendikas, Valerio Modugno, Dimitrios Kanoulas, Francisco Vasconcelos, Danail Stoyanov
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ORBIT-Surgical: An Open-Simulation Framework for Learning Surgical Augmented Dexterity
Qinxi Yu, Masoud Moghani, Karthik Dharmarajan, Vincent Schorp, William Panitch, Jingzhou Liu, Kush Hari, Huang Huang, Mayank Mittal, Ken Goldberg, Animesh Garg
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An Offline Learning of Behavior Correction Policy for Vision-Based Robotic Manipulation
Qingxiuxiong Dong, Toshimitsu Kaneko, Masashi Sugiyama
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Efficient Multi-Task and Transfer Reinforcement Learning with Parameter-Compositional Framework
Lingfeng Sun, Haichao Zhang, Wei Xu, Masayoshi Tomizuka
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Mastering Stacking of Diverse Shapes with Large-Scale Iterative Reinforcement Learning on Real Robots
Thomas Lampe, Abbas Abdolmaleki, Sandy H. Huang, Sarah Bechtle, Jost Tobias Springenberg, Michael Bloesch, Oliver Groth, Roland Hafner, Tim Hertweck, Michael Neunert, Markus Wulfmeier, Jingwei Zhang, Francesco Nori, Nicolas Heess, Martin Riedmiller
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Optimal Containment Control of Multiple Quadrotors Via Reinforcement Learning
Ming Cheng, Hao Liu, Deyuan Liu, Haibo Gu, Xiangke Wang
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Reinforcement Learning for Collision-Free Flight Exploiting Deep Collision Encoding
Mihir Kulkarni, Kostas Alexis
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A Tube-Based Reinforcement Learning Approach for Optimal Motion Planning in Unknown Workspaces
Panagiotis Rousseas, Charalampos Bechlioulis, Kostas Kyriakopoulos
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Uncertainty-Driven Exploration Strategies for Online Grasp Learning
Yitian Shi, Philipp Schillinger, Miroslav Gabriel, Alexander Qualmann, Hanna Ziesche, Zohar Feldman, Ngo Anh Vien
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LEAGUE: Guided Skill Learning and Abstraction for Long-Horizon Manipulation
Shuo Cheng, Danfei Xu
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Multi-Robot Cooperative Socially-Aware Navigation Using Multi-Agent Reinforcement Learning
Weizheng Wang, Le Mao, Ruiqi Wang, Byung-Cheol Min
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Learning Model Predictive Control with Error Dynamics Regression for Autonomous Racing
Haoru Xue, Edward Zhu, John M. Dolan, Francesco Borrelli
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Learning Force Control for Legged Manipulation
Tifanny Portela, Gabriel Margolis, Yandong Ji, Pulkit Agrawal
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An Efficient Model Based Approach on Learning Agile Motor Skills without Reinforcement
Haojie Shi, Tingguang Li, Qingxu Zhu, Jiapeng Sheng, Lei Han, Max Q.-H. Meng
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Interactive Continual Learning Architecture for Long-Term Personalization of Home Service Robots
Ali Ayub, Chrystopher Nehaniv, Kerstin Dautenhahn
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Learning Failure Prevention Skills for Safe Robot Manipulation
Abdullah Cihan Ak, Eren Erdal Aksoy, Sanem Sariel
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Informed Reinforcement Learning for Situation-Aware Traffic Rule Exceptions
Daniel Bogdoll, Jing Qin, Moritz Nekolla, Ahmed Abouelazm, Tim Joseph, Johann Marius Zöllner
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Lifelong Robot Learning with Human Assisted Language Planners
Meenal Parakh, Alisha Fong, Anthony Simeonov, Tao Chen, Abhishek Gupta, Pulkit Agrawal
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Benchmarking Actor-Critic Deep Reinforcement Learning Algorithms for Robotics Control with Action Constraints
Kazumi Kasaura, Shuwa Miura, Tadashi Kozuno, Ryo Yonetani, Kenta Hoshino, Yohei Hosoe
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Distributional Reinforcement Learning with Sample-Set Bellman Update
Weijian Zhang, Jianshu Wang, Yu Yang
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Under Pressure: Learning-Based Analog Gauge Reading in the Wild
Maurits Reitsma, Julian Keller, Kenneth Blomqvist, Roland Siegwart
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Probabilistic Spiking Neural Network for Robotic Tactile Continual Learning
Senlin Fang, Yi Wen Liu, Chengliang Liu, Jingnan Wang, Yuanzhe Su, Yupo Zhang, Hoiio Kong, Zhengkun Yi, Xinyu Wu
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Direct learning of home vector direction for insect-inspired robot navigation
Michiel Vital M Firlefyn, Jesse Hagenaars, Guido de Croon
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Benchmarking Classical and Learning-Based Multibeam Point Cloud Registration
Li Ling, Jun Zhang, Nils Bore, John Folkesson, Anna Wåhlin
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Reinforcement Learning with Energy-Exchange Dynamics for Spring-Loaded Biped Robot Walking
Cheng-Yu Kuo, Hirofumi Shin, Takamitsu Matsubara
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Hierarchical Meta-Learning-Based Adaptive Controller
Fengze Xie, Guanya Shi, Michael O'Connell, Yisong Yue, Soon-Jo Chung
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Two-Stage Learning of Highly Dynamic Motions with Rigid and Articulated Soft Quadrupeds
francesco vezzi, Jiatao Ding, Antonin Raffin, Jens Kober, Cosimo Della Santina
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Gen2Sim: Scaling up Robot Learning in Simulation with Generative Models
Pushkal Katara, Zhou Xian, Aikaterini Fragkiadaki
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Learning Covariances for Estimation with Constrained Bilevel Optimization
Mohamad Qadri, Zachary Manchester, Michael Kaess
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Learning Interaction Regions and Motion Trajectories Simultaneously from Egocentric Demonstration Videos
Jianjia Xin, Lichun Wang, Kai Xu, Chao Yang, Baocai Yin
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Learning to Play Foosball: System and Baselines
Janosch Moos, Cedric Derstroff, Niklas Schröder, Debora Clever
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Co-Learning Planning and Control Policies Constrained by Differentiable Logic Specifications
Zikang Xiong, Daniel Lawson, Joe Kurian Eappen, Ahmed H. Qureshi, Suresh Jagannathan
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Contrastive Learning for Enhancing Robust Scene Transfer in Vision-Based Agile Flight
Jiaxu Xing, Leonard Bauersfeld, Yunlong Song, Chunwei Xing, Davide Scaramuzza
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Grasp Anything: Combining Teacher-Augmented Policy Gradient Learning with Instance Segmentation to Grasp Arbitrary Objects
Malte Mosbach, Sven Behnke
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Robotic Constrained Imitation Learning for the Peg Transfer Task in Fundamentals of Laparoscopic Surgery
Kento Kawaharazuka, Kei Okada, Masayuki Inaba
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Towards Real-World Efficiency: Domain Randomization in Reinforcement Learning for Pre-Capture of Free-Floating Moving Targets by Autonomous Robots
Bahador Beigomi, ZhengHong (George) Zhu
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Learning to Design 3D Printable Adaptations on Everyday Objects for Robot Manipulation
Michelle Guo, Ziang Liu, Stephen Tian, Zhaoming Xie, Jiajun Wu, Karen Liu
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Hamiltonian Dynamics Learning from Point Cloud Observations for Nonholonomic Mobile Robot Control
Abdullah Altawaitan, Jason Stanley, Sambaran Ghosal, Thai Duong, Nikolay Atanasov
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Self-Supervised Learning of Monocular Visual Odometry and Depth with Uncertainty-Aware Scale Consistency
Changhao Wang, Guanwen Zhang, Wei Zhou
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Dynamic Crane Scheduling with Reinforcement Learning for a Steel Coil Warehouse
Sang-Hyun Cho, Woo-Jin Shin, Jeongsun Ahn, Sanghyun Joo, Hyun-Jung Kim
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Learning Emergent Gaits with Decentralized Phase Oscillators: On the Role of Observations, Rewards, and Feedback
Jenny Zhang, Steve Heim, Se Hwan Jeon, Sangbae Kim
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Pedestrian Trajectory Prediction Using Dynamics-Based Deep Learning
Honghui Wang, Weiming Zhi, Gustavo Batista, Rohitash Chandra
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Learning to Predict Navigational Patterns from Partial Observations
Robin Karlsson, Alexander Carballo, Francisco Lepe-Salazar, Keisuke Fujii, Kento Ohtani, Kazuya Takeda
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The Treachery of Images: Bayesian Scene Keypoints for Deep Policy Learning in Robotic Manipulation
Jan Ole von Hartz, Eugenio Chisari, Tim Welschehold, Wolfram Burgard, Joschka Boedecker, Abhinav Valada
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Active Learning of Discrete-Time Dynamics for Uncertainty-Aware Model Predictive Control
Alessandro Saviolo, Jonathan Frey, Abhishek Rathod, Moritz Diehl, Giuseppe Loianno
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