机器人 / 具身智能 - arXivDaily 专题

1810.00599 2018-10-02 cs.CV 57%

Unsupervised Trajectory Segmentation and Promoting of Multi-Modal Surgical Demonstrations

Zhenzhou Shao, Hongfa Zhao, Jiexin Xie, Ying Qu, Yong Guan, Jindong Tan

专题命中机器人学习：robot learning(abstract)；分类 cs.CV

Comments 7 pages, 6 figures

1806.00319 2018-06-04 stat.ML cs.LG math.OC 57%

Learning convex bounds for linear quadratic control policy synthesis

Jack Umenberger, Thomas B. Schön

专题命中机器人学习：robotics(abstract)；分类 cs.LG

1706.06133 2017-12-14 cs.AI 57%

Scalable Co-Optimization of Morphology and Control in Embodied Machines

Nick Cheney, Josh Bongard, Vytas SunSpiral, Hod Lipson

专题命中机器人学习：robotics(abstract)；分类 cs.AI

1711.03179 2017-11-10 cs.CV 57%

Multi-stage Suture Detection for Robot Assisted Anastomosis based on Deep Learning

Yang Hu, Yun Gu, Jie Yang, Guang-Zhong Yang

专题命中机器人学习：robotic(abstract)；分类 cs.CV

Comments Submitted to ICRA 2018

1710.02714 2017-10-10 cs.AI 57%

Interactive Learning of State Representation through Natural Language Instruction and Explanation

Qiaozi Gao, Lanbo She, Joyce Y. Chai

专题命中机器人学习：robot learning(abstract)；分类 cs.AI

1709.03486 2017-09-12 cs.RO 57%

Robot Composite Learning and the Nunchaku Flipping Challenge

Leidi Zhao, Yiwen Zhao, Siddharth Patil, Dylan Davies, Cong Wang, Lu Lu, Bo Ouyang

专题命中机器人学习：robot learning(abstract)；分类 cs.RO

1706.08807 2017-06-28 cs.CV 57%

Recurrent Residual Learning for Action Recognition

Ahsan Iqbal, Alexander Richard, Hilde Kuehne, Juergen Gall

专题命中机器人学习：robot learning(abstract)；分类 cs.CV

1503.06375 2015-05-11 cs.RO 57%

Policy Learning with Hypothesis based Local Action Selection

Bharath Sankaran, Jeannette Bohg, Nathan Ratliff, Stefan Schaal

专题命中机器人学习：manipulation(abstract)；分类 cs.RO

Comments RLDM abstract

1411.1112 2014-11-06 cs.AI cs.MA 57%

Learning of Agent Capability Models with Applications in Multi-agent Planning

Yu Zhang, Subbarao Kambhampati

专题命中机器人学习：robot learning(abstract)；分类 cs.AI

2604.20468 2026-08-28 cs.RO cs.AI cs.CL cs.HC cs.LG 版本更新 56%

MOMO: A framework for seamless physical, verbal, and graphical robot skill learning and adaptation

MOMO：一种无缝物理、语言和图形机器人技能学习与适应框架

Markus Knauer, Edoardo Fiorini, Maximilian Mühlbauer, Stefan Schneyer, Promwat Angsuratanawech, Florian Samuel Lay, Timo Bachmann, Samuel Bustamante, Korbinian Nottensteiner, Freek Stulp, Alin Albu-Schäffer, João Silvério, Thomas Eiband

机构 * German Aerospace Center (DLR), Institute of Robotics and Mechatronics (RMC)（德国航空航天中心（DLR）机器人与机电研究所）； School of Computation, Information and Technology (CIT), Technical University of Munich (TUM)（计算、信息与技术学院（CIT），慕尼黑技术大学）

专题命中机器人学习：分类 cs.RO、cs.AI、cs.LG；robotics(journal_ref)

AI总结本文提出MOMO框架，通过三种互补交互方式实现机器人技能的灵活适应，结合触觉、自然语言和图形界面，提升非专家用户在工业环境中的应用能力。

Comments Accepted and published at IEEE RA-P, 15 pages, 13 figures, 3 tables

Journal ref IEEE Robotics and Automation Practice (RA-P), 2026, ISSN: 2995-4304, Page(s): 1 - 6

1812.07084 2026-06-04 cs.RO cs.AI cs.LG cs.SY eess.SY 56%

Learning Constraints from Demonstrations

从示范中学习约束

Glen Chou, Dmitry Berenson, Necmiye Ozay

机构 * Dept. of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, MI, 48109, USA（电气工程与计算机科学系，密歇根大学，安娜堡，MI，48109，美国）

专题命中机器人学习：分类 cs.RO、cs.AI、cs.LG；robotics(comments)

AI总结该研究提出了一种从示范中学习未知约束的方法，通过任务示范、成本函数和系统动力学与控制约束，利用hit-and-run采样获取低成本但不安全的轨迹，并通过整数规划获得一致的不安全集表示，同时理论分析了可从安全示范中学习的约束子集。

Comments Presented at the Workshop on the Algorithmic Foundations of Robotics (WAFR), 2018, Mérida, Mexico

2509.09074 2025-11-13 cs.RO cs.AI cs.LG 56%

KoopMotion: Learning Almost Divergence Free Koopman Flow Fields for Motion Planning

Alice Kate Li, Thales C Silva, Victoria Edwards, Vijay Kumar, M. Ani Hsieh

机构 * GRASP Laboratory University of Pennsylvania（GRASP实验室大学）

专题命中机器人学习：分类 cs.RO、cs.AI、cs.LG；robot learning(comments)

Comments Revised with link to code. Accepted to CoRL 2025 (Conference on Robot Learning). 15 pages 11 figures

2508.01131 2025-09-09 cs.RO cs.AI cs.LG 56%

COLLAGE: Adaptive Fusion-based Retrieval for Augmented Policy Learning

Sateesh Kumar, Shivin Dass, Georgios Pavlakos, Roberto Martín-Martín

机构 * The University of Texas at Austin（德克萨斯大学奥斯汀分校）

专题命中机器人学习：分类 cs.RO、cs.AI、cs.LG；robot learning(comments)

Comments Accepted at the Conference on Robot Learning (CoRL), 2025. Project page: https://robin-lab.cs.utexas.edu/COLLAGE

2503.04679 2025-03-07 cs.MA cs.AI cs.LG cs.RO 56%

Multi-Agent Inverse Q-Learning from Demonstrations

Nathaniel Haynam, Adam Khoja, Dhruv Kumar, Vivek Myers, Erdem Bıyık

专题命中机器人学习：分类 cs.RO、cs.AI、cs.LG；robotics(comments)

Comments 8 pages, 4 figures, 2 tables. Published at the International Conference on Robotics and Automation (ICRA) 2025

2206.04632 2024-12-10 cs.RO cs.AI cs.FL cs.LG cs.SY eess.SY 56%

Temporal Logic Imitation: Learning Plan-Satisficing Motion Policies from Demonstrations

Yanwei Wang, Nadia Figueroa, Shen Li, Ankit Shah, Julie Shah

专题命中机器人学习：分类 cs.RO、cs.AI、cs.LG；robot learning(journal_ref)

Comments CoRL 2022 Oral Talk

Journal ref Proceedings of The 6th Conference on Robot Learning (2022) PMLR 205:94-105

2406.10115 2024-10-16 cs.CV cs.LG cs.RO 56%

Shelf-Supervised Cross-Modal Pre-Training for 3D Object Detection

Mehar Khurana, Neehar Peri, James Hays, Deva Ramanan

专题命中机器人学习：分类 cs.RO、cs.CV、cs.LG；robot learning(comments)

Comments The first two authors contributed equally. This work has been accepted to the Conference on Robot Learning (CoRL) 2024

2311.13014 2023-11-23 eess.SY cs.SY 56%

Neural Graph Control Barrier Functions Guided Distributed Collision-avoidance Multi-agent Control

Songyuan Zhang, Kunal Garg, Chuchu Fan

专题命中机器人学习：robotics(abstract)；robot learning(comments)

Comments 20 pages, 10 figures; Accepted by 7th Conference on Robot Learning (CoRL 2023)

2102.07730 2021-02-16 cs.RO cs.AI cs.LG 56%

Learning from Demonstrations using Signal Temporal Logic

Aniruddh G. Puranic, Jyotirmoy V. Deshmukh, Stefanos Nikolaidis

专题命中机器人学习：分类 cs.RO、cs.AI、cs.LG；robot learning(comments)

Comments Published at Conference on Robot Learning (CoRL) 2020

2012.08637 2020-12-17 cs.RO cs.AI cs.LG 56%

Multi-Modal Anomaly Detection for Unstructured and Uncertain Environments

Tianchen Ji, Sri Theja Vuppala, Girish Chowdhary, Katherine Driggs-Campbell

专题命中机器人学习：分类 cs.RO、cs.AI、cs.LG；robot learning(comments)

Comments Conference on Robot Learning (CoRL) 2020

1912.02973 2020-11-20 cs.CV cs.LG cs.RO 56%

SAM: Squeeze-and-Mimic Networks for Conditional Visual Driving Policy Learning

Albert Zhao, Tong He, Yitao Liang, Haibin Huang, Guy Van den Broeck, Stefano Soatto

专题命中机器人学习：分类 cs.RO、cs.CV、cs.LG；robot learning(comments)

Comments Conference on Robot Learning (CoRL) 2020

2011.05289 2020-11-11 cs.CV cs.LG cs.RO 56%

Learning to Communicate and Correct Pose Errors

Nicholas Vadivelu, Mengye Ren, James Tu, Jingkang Wang, Raquel Urtasun

专题命中机器人学习：分类 cs.RO、cs.CV、cs.LG；robot learning(comments)

Comments Conference on Robot Learning (CoRL) 2020. 16 pages, 7 figures

2010.16404 2020-11-10 cs.CV cs.GR cs.LG cs.RO 56%

Unsupervised Monocular Depth Learning in Dynamic Scenes

Hanhan Li, Ariel Gordon, Hang Zhao, Vincent Casser, Anelia Angelova

专题命中机器人学习：分类 cs.RO、cs.CV、cs.LG；robot learning(comments)

Comments Accepted at 4th Conference on Robot Learning (CoRL 2020)

1909.03752 2020-01-20 cs.CV cs.LG cs.RO 56%

Masking by Moving: Learning Distraction-Free Radar Odometry from Pose Information

Dan Barnes, Rob Weston, Ingmar Posner

专题命中机器人学习：分类 cs.RO、cs.CV、cs.LG；robot learning(comments)

Comments Conference on Robot Learning (CoRL), 2019. Video summary: https://youtu.be/eG4Q-j3_6dk

1905.09264 2019-07-24 cs.RO cs.AI cs.LG 56%

Automated shapeshifting for function recovery in damaged robots

Sam Kriegman, Stephanie Walker, Dylan Shah, Michael Levin, Rebecca Kramer-Bottiglio, Josh Bongard

专题命中机器人学习：分类 cs.RO、cs.AI、cs.LG；robotics(journal_ref)

Journal ref Proceedings of Robotics: Science and Systems (2019)

1810.05157 2018-10-29 cs.LG cs.AI cs.HC cs.RO stat.ML 56%

Learning under Misspecified Objective Spaces

Andreea Bobu, Andrea Bajcsy, Jaime F. Fisac, Anca D. Dragan

专题命中机器人学习：分类 cs.RO、cs.AI、cs.LG；robot learning(comments)

Comments Conference on Robot Learning (CoRL) 2018

2310.14196 2025-05-07 cs.RO cs.AI 54%

Learning to Discern: Imitating Heterogeneous Human Demonstrations with Preference and Representation Learning

Sachit Kuhar, Shuo Cheng, Shivang Chopra, Matthew Bronars, Danfei Xu

专题命中机器人学习：robot learning(comments,journal_ref)；分类 cs.RO、cs.AI

Comments To appear at the 7th Annual Conference on Robot Learning (CoRL) 2023

Journal ref Proceedings of the 7th Annual Conference on Robot Learning (CoRL 2023), November 6-9, 2023, Atlanta, Georgia, USA

2204.05909 2022-12-20 cs.RO cs.LG 54%

Learning Performance Graphs from Demonstrations via Task-Based Evaluations

Aniruddh G. Puranic, Jyotirmoy V. Deshmukh, Stefanos Nikolaidis

专题命中机器人学习：robotics(comments,journal_ref)；分类 cs.RO、cs.LG

Comments Published in IEEE Robotics and Automation Letters (RA-L) Vol. 8 Issue 1

Journal ref in IEEE Robotics and Automation Letters, vol. 8, no. 1, pp. 336-343, Jan. 2023

2202.05481 2022-03-03 cs.RO cs.LG cs.SY eess.SY 54%

Concurrent Training of a Control Policy and a State Estimator for Dynamic and Robust Legged Locomotion

Gwanghyeon Ji, Juhyeok Mun, Hyeongjun Kim, Jemin Hwangbo

专题命中机器人学习：robotics(comments,journal_ref)；分类 cs.RO、cs.LG

Comments Accepted for IEEE Robotics and Automation Letters (RA-L) and ICRA 2022

Journal ref IEEE Robotics and Automation Letters (Volume: 7, Issue: 2, April 2022)

1903.00589 2026-06-04 eess.SY cs.SY 50%

Formal Policy Learning from Demonstrations for Reachability Properties

从演示中学习形式策略以满足可达性属性

Hadi Ravanbakhsh, Sriram Sankaranarayanan, Sanjit A. Seshia

专题命中机器人学习：robotic(abstract)

AI总结本文提出了一种从演示中学习结构化闭环策略的方法，用于控制欠驱动机器人系统，以满足如到达目标状态集等形式行为规范。该方法通过策略学习者、演示者和验证器之间的交互，利用反例引导的迭代循环，通过反例更新训练数据并细化策略。

1603.04834 2026-06-04 eess.SY cs.IT cs.SY math.IT math.OC stat.AP 50%

Mobile Beamforming & Spatially Controlled Relay Communications

移动波束成形与空间控制中继通信

Dionysios S. Kalogerias, Athina P. Petropulu

专题命中机器人学习：robotic(abstract)

AI总结本文研究了单源单目标机器人中继网络中的随机运动规划问题，提出了一种两阶段随机规划方法，通过优化中继位置以最大化总波束成形功率的期望倒数，采用随机因果信道状态信息进行决策。

Comments 41st International Conference on Acoustics, Speech & Signal Processing (ICASSP 2016) Presentation Available: http://sigport.org/831

1. 机器人学习 876 篇

Unsupervised Trajectory Segmentation and Promoting of Multi-Modal Surgical Demonstrations

Learning convex bounds for linear quadratic control policy synthesis

Scalable Co-Optimization of Morphology and Control in Embodied Machines

Multi-stage Suture Detection for Robot Assisted Anastomosis based on Deep Learning

Interactive Learning of State Representation through Natural Language Instruction and Explanation

Robot Composite Learning and the Nunchaku Flipping Challenge

Recurrent Residual Learning for Action Recognition

Policy Learning with Hypothesis based Local Action Selection

Learning of Agent Capability Models with Applications in Multi-agent Planning

MOMO: A framework for seamless physical, verbal, and graphical robot skill learning and adaptation

Learning Constraints from Demonstrations

KoopMotion: Learning Almost Divergence Free Koopman Flow Fields for Motion Planning

COLLAGE: Adaptive Fusion-based Retrieval for Augmented Policy Learning

Multi-Agent Inverse Q-Learning from Demonstrations

Temporal Logic Imitation: Learning Plan-Satisficing Motion Policies from Demonstrations

Shelf-Supervised Cross-Modal Pre-Training for 3D Object Detection

Neural Graph Control Barrier Functions Guided Distributed Collision-avoidance Multi-agent Control

Learning from Demonstrations using Signal Temporal Logic

Multi-Modal Anomaly Detection for Unstructured and Uncertain Environments

SAM: Squeeze-and-Mimic Networks for Conditional Visual Driving Policy Learning

Learning to Communicate and Correct Pose Errors

Unsupervised Monocular Depth Learning in Dynamic Scenes

Masking by Moving: Learning Distraction-Free Radar Odometry from Pose Information

Automated shapeshifting for function recovery in damaged robots

Learning under Misspecified Objective Spaces

Learning to Discern: Imitating Heterogeneous Human Demonstrations with Preference and Representation Learning

Learning Performance Graphs from Demonstrations via Task-Based Evaluations

Concurrent Training of a Control Policy and a State Estimator for Dynamic and Robust Legged Locomotion

Formal Policy Learning from Demonstrations for Reachability Properties

Mobile Beamforming & Spatially Controlled Relay Communications