机器人 / 具身智能

ST-MTL: Spatio-Temporal Multitask Learning Model to Predict Scanpath While Tracking Instruments in Robotic Surgery

Mobarakol Islam, Vibashan VS, Chwee Ming Lim, Hongliang Ren

专题命中 机器人数据与评测 ：robotic(title,abstract)；分类 cs.RO、cs.CV

Comments 12 pages

Continuous Perception for Classifying Shapes and Weights of Garmentsfor Robotic Vision Applications

Li Duan, Gerardo Aragon-Camarasa

专题命中 机器人数据与评测 ：robotic(title,abstract)；分类 cs.RO、cs.CV

Comments Accepted by the 17th International Conference on Computer Vision Theory and Applications

Unseen Object Instance Segmentation for Robotic Environments

Christopher Xie, Yu Xiang, Arsalan Mousavian, Dieter Fox

专题命中 机器人数据与评测 ：robotic(title,abstract)；分类 cs.RO、cs.CV

Comments Journal version of arXiv:1907.13236

Isaac Gym: High Performance GPU-Based Physics Simulation For Robot Learning

Viktor Makoviychuk, Lukasz Wawrzyniak, Yunrong Guo, Michelle Lu, Kier Storey, Miles Macklin, David Hoeller, Nikita Rudin, Arthur Allshire, Ankur Handa, Gavriel State

专题命中 机器人数据与评测 ：robot learning(title)；robotics(abstract)；分类 cs.RO、cs.LG

Comments tech report on isaac-gym

Sim-to-Real Transfer in Deep Reinforcement Learning for Robotics: a Survey

Wenshuai Zhao, Jorge Peña Queralta, Tomi Westerlund

专题命中 机器人数据与评测 ：robotics(title,abstract)；分类 cs.RO、cs.LG

Comments Accepted to the 2020 IEEE Symposium Series on Computational Intelligence

Journal ref 2020 IEEE Symposium Series on Computational Intelligence (SSCI), 2020, pp. 737-744

Neuroscience-inspired perception-action in robotics: applying active inference for state estimation, control and self-perception

Pablo Lanillos, Marcel van Gerven

专题命中 机器人数据与评测 ：robotics(title,abstract)；分类 cs.RO、cs.AI

Comments Accepted at ICLR 2021 Brain2AI workshop

Dataset and Performance Comparison of Deep Learning Architectures for Plum Detection and Robotic Harvesting

Jasper Brown, Salah Sukkarieh

专题命中 机器人数据与评测 ：robotic(title,abstract)；分类 cs.RO、cs.CV

Comments 20 pages, 8 figures, 2 tables. Associated dataset at http://data.acfr.usyd.edu.au/Agriculture/PlumDetection/

Robotic needle steering in deformable tissues with extreme learning machines

Pedro Henrique Suruagy Perrusi, Anna Cazzaniga, Paul Baksic, Eleonora Tagliabue, Elena de Momi, Hadrien Courtecuisse

专题命中 机器人数据与评测 ：robotic(title,abstract)；分类 cs.RO、cs.AI

Journal ref AUTOMED 2021, Jun 2021, Basel, Switzerland

Visual Perception Generalization for Vision-and-Language Navigation via Meta-Learning

Ting Wang, Zongkai Wu, Donglin Wang

专题命中 机器人数据与评测 ：navigation(title,abstract)；分类 cs.RO、cs.AI

Comments 8 pages, 4 figures, preprinted version

A comparative evaluation of machine learning methods for robot navigation through human crowds

Anastasia Gaydashenko, Daniel Kudenko, Aleksei Shpilman

专题命中 机器人数据与评测 ：navigation(title,abstract)；分类 cs.RO、cs.LG

Integrated Benchmarking and Design for Reproducible and Accessible Evaluation of Robotic Agents

Jacopo Tani, Andrea F. Daniele, Gianmarco Bernasconi, Amaury Camus, Aleksandar Petrov, Anthony Courchesne, Bhairav Mehta, Rohit Suri, Tomasz Zaluska, Matthew R. Walter, Emilio Frazzoli, Liam Paull, Andrea Censi

专题命中 机器人数据与评测 ：robotic(title)；robotics(abstract)；分类 cs.RO、cs.LG

Comments IROS 2020; Code available at https://github.com/duckietown

2018 Robotic Scene Segmentation Challenge

Max Allan, Satoshi Kondo, Sebastian Bodenstedt, Stefan Leger, Rahim Kadkhodamohammadi, Imanol Luengo, Felix Fuentes, Evangello Flouty, Ahmed Mohammed, Marius Pedersen, Avinash Kori, Varghese Alex, Ganapathy Krishnamurthi, David Rauber, Robert Mendel, Christoph Palm, Sophia Bano, Guinther Saibro, Chi-Sheng Shih, Hsun-An Chiang, Juntang Zhuang, Junlin Yang, Vladimir Iglovikov, Anton Dobrenkii, Madhu Reddiboina, Anubhav Reddy, Xingtong Liu, Cong Gao, Mathias Unberath, Myeonghyeon Kim, Chanho Kim, Chaewon Kim, Hyejin Kim, Gyeongmin Lee, Ihsan Ullah, Miguel Luna, Sang Hyun Park, Mahdi Azizian, Danail Stoyanov, Lena Maier-Hein, Stefanie Speidel

专题命中 机器人数据与评测 ：robotic(title,abstract)；分类 cs.RO、cs.CV

Decentralized Dynamic Task Allocation in Swarm Robotic Systems for Disaster Response

Payam Ghassemi, David DePauw, Souma Chowdhury

专题命中 机器人数据与评测 ：robotic(title,abstract)；分类 cs.RO、cs.AI

Comments Accepted for poster presentation in (and publication as extended abstract in the proceedings of) The IEEE 2019 International Symposium on Multi-Robot and Multi-Agent Systems (MRS)

RoboTHOR: An Open Simulation-to-Real Embodied AI Platform

Matt Deitke, Winson Han, Alvaro Herrasti, Aniruddha Kembhavi, Eric Kolve, Roozbeh Mottaghi, Jordi Salvador, Dustin Schwenk, Eli VanderBilt, Matthew Wallingford, Luca Weihs, Mark Yatskar, Ali Farhadi

专题命中 机器人数据与评测 ：embodied AI(title,abstract)；分类 cs.RO、cs.CV

Comments CVPR 2020

Leveraging Vision and Kinematics Data to Improve Realism of Biomechanic Soft-tissue Simulation for Robotic Surgery

Jie Ying Wu, Peter Kazanzides, Mathias Unberath

专题命中 机器人数据与评测 ：robotic(title,abstract)；分类 cs.RO、cs.CV

Comments 12 pages, 4 figures, to be published in IJCARS IPCAI special edition 2020

Rethinking Temporal Object Detection from Robotic Perspectives

Xingyu Chen, Zhengxing Wu, Junzhi Yu, Li Wen

专题命中 机器人数据与评测 ：robotic(title,abstract)；分类 cs.RO、cs.CV

Scalable and Probabilistically Complete Planning for Robotic Spatial Extrusion

Caelan Reed Garrett, Yijiang Huang, Tomás Lozano-Pérez, Caitlin Tobin Mueller

专题命中 机器人数据与评测 ：robotic(title,abstract)；分类 cs.RO、cs.AI

Augmented Reality for Human-Swarm Interaction in a Swarm-Robotic Chemistry Simulation

Sumeet Batra, John Klingner, Nikolaus Correll

专题命中 机器人数据与评测 ：robotic(title,abstract)；分类 cs.RO、cs.CV

Sim-to-Real Robot Learning from Pixels with Progressive Nets

Andrei A. Rusu, Mel Vecerik, Thomas Rothörl, Nicolas Heess, Razvan Pascanu, Raia Hadsell

专题命中 机器人数据与评测 ：robot learning(title)；manipulation(abstract)；分类 cs.RO、cs.LG

Roborobo! a Fast Robot Simulator for Swarm and Collective Robotics

Nicolas Bredeche, Jean-Marc Montanier, Berend Weel, Evert Haasdijk

专题命中 机器人数据与评测 ：robotics(title,abstract)；分类 cs.RO、cs.AI

Comments 2 pages, 1 figure

A Generalized Theory of Load Distribution in Redundantly-actuated Robotic Systems

冗余驱动机器人系统中载荷分布的通用理论

Joshua Flight, Clément Gosselin

专题命中 机器人数据与评测 ：robotic(title,abstract)；分类 cs.RO；robotics(comments)

AI总结 本文提出冗余驱动机器人系统中载荷分布的通用理论，推导了高效力合成与分析解，并指出现有方法的不足，通过示例展示改进效果。

Comments 23 pages, 15 figures. Submitted to The International Journal of Robotics Research

Robust Silicone Pour Casting and Sensor Embedding Procedures for Soft Robotic Actuators

用于软机器人致动器的稳健硅胶浇注成型和传感器嵌入程序

Harshit Thakker, Paul Dela Cruz, Mostafa Mo. Massoud, Jacqueline Libby

专题命中 机器人数据与评测 ：robotic(title)；robotics(abstract,comments)；分类 cs.RO

AI总结 研究软机器人可重复可扩展制造问题，核心方法是双组分浇注成型制造软气动致动器及嵌入薄膜柔性传感器，并进行有限元建模和多种实验验证，主要贡献是提供稳健制造程序及相关验证，推动软机器人广泛应用。

Comments 8 pages, 17 figures, to be published in: IEEE RAS/EMBS 11th International Conference on Biomedical Robotics and Biomechatronics (BioRob 2026)

Beyond Failure Recovery: An Engagement-Aware Human-in-the-loop Framework for Robotic Systems

超越故障恢复：一种面向机器人系统的参与感知人在回路框架

Jiaying Fang, Joyce Yang, Zhanxin Wu, Bohan Yang, Tapomayukh Bhattacharjee

机构 * Cornell University（康奈尔大学） 纠错

专题命中 机器人数据与评测 ：robotic(title)；robotics(abstract,journal_ref)；分类 cs.RO

AI总结 提出一种参与感知模型预测控制（E-MPC）方法，通过规划交互频率和类型来维持用户参与度并控制工作负荷，在机器人辅助进食系统中验证了其提升用户体验且不降低任务成功率的效果。

Comments Project website at https://emprise.cs.cornell.edu/empc

Journal ref Robotics: Science and Systems 2026

D-CLING: Prior-Preserving Depth-Conditioned Fine-Tuning for Navigation Foundation Models

D-CLING: 保留先验知识的深度条件细调方法用于导航基础模型

Shintaro Nakaoka, Takayuki Kanai, Kazuhito Tanaka

机构 * Frontier Research Center, Toyota Motor Corporation（丰田电机公司前沿研究中心） 纠错

专题命中 机器人数据与评测 ：navigation(title,abstract)；分类 cs.RO；robotics(comments)

AI总结 本文提出了一种新的细调方法，通过利用大规模预训练同时高效学习新环境或相机配置等新设置，从而在保留预训练知识的同时提升导航模型的鲁棒性和准确性。

Comments This paper has been accepted to the 2026 IEEE International Conference on Robotics and Automation (ICRA 2026), which will be held in Vienna, Austria, from June 1 to 5, 2026

A Bayesian Reasoning Framework for Robotic Systems in Autonomous Casualty Triage

一种用于自主急救分级的贝叶斯推理框架

Szymon Rusiecki, Cecilia Morales, Pia Störy, Kimberly Elenberg, Leonard Weiss, Artur Dubrawski

机构 * AGH University of Krakow（克拉科夫AGH大学） ； Carnegie Mellon University（卡内基梅隆大学） ； Osnabrück University（奥斯纳布吕克大学） ； University of Pittsburgh（匹兹堡大学） 纠错

专题命中 机器人数据与评测 ：robotic(title,abstract)；分类 cs.RO；robotics(comments)

AI总结 本文提出一种融合多视觉算法的自主机器人系统，利用贝叶斯网络提升急救分级准确性，实验显示其在生理评估和整体分级准确率上显著提升。

Comments Accepted to the 2026 IEEE International Conference on Robotics and Automation (ICRA)

RoboBPP: Benchmarking Robotic Online Bin Packing with Physics-based Simulation

RoboBPP：基于物理模拟的机器人在线装箱基准测试

Zhoufeng Wang, Hang Zhao, Juzhan Xu, Shishun Zhang, Ruizhen Hu, Chenyang Zhu, Zecui Zeng, Weiyan Zhu, Zeyu Xiong, Haibin Yu, Kai Xu

机构 * National University of Defense Technology（国防科技大学） ； Institute of AI for Industries, Chinese Academy of Sciences（中国科学院人工智能产业研究院） ； Wuhan University（武汉大学） ； Shenzhen University（深圳大学） ； JD Explore Academy（京东探索研究院） ； China Post Technology Company（中国邮政技术公司） 纠错

专题命中 机器人数据与评测 ：robotic(title,abstract)；分类 cs.RO；robotics(comments)

AI总结 本文提出RoboBPP基准系统，通过物理模拟和真实工业数据集，解决在线装箱中评估标准不统一的问题，提供结构稳定性与操作安全性等新指标。

Comments Under review at the International Journal of Robotics Research (IJRR)

Rusty Flying Robots: Learning a Full Robotics Stack with Real-Time Operation on an STM32 Microcontroller in a 9 ECTS MS Course

锈迹斑斑的飞行机器人：在9 ECTS硕士课程中利用STM32微控制器实时操作学习完整的机器人系统

Wolfgang Hoenig, Christoph Scherer, Khaled Wahba

机构 * Technical University Berlin（柏林工业大学） ； Robotics Institute Germany (RIG)（德国机器人研究所（RIG）） 纠错

专题命中 机器人数据与评测 ：robotics(title,abstract)；分类 cs.RO

AI总结 本课程通过在高度受限的STM32微控制器上实时操作，让学生学习完整的机器人系统，强调非线性算法的应用和Rust语言的使用，提升实际操作能力。

Comments Accepted at the International Conference on Robotics in Education (RiE), 2026

Data Scaling for Navigation in Unknown Environments

未知环境中的导航数据扩展

Lauri Suomela, Naoki Takahata, Sasanka Kuruppu Arachchige, Harry Edelman, Joni-Kristian Kämäräinen

机构 * Signal Processing Research Centre, Faculty of Information Technology and Communication Sciences, Tampere University（信号处理研究中心，信息科技与通信科学学院，塔尔皮奥大学） ； Graduate School of Information Sciences, Tohoku University（信息科学研究生院，东北大学） ； Faculty of Engineering, Turku University of Applied Sciences（工程学院，图尔库应用科学大学） 纠错

专题命中 机器人数据与评测 ：navigation(title,abstract)；分类 cs.RO；robotics(comments)

AI总结 研究通过大规模数据和多样性提升未知环境导航性能，发现数据多样性比数量更重要，且简单回归模型在嘈杂数据中表现更优。

Comments Robotics and Automation Letters (RA-L) 2026

SurgSync: Time-Synchronized Multi-Modal Data Collection Framework and Dataset for Surgical Robotics

SurgSync: 用于手术机器人的时间同步多模态数据采集框架和数据集

Haoying Zhou, Chang Liu, Yimeng Wu, Junlin Wu, Zijian Wu, Yu Chung Lee, Sara Martuscelli, Spetimiu E. Salcudean, Gregory S. Fischer, Peter Kazanzides

机构 * Department of Robotics Engineering, Worcester Polytechnic Institute（机器人工程系，沃斯特理工学院） ； Laboratory for Computational Sensing and Robotics（计算感知与机器人实验室） ； Department of Computer Science, Johns Hopkins University（计算机科学系，约翰霍普金斯大学） ； Robotics and Control Laboratory, the University of British Columbia（机器人与控制实验室，不列颠哥伦比亚大学） ； Department of Electronics, Information and Bioengineering, Politecnico di Milano（电子、信息与生物工程系，米兰理工学院） 纠错

专题命中 机器人数据与评测 ：robotics(title,comments)；robotic(abstract)；分类 cs.RO

AI总结 SurgSync提出了一种时间同步的多模态数据采集框架和数据集，用于手术机器人中的高阶控制与训练，通过多传感器和后处理工具提升数据质量与实用性。

Comments Accepted By International Conference on Robotics and Automation (ICRA), IEEE, 2026. More details can be found at https://surgsync.github.io/

Learning with pyCub: A Simulation and Exercise Framework for Humanoid Robotics

通过pyCub学习：人形机器人的仿真与练习框架

Lukas Rustler, Matej Hoffmann

机构 * Department of Cybernetics, Faculty of Electrical Engineering, Czech Technical University in Prague（控制系，电气工程学院，布拉格捷克技术大学） 纠错

专题命中 机器人数据与评测 ：robotics(title,abstract)；分类 cs.RO

AI总结 pyCub是一个基于Python的人形机器人仿真与练习框架，无需YARP中间件，提供从基础控制到复杂任务的多级练习，适用于编程经验较少的学习者。

Comments Accepted to 17th International Conference on Robotics in Education (RiE 2026)