---
title: "ICRA (A*): papers and universities"
description: "ICRA (IEEE International Conference on Robotics and Automation) is rated A* by the CORE Conference Rankings (ICORE2026); OpenAlex lists 5,147 of its papers from 2024–2026 (1,766 in 2024, 1,610 in 2025, 1,771 in 2026). By the countries of the authors' institutions, the most papers come from the United States (1,862), China (1,507) and Germany (438)."
url: https://scholar4ai.com/proceedings/icra
markdown_url: https://scholar4ai.com/proceedings/icra.md
license: CC BY-NC 4.0 (https://creativecommons.org/licenses/by-nc/4.0/)
share_text: "ICRA (IEEE International Conference on Robotics and Automation) is rated A* by the CORE Conference Rankings (ICORE2026); OpenAlex lists 5,147 of its papers from 2024–2026 (1,766 in 2024, 1,610 in 2025, 1,771 in 2026). (as of 2026-11-02)"
data_url: https://scholar4ai.com/data/rankings.json
updated: 2026-11-02T12:20:52+09:00
window: 2026-10-04 to 2026-11-02
source: OpenAlex (CC0)
---

# ICRA: IEEE International Conference on Robotics and Automation — papers and institutions, 2024–2026

Papers of ICRA, IEEE International Conference on Robotics and Automation (CORE rank A*; field: Artificial intelligence, Computer science (general)), 2024–2026: per year, the institutions, countries and topics, and the most-cited papers. Ranks are those of the CORE Conference Rankings, edition ICORE2026 (portal.core.edu.au), applied to every year shown. Papers are the works OpenAlex lists for the conference's proceedings, or for the issues of a conference-linked journal that publishes its papers (such as PACMPL, PVLDB or ACM TOG), by publication year; workshops, companion volumes, posters and Findings are left out. A paper counts once for each institution and country among its authors' affiliations as OpenAlex assigns them; papers without affiliations in OpenAlex count for none. For conferences published in book series that OpenAlex files as one source (LNCS, LIPIcs, SIAM and IOS Press proceedings), the papers are found by DOI: those of the volumes with the conference's title in Crossref, or LIPIcs DOIs, which name the conference. Conferences without DOIs (PMLR, USENIX, OpenReview) are listed without counts. A dash (–) for a year means OpenAlex has no papers of the conference for it yet: the proceedings are not published or indexed yet, or the conference did not meet that year (some meet every other year). 2026 counts what OpenAlex had indexed by 2026-11-02.

All conferences: https://scholar4ai.com/proceedings.md

## Key findings

- ICRA (IEEE International Conference on Robotics and Automation) is rated A* by the CORE Conference Rankings (ICORE2026); OpenAlex lists 5,147 of its papers from 2024–2026 (1,766 in 2024, 1,610 in 2025, 1,771 in 2026).
- By the countries of the authors' institutions, the most papers come from the United States (1,862), China (1,507) and Germany (438).
- The institutions with the most papers are Carnegie Mellon University (201), Tsinghua University (189) and Technical University of Munich (142).
- Its most-cited paper of these years is “ConceptGraphs: Open-Vocabulary 3D Scene Graphs for Perception and Planning” (2024), with 290 citations.

## Papers per year

*ICRA papers per publication year in OpenAlex (–: not in OpenAlex yet)*

| Year | Papers | With affiliations |
|---|---:|---:|
| 2024 | 1,766 | 1,714 |
| 2025 | 1,610 | 1,579 |
| 2026 | 1,771 | 1,715 |

## Sources

*Where OpenAlex lists the papers*

| OpenAlex source | Which papers |
|---|---|
| [S4210217939](https://openalex.org/S4210217939) | The conference's proceedings |

## Who publishes there

*Institutions with the most ICRA papers, 2024–2026*

| # | Institution | Papers |
|---:|---|---:|
| 1 | Carnegie Mellon University | 201 |
| 2 | [Tsinghua University](https://scholar4ai.com/institutions/tsinghua-university.md) | 189 |
| 3 | Technical University of Munich | 142 |
| 4 | [Shanghai Jiao Tong University](https://scholar4ai.com/institutions/shanghai-jiao-tong-university.md) | 140 |
| 5 | Massachusetts Institute of Technology | 138 |
| 6 | [Zhejiang University](https://scholar4ai.com/institutions/zhejiang-university.md) | 120 |
| 7 | [Chinese Academy of Sciences](https://scholar4ai.com/institutions/chinese-academy-of-sciences.md) | 117 |
| 8 | Chinese University of Hong Kong | 95 |
| 9 | Georgia Institute of Technology | 92 |
| 10 | University of California, Berkeley | 90 |

*Countries with the most ICRA papers, 2024–2026*

| # | Country | Papers |
|---:|---|---:|
| 1 | United States | 1,862 |
| 2 | China | 1,507 |
| 3 | Germany | 438 |
| 4 | United Kingdom | 344 |
| 5 | South Korea | 237 |
| 6 | Hong Kong | 227 |
| 7 | Japan | 185 |
| 8 | Canada | 163 |
| 9 | Singapore | 155 |
| 10 | Switzerland | 139 |

*Keywords with the most ICRA papers, 2024–2026*

| # | Keyword | Papers |
|---:|---|---:|
| 1 | robotic manipulation | 389 |
| 2 | human-robot interaction | 292 |
| 3 | autonomous driving | 256 |
| 4 | collision avoidance | 164 |
| 5 | imitation learning | 161 |
| 6 | robot navigation | 157 |
| 7 | [vision-language models](https://scholar4ai.com/keywords/vision-language-models.md) | 156 |
| 8 | [large language models](https://scholar4ai.com/keywords/large-language-models.md) | 150 |
| 9 | sim-to-real transfer | 148 |
| 10 | [reinforcement learning](https://scholar4ai.com/keywords/reinforcement-learning.md) | 147 |

## Most-cited papers

*Most-cited ICRA papers of 2024–2026 (citations counted by OpenAlex)*

| # | Citations | Title | Published | Authors |
|---:|---:|---|---|---|
| 1 | 290 | [ConceptGraphs: Open-Vocabulary 3D Scene Graphs for Perception and Planning](https://doi.org/10.1109/icra57147.2024.10610243) | 2024-05-13 | Qiao Gu, Alihusein Kuwajerwala, Sacha Morin et al. |
| 2 | 214 | [HIC-YOLOv5: Improved YOLOv5 For Small Object Detection](https://doi.org/10.1109/icra57147.2024.10610273) | 2024-05-13 | Shiyi Tang, Shu Zhang, Yini Fang |
| 3 | 198 | [Open X-Embodiment: Robotic Learning Datasets and RT-X Models : Open X-Embodiment Collaboration 0](https://doi.org/10.1109/icra57147.2024.10611477) | 2024-05-13 | Abby O'Neill, Abdul Rehman, Abhiram Maddukuri et al. |
| 4 | 190 | [Driving with LLMs: Fusing Object-Level Vector Modality for Explainable Autonomous Driving](https://doi.org/10.1109/icra57147.2024.10611018) | 2024-05-13 | Long Chen, Oleg Sinavski, Jan Hünermann et al. |
| 5 | 180 | [RoCo: Dialectic Multi-Robot Collaboration with Large Language Models](https://doi.org/10.1109/icra57147.2024.10610855) | 2024-05-13 | Zhao Mandi, Shreeya Jain, Shuran Song |
| 6 | 176 | [Extreme Parkour with Legged Robots](https://doi.org/10.1109/icra57147.2024.10610200) | 2024-05-13 | Xuxin Cheng, Kexin Shi, Ananye Agarwal et al. |
| 7 | 154 | [VLFM: Vision-Language Frontier Maps for Zero-Shot Semantic Navigation](https://doi.org/10.1109/icra57147.2024.10610712) | 2024-05-13 | Naoki Yokoyama, Sehoon Ha, Dhruv Batra et al. |
| 8 | 139 | [NoMaD: Goal Masked Diffusion Policies for Navigation and Exploration](https://doi.org/10.1109/icra57147.2024.10610665) | 2024-05-13 | Ajay Sridhar, Dhruv Shah, Catherine Glossop et al. |
| 9 | 112 | [Physically Grounded Vision-Language Models for Robotic Manipulation](https://doi.org/10.1109/icra57147.2024.10610090) | 2024-05-13 | Jensen Gao, Bidipta Sarkar, Fei Xia et al. |
| 10 | 99 | [AutoTAMP: Autoregressive Task and Motion Planning with LLMs as Translators and Checkers](https://doi.org/10.1109/icra57147.2024.10611163) | 2024-05-13 | Yongchao Chen, Jacob Arkin, Charles Dawson et al. |

## Cite this page

Scholar4AI. (2026). ICRA: IEEE International Conference on Robotics and Automation — papers and institutions, 2024–2026. Journal and Conference Research Rankings. Retrieved November 2, 2026, from https://scholar4ai.com/proceedings/icra

```bibtex
@misc{scholar4ai-proceedings-icra,
  author = {{Scholar4AI}},
  title = {ICRA: IEEE International Conference on Robotics and Automation — papers and institutions, 2024–2026},
  year = {2026},
  howpublished = {\url{https://scholar4ai.com/proceedings/icra}},
  urldate = {2026-11-02},
  note = {Journal and Conference Research Rankings; data from OpenAlex (CC0); licensed CC BY-NC 4.0}
}
```

License: CC BY-NC 4.0 (https://creativecommons.org/licenses/by-nc/4.0/).