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IF 5.7 3区 计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS Pub Date : 2024-09-10 DOI: 10.1109/mra.2024.3442413
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引用次数: 0
ICRA 40: a Special Event to Commemorate the 40th Anniversary of ICRA and RAS 国际注册会计师协会 40:纪念国际注册会计师协会和注册会计师协会成立 40 周年特别活动
IF 5.7 3区 计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS Pub Date : 2024-09-10 DOI: 10.1109/mra.2024.3428751
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引用次数: 0
IEEE Robotics and Automation Magazine Call for Papers Special Issue on Robot Ethics Ethical, Legal and User Perspectives in the Development and Application of Robotics and Automation IEEE 机器人与自动化杂志征稿启事 机器人伦理特刊 机器人与自动化开发和应用中的伦理、法律和用户视角
IF 5.7 3区 计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS Pub Date : 2024-09-10 DOI: 10.1109/mra.2024.3428749
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引用次数: 0
IEEE Transactions on Field Robotics Call for Special Issue on Space Robotics [Society News] IEEE 《现场机器人技术》杂志征集太空机器人特刊 [学会新闻]
IF 5.7 3区 计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS Pub Date : 2024-09-10 DOI: 10.1109/mra.2024.3428228
Provides society information that may include news, reviews or technical notes that should be of interest to practitioners and researchers.
提供从业人员和研究人员感兴趣的社会信息,包括新闻、评论或技术说明。
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引用次数: 0
Organizing the Big Flagship Conference: Connect +: The International Conference on Robotics and Automation 2024 [Conference Highlights] 组织大型旗舰会议:Connect +:2024 年机器人与自动化国际会议 [会议亮点]
IF 5.7 3区 计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS Pub Date : 2024-09-10 DOI: 10.1109/mra.2024.3428035
Zhidong Wang
Five weeks after the International Conference on Robotics and Automation (ICRA) 2024, I am enjoying writing a small number of e-mails every day, for uploading Plenary/Keynote video recordings to InfoVaya, answering inquiries from our attendees, and some wrapping tasks for the conference, etc., as the general chair of the conference. Images of the exciting days of the conference at Pacific Yokohama are becoming a good memory for me and our organizing team, closed by the Japanese Dram performance and fireworks, and the very exciting workshop day. We would like to thank the opportunity to organize this Robotics and Automation Society (RAS) flagship conference at Yokohama, and express our heartfelt thanks to all of the authors, members of the ICRA Conference Editorial Board, institutes and industrial partners, workshop/tutorial and competition organizers, student volunteers and staff, and all of the attendees for their unwavering support and contributions to make this conference a success (Figure 1).
2024 年国际机器人与自动化大会(ICRA)已经过去五周了,作为大会总主席,我每天都要写几封邮件,将全会/主题演讲的视频录像上传到 InfoVaya,回答参会者的询问,以及大会的一些收尾工作等等。在太平洋横滨会议期间的精彩画面已成为我和我们组织团队的美好回忆,日本戏剧表演和焰火晚会以及令人兴奋的研讨会日为会议画上了圆满的句号。我们要感谢能有机会在横滨组织这次机器人与自动化学会(RAS)的旗舰会议,并向所有作者、国际机器人与自动化学会会议编辑委员会成员、研究所和工业合作伙伴、研讨会/教程和竞赛组织者、学生志愿者和工作人员以及所有与会者表示衷心的感谢,感谢他们为本次会议的成功举办提供了坚定不移的支持和贡献(图 1)。
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引用次数: 0
RAS Congratulates the Honorees at the ICRA 2024 Awards Ceremony [Society News] RAS 在国际注册会计师协会 2024 年颁奖典礼上向获奖者表示祝贺 [协会新闻]
IF 5.7 3区 计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS Pub Date : 2024-09-10 DOI: 10.1109/mra.2024.3428208
Provides society information that may include news, reviews or technical notes that should be of interest to practitioners and researchers.
提供从业人员和研究人员感兴趣的社会信息,包括新闻、评论或技术说明。
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引用次数: 0
2024 IERA Award: Realtime Robotics Awarded for Optimization Tool [Industry Activities] 2024 年 IERA 奖:实时机器人优化工具获奖 [行业活动]
IF 5.7 3区 计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS Pub Date : 2024-09-10 DOI: 10.1109/mra.2024.3428168
Andra Keay
The 2024 “Award for Innovation and Entrepreneurship in Robotics and Automation” (IERA) was given to Realtime Robotics, a U.S. company in Boston, for its fully automatic motion planning tool for industrial robots (see Figure 1). The solution develops an optimized “choreography” for robots that work closely together in work cells without collision. This year, for the first time, all four finalists are newcomers in the industry.
2024 年 "机器人与自动化创新创业奖"(IERA)授予了位于波士顿的美国公司 Realtime Robotics,以表彰其工业机器人全自动运动规划工具(见图 1)。该解决方案为机器人开发了优化的 "编排",使其在工作单元中紧密协作,不会发生碰撞。今年,首次有四家入围企业都是业内新秀。
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引用次数: 0
RAM Calendar - for September 2024 issue RAM 日历 - 2024 年 9 月刊
IF 5.7 3区 计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS Pub Date : 2024-09-10 DOI: 10.1109/mra.2024.3427889
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引用次数: 0
IEEE Launches New Study Group for Humanoids to Explore Current Standards Landscape and Develop Future Standards Roadmap [Standards] 电气和电子工程师学会(IEEE)成立新的人形机器人研究小组,探讨当前的标准状况并制定未来的标准路线图 [标准
IF 5.7 3区 计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS Pub Date : 2024-09-10 DOI: 10.1109/mra.2024.3428752
Aaron Prather
To help support the rapid development of humanoid robotics across numerous industries, the IEEE Robotics and Automation Society’s Standing Committee for Standards Activities has approved a new study group to explore what standards should be developed going forward. This article describes this new study group and solicits participation from others in the community who are interested.
为了帮助支持仿人机器人技术在各行各业的快速发展,电气和电子工程师学会机器人与自动化协会的标准活动常设委员会批准成立一个新的研究小组,探讨今后应制定哪些标准。本文将介绍这个新的研究小组,并邀请社区中感兴趣的其他人士参与。
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引用次数: 0
Computer and Robot Vision: Past, Present, and Future [TC Spotlight] 计算机和机器人视觉:过去、现在和未来 [TC 聚焦]
IF 5.7 3区 计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS Pub Date : 2024-09-10 DOI: 10.1109/mra.2024.3428780
Letizia Gionfrida, Chen Wang, Lu Gan, Margarita Chli, Luca Carlone
Robot perception is the capability of a robot to estimate and understand its surroundings to the degree that enables it to navigate and interact with the environment. Right at the core of robot perception lies the problem of building an internal model of the robot’s surroundings using onboard sensor data and prior knowledge. Although the internal model of the environment can be purely geometric (e.g., a point cloud)—as in traditional simultaneous localization and mapping (SLAM)—it can also contain higher-level structures, such as objects and other semantic elements of the scene (e.g., buildings, roads, pedestrians). In this sense, robot perception is related to the topic of scene understanding in the computer vision literature. Due to its crucial role in enabling robotics applications, ranging from navigation to manipulation and human–robot interaction, robot perception has been at the center stage of robotics research for more than 50 years [1]. Similarly, perception has been a core topic in the computer vision community since its inception [2].
机器人感知能力是指机器人对周围环境的估计和理解能力,这种能力使机器人能够导航并与环境互动。机器人感知的核心问题是利用机载传感器数据和先验知识建立机器人周围环境的内部模型。虽然环境的内部模型可以是纯粹的几何模型(如点云)--如传统的同步定位和映射(SLAM)--但也可以包含更高层次的结构,如物体和场景中的其他语义元素(如建筑物、道路、行人)。从这个意义上说,机器人感知与计算机视觉文献中的场景理解主题相关。由于机器人感知在实现机器人应用(从导航到操纵和人机交互)方面发挥着至关重要的作用,50 多年来,机器人感知一直处于机器人研究的中心位置[1]。同样,自计算机视觉社区成立以来,感知一直是其核心课题[2]。
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引用次数: 0
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IEEE Robotics & Automation Magazine
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