机器人 / 具身智能

Active Inference and Behavior Trees for Reactive Action Planning and Execution in Robotics

Corrado Pezzato, Carlos Hernandez Corbato, Stefan Bonhof, Martijn Wisse

专题命中 机器人操作 ：robotics(title,comments)；robotic(abstract)；分类 cs.RO、cs.AI

Comments Accepted at Transactions on Robotics (IEEE T-RO)

Reaching Through Latent Space: From Joint Statistics to Path Planning in Manipulation

Chia-Man Hung, Shaohong Zhong, Walter Goodwin, Oiwi Parker Jones, Martin Engelcke, Ioannis Havoutis, Ingmar Posner

专题命中 机器人操作 ：manipulation(title)；robotic(abstract)；分类 cs.RO、cs.LG；robotics(journal_ref)

Comments 10 pages, 6 figures, 4 tables

Journal ref IEEE Robotics and Automation Letters 7.2 (2022): 5334-5341

Uncertainty Guided Policy for Active Robotic 3D Reconstruction using Neural Radiance Fields

Soomin Lee, Le Chen, Jiahao Wang, Alexander Liniger, Suryansh Kumar, Fisher Yu

专题命中 机器人操作 ：robotic(title,abstract)；分类 cs.RO、cs.CV；robotics(comments)

Comments 8 pages, 9 figure; Accepted for publication at IEEE Robotics and Automation Letters (RA-L) 2022

DiffSRL: Learning Dynamical State Representation for Deformable Object Manipulation with Differentiable Simulator

Sirui Chen, Yunhao Liu, Jialong Li, Shang Wen Yao, Tingxiang Fan, Jia Pan

专题命中 机器人操作 ：manipulation(title)；robot learning(abstract)；分类 cs.RO、cs.AI；robotics(journal_ref)

Comments 8 pages 9 figures

Journal ref IEEE Robotics and Automation Letters, 2022

Robot Cooking with Stir-fry: Bimanual Non-prehensile Manipulation of Semi-fluid Objects

Junjia Liu, Yiting Chen, Zhipeng Dong, Shixiong Wang, Sylvain Calinon, Miao Li, Fei Chen

专题命中 机器人操作 ：manipulation(title,abstract)；分类 cs.RO、cs.AI；robotics(journal_ref)

Comments 8 pages, 8 figures, published to RA-L

Journal ref IEEE Robotics and Automation Letters, vol. 7, no. 2, pp. 5159-5166, April 2022

Manipulation of Granular Materials by Learning Particle Interactions

Neea Tuomainen, David Blanco-Mulero, Ville Kyrki

专题命中 机器人操作 ：manipulation(title,abstract)；分类 cs.RO、cs.LG；robotics(comments)

Comments 8 pages, 5 figures. Accepted to IEEE Robotics and Automation Letters (RA-L)

Benchmarking Robot Manipulation with the Rubik's Cube

Boling Yang, Patrick E. Lancaster, Siddhartha S. Srinivasa, Joshua R. Smith

专题命中 机器人操作 ：manipulation(title,abstract)；分类 cs.RO、cs.AI；robotics(journal_ref)

Comments IEEE RAL

Journal ref IEEE Robotics and Automation Letters 5.2 (2020): 2094-2099

Deformable One-Dimensional Object Detection for Routing and Manipulation

Azarakhsh Keipour, Maryam Bandari, Stefan Schaal

专题命中 机器人操作 ：manipulation(title,abstract)；分类 cs.RO、cs.CV；robotics(comments)

Comments Accepted to IEEE Robotics and Automation Letters, January 2022. 8 pages

Beyond Pick-and-Place: Tackling Robotic Stacking of Diverse Shapes

Alex X. Lee, Coline Devin, Yuxiang Zhou, Thomas Lampe, Konstantinos Bousmalis, Jost Tobias Springenberg, Arunkumar Byravan, Abbas Abdolmaleki, Nimrod Gileadi, David Khosid, Claudio Fantacci, Jose Enrique Chen, Akhil Raju, Rae Jeong, Michael Neunert, Antoine Laurens, Stefano Saliceti, Federico Casarini, Martin Riedmiller, Raia Hadsell, Francesco Nori

专题命中 机器人操作 ：robotic(title,abstract)；分类 cs.RO、cs.LG；robotics(comments)

Comments CoRL 2021. Video: https://dpmd.ai/robotics-stacking-YT . Blog: https://dpmd.ai/robotics-stacking . Code: https://github.com/deepmind/rgb_stacking

Goal-Auxiliary Actor-Critic for 6D Robotic Grasping with Point Clouds

Lirui Wang, Yu Xiang, Wei Yang, Arsalan Mousavian, Dieter Fox

专题命中 机器人操作 ：robotic(title,abstract)；分类 cs.RO、cs.CV；robot learning(journal_ref)

Journal ref The Conference on Robot Learning (CoRL 2021)

DeformerNet: A Deep Learning Approach to 3D Deformable Object Manipulation

Bao Thach, Alan Kuntz, Tucker Hermans

专题命中 机器人操作 ：manipulation(title,abstract)；分类 cs.RO、cs.AI；robotics(comments)

Comments Published at RSS 2021 Workshop on Deformable Object Simulation in Robotics; received Honorable Mention for Best Paper Award

Vision-based Robotic Grasping From Object Localization, Object Pose Estimation to Grasp Estimation for Parallel Grippers: A Review

Guoguang Du, Kai Wang, Shiguo Lian, Kaiyong Zhao

专题命中 机器人操作 ：robotic(title,abstract)；分类 cs.RO、cs.CV

Comments This is a pre-print of an article published in Artificial Intelligence Review. The final authenticated version is available online at: https://doi.org/10.1007/s10462-020-09888-5. Related refs are summarized at: https://github.com/GeorgeDu/vision-based-robotic-grasping

UniGrasp: Learning a Unified Model to Grasp with Multifingered Robotic Hands

Lin Shao, Fabio Ferreira, Mikael Jorda, Varun Nambiar, Jianlan Luo, Eugen Solowjow, Juan Aparicio Ojea, Oussama Khatib, Jeannette Bohg

专题命中 机器人操作 ：robotic(title,abstract)；分类 cs.RO、cs.AI；robotics(comments)

Comments Accepted to IEEE Robotics and Automation Letters with ICRA 2020 option

A Motion Taxonomy for Manipulation Embedding

David Paulius, Nicholas Eales, Yu Sun

专题命中 机器人操作 ：manipulation(title,abstract)；分类 cs.RO、cs.LG；robotics(journal_ref)

Comments RSS 2020 Submission -- Corrected Several Errors in Paper (last updated July 13th, 2020)

Journal ref Proceedings of Robotics: Science and Systems 2020

Quantile QT-Opt for Risk-Aware Vision-Based Robotic Grasping

Cristian Bodnar, Adrian Li, Karol Hausman, Peter Pastor, Mrinal Kalakrishnan

专题命中 机器人操作 ：robotic(title,abstract)；分类 cs.RO、cs.LG；robotics(journal_ref)

Comments Camera-ready version for RSS 2020. Contains 8 pages, 7 figures

Journal ref Proceedings of Robotics: Science and Systems (2020)

Visual-Inertial Telepresence for Aerial Manipulation

Jongseok Lee, Ribin Balachandran, Yuri S. Sarkisov, Marco De Stefano, Andre Coelho, Kashmira Shinde, Min Jun Kim, Rudolph Triebel, Konstantin Kondak

专题命中 机器人操作 ：manipulation(title,abstract)；分类 cs.RO、cs.CV；robotics(comments)

Comments Accepted to International Conference on Robotics and Automation (ICRA) 2020, IEEE copyright, 8 pages, 10 figures

6-DOF Grasping for Target-driven Object Manipulation in Clutter

Adithyavairavan Murali, Arsalan Mousavian, Clemens Eppner, Chris Paxton, Dieter Fox

专题命中 机器人操作 ：manipulation(title)；robotic(abstract)；分类 cs.RO、cs.CV；robotics(comments)

Comments Accepted to the International Conference on Robotics and Automation (ICRA) 2020

A Lobster-inspired Robotic Glove for Hand Rehabilitation

Yaohui Chen, Sing Le, Qiao Chu Tan, Oscar Lau, Fang Wan, Chaoyang Song

专题命中 机器人操作 ：robotic(title)；robotics(abstract,journal_ref)；分类 cs.RO、cs.LG

Comments 6 pages, 8 figures, accepted for IEEE ICRA 2017

Journal ref 2017 IEEE International Conference on Robotics and Automation (ICRA)

A Mobile Manipulation System for One-Shot Teaching of Complex Tasks in Homes

Max Bajracharya, James Borders, Dan Helmick, Thomas Kollar, Michael Laskey, John Leichty, Jeremy Ma, Umashankar Nagarajan, Akiyoshi Ochiai, Josh Petersen, Krishna Shankar, Kevin Stone, Yutaka Takaoka

专题命中 机器人操作 ：manipulation(title,abstract)；分类 cs.RO、cs.CV；robotics(comments)

Comments The video is available at: https://youtu.be/HSyAGMGikLk. 7 pages, 5 figures, accepted by IEEE 2020 Robotics International Conference on Robotics and Automation (ICRA)

Joint Learning of Instance and Semantic Segmentation for Robotic Pick-and-Place with Heavy Occlusions in Clutter

Kentaro Wada, Kei Okada, Masayuki Inaba

专题命中 机器人操作 ：robotic(title,abstract)；分类 cs.RO、cs.CV；robotics(comments)

Comments 7 pages, 13 figures, IEEE International Conference on Robotics and Automation (ICRA) 2019

ROBEL: Robotics Benchmarks for Learning with Low-Cost Robots

Michael Ahn, Henry Zhu, Kristian Hartikainen, Hugo Ponte, Abhishek Gupta, Sergey Levine, Vikash Kumar

专题命中 机器人操作 ：robotics(title)；manipulation(abstract)；分类 cs.RO、cs.LG；robot learning(journal_ref)

Comments Published @ CoRL2019. For details visit - http://www.roboticsbenchmarks.org

Journal ref Conference on Robot Learning, 2019

kPAM-SC: Generalizable Manipulation Planning using KeyPoint Affordance and Shape Completion

Wei Gao, Russ Tedrake

专题命中 机器人操作 ：manipulation(title,abstract)；分类 cs.RO、cs.CV

Comments In submission. The video demo and source code are available on https://sites.google.com/view/generalizable-manipulation/

GarmNet: Improving Global with Local Perception for Robotic Laundry Folding

Daniel Fernandes Gomes, Shan Luo, Luis F. Teixeira

专题命中 机器人操作 ：robotic(title,comments)；robotics(abstract)；分类 cs.RO、cs.CV

Comments 13 pages, 5 figures, published in the 20th Towards Autonomous Robotic Systems Conference

Learning Probabilistic Multi-Modal Actor Models for Vision-Based Robotic Grasping

Mengyuan Yan, Adrian Li, Mrinal Kalakrishnan, Peter Pastor

专题命中 机器人操作 ：robotic(title,abstract)；分类 cs.RO、cs.LG；robotics(journal_ref)

Journal ref The 2019 International Conference on Robotics and Automation (ICRA)

Learning Robust Manipulation Skills with Guided Policy Search via Generative Motor Reflexes

Philipp Ennen, Pia Bresenitz, Rene Vossen, Frank Hees

专题命中 机器人操作 ：manipulation(title,abstract)；分类 cs.RO、cs.AI；robotics(comments)

Comments IEEE International Conference on Robotics and Automation (ICRA) 2019

Learning a visuomotor controller for real world robotic grasping using simulated depth images

Ulrich Viereck, Andreas ten Pas, Kate Saenko, Robert Platt

专题命中 机器人操作 ：robotic(title,abstract)；分类 cs.RO、cs.AI；robot learning(comments)

Comments 1st Conference on Robot Learning (CoRL), 13-15 November 2017, Mountain View, CA

MorphIt: Flexible Spherical Approximation of Robot Morphology for Representation-driven Adaptation

MorphIt：面向表征驱动适应的机器人形态的灵活球形近似

Nataliya Nechyporenko, Yutong Zhang, Sean Campbell, Alessandro Roncone

机构 * Human Interaction and RObotics [HIRO] Group（人机交互与机器人[HIRO]组） ； Department of Computer Science（计算机科学系） ； College of Engineering and Applied Science（工程与应用科学学院） ； University of Colorado Boulder（科罗拉多大学波尔得分校） 纠错

专题命中 机器人操作 ：robotics(abstract)；manipulation(abstract)；navigation(abstract)；robotic(abstract)

AI总结 MorphIt是一种新型球形近似框架，可将机器人形态表征作为可调资源，通过梯度优化实现任务驱动型形态适应，速度比同类方法快达100倍，能提升机器人碰撞检测等能力，为机器人操作开辟新前沿。

GIRAF: Towards Generalizable Human Interactions with Articulated Objects

GIRAF：迈向与关节物体的可泛化人类交互

Xiaohan Zhang, Sebastian Starke, Alexander Winkler, Federica Bogo, Samir Aroudj, Yuting Ye

机构 * Meta 纠错

专题命中 机器人操作 ：robotics(abstract)；embodied AI(abstract)；manipulation(abstract)；navigation(abstract)

AI总结 针对合成与关节物体的逼真全身人类交互难题，现有模型有局限。本文提出文本条件扩散模型，通过以物体为中心的表示、混合域训练策略和基于接触的增强方案应对挑战，实验证明其对未见物体配置泛化能力强，超越现有方法。

Comments 12 pages, 6 figures, 3 tables. Accepted at the Third Workshop on Human Motion Generation (HuMoGen), CVPR 2026

RMPflow: A Computational Graph for Automatic Motion Policy Generation

RMPflow：一种用于自动运动策略生成的计算图

Ching-An Cheng, Mustafa Mukadam, Jan Issac, Stan Birchfield, Dieter Fox, Byron Boots, Nathan Ratliff

机构 * NVIDIA, Seattle Robotics Lab（NVIDIA西雅图机器人实验室） ； Georgia Institute of Technology, Robot Learning Lab（佐治亚理工学院机器人学习实验室） ； University of Washington, Robotics and State Estimation Lab（华盛顿大学机器人与状态估计实验室） 纠错

专题命中 机器人操作 ：manipulation(summary_cn,abstract)；分类 cs.RO

AI总结 本文提出了一种基于Riemannian Motion Policies几何一致变换的新型策略合成算法RMPflow，通过结合局部策略生成全局策略并利用稀疏结构提高计算效率，同时研究了其几何性质并验证了在高自由度 manipulation 系统中通过障碍物规划的简化效果。

Comments WAFR 2018

On the Generalization Capabilities, Design Choices and Limitations of Keypoint Imitation Learning

关键点模仿学习的泛化能力、设计选择与局限性

Thomas Lips, Marco Moletta, Michael C. Welle, Danica Kragic, Francis wyffels

机构 * AI and Robotics Lab, IDLAB-AIRO, Ghent University-imec（人工智能与机器人实验室，IDLAB-AIRO，根特大学-imec） ； Robotics, Perception and Learning Lab, (RPL), EECS, KTH Royal Institute of Technology（机器人、感知与学习实验室，（RPL），EECS，皇家理工学院） ； INCAR Robotics AB, Stockholm, Sweden（INCAR机器人公司，斯德哥尔摩，瑞典） 纠错

专题命中 机器人操作 ：manipulation(abstract,abstract_cn)；robot learning(abstract)；robotic(abstract)；分类 cs.RO

AI总结 本文通过2000多次真实世界实验，系统评估了基于视觉基础模型的关键点模仿学习在机器人操作中的泛化能力、设计选择及局限性，发现其总体成功率达75%，显著优于RGB基线（47%），与S2扩散模型（73%）相当，但未超越其他表示方法且继承了基础模型的局限。

Comments This version was submitted to IROS 2026