会议信息

ICRL 2026: International Conference on Robotics and Learning

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截稿日期:
2026-05-10 已截稿
通知日期:
2026-06-18
会议日期:
2026-07-10
会议地点:
Yili, China
浏览: 1082   关注: 0   参加: 0
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ICRL
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搜索与榜单列表完全无需凭证;本页的完整详情需要一把免费 API 密钥。详见开发者接入页。

会伴指数 (CP-I)

44.1 / 100
全站第 3,246 名 / 共 5,705 个会议 · 前 57%

机器人与控制 第 212 / 472

证据有限:这个会议不在 CCF / ICORE / QUALIS 任何一份榜单里,也没有录用率数据,因此分数的大部分回落到了中性基准。
学术认可 (35%) 无数据 —— 按中性基准 50 分计入 —
投稿选择性 (20%) 无数据 —— 按中性基准 50 分计入 —
会议传承 (20%) 无数据 —— 按中性基准 50 分计入 —
社区关注 (10%)
13
资料公开度 (15%)
35

用到的输入: 过去 24 个月打开过本页的研究者:5 人

公开资料里还缺: 历年录用率 (+4.5) · 历届信息 (+3.0) · 最佳论文记录 (+2.3)
主办方认领本会议后,可直接在这一页补上;分数每晚重算。如何提升这个分数

置信度 25% —— 分数中有多大比例来自实际观测到的数据,而不是中性基准。 这个分数是怎么算出来的 · 查看完整榜单 · 算法版本 1.2 · 算于 2026-10-16

征稿

ICRL 2026 (International Conference on Robotics and Learning) is an academic conference held in Yili, China on 2026-07-10. The paper submission deadline is 2026-05-10. Acceptance notifications are sent on 2026-06-18.

International Conference on Robotics and Learning (ICRL) aims to promote the exchange of ideas in robotics, with a focus on robot learning. The topics of interest for submission include, but are not limited to: Robotics Embodied Intelligence Robot Robot Learning & Adaptive Control Neuro-robotics Multimodal Sensor Fusion Dexterous Hands & Tactile Sensing Force Control & Compliant Manipulation Advanced Optoelectronic Sensors for Robotic Perception Novel Actuation Materials Micro/Nanorobotics Reconfigurable Robotics Medical & Rehabilitation Robotics Simulation & Digital Twins Multi-Robot Collaboration Embodied Foundation Models Sustainable Robotics Bio-inspired Robotics Space & Underwater Robotics Service Robotics Robotic Vision Perception Intelligent Transportation & Autonomous Driving Learning Learning Enhanced Perception for Robotics Learning Enhanced Robot Planning Learning Enhanced Robot Manipulation Learning Enhanced Robot Control Learning Method for Human-robot Coordination Learning Method for Multi-robot Cooperation or Confrontation Learning Method for Self-driving Learning Based Robotic Warehousing Learning Enhanced Intelligent Transportation Learning Method for Bionic Robotics and Medical Robotics Learning Method for UAV and USV Deep Learning, Imitation Learning and Reinforcement Learning for Robotic System Sim-to-Real Transfer for Robotic Applications Dataset, Benchmark and Simulator for Robotic Learning Applications for Robotic Learning Opto-Mechano-Electronic Integrated Intelligent Robotic Systems
由 Dou Sun 最后更新于

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