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A Survey of Research on Cloud Robotics and Automation

机译:云机器人与自动化研究综述

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The Cloud infrastructure and its extensive set of Internet-accessible resources has potential to provide significant benefits to robots and automation systems. We consider robots and automation systems that rely on data or code from a network to support their operation, i.e., where not all sensing, computation, and memory is integrated into a standalone system. This survey is organized around four potential benefits of the Cloud: 1) Big Data: access to libraries of images, maps, trajectories, and descriptive data; 2) Cloud Computing: access to parallel grid computing on demand for statistical analysis, learning, and motion planning; 3) Collective Robot Learning: robots sharing trajectories, control policies, and outcomes; and 4) Human Computation: use of crowdsourcing to tap human skills for analyzing images and video, classification, learning, and error recovery. The Cloud can also improve robots and automation systems by providing access to: a) datasets, publications, models, benchmarks, and simulation tools; b) open competitions for designs and systems; and c) open-source software. This survey includes over 150 references on results and open challenges. A website with new developments and updates is available at:
机译:云基础架构及其广泛的Internet可访问资源集有可能为机器人和自动化系统带来重大利益。我们认为机器人和自动化系统依赖于网络中的数据或代码来支持其操作,即并非所有传感,计算和内存都集成到一个独立系统中。这项调查围绕云的四个潜在好处进行组织:1)大数据:访问图像,地图,轨迹和描述性数据的库; 2)云计算:根据需要访问并行网格计算以进行统计分析,学习和运动计划; 3)集体机器人学习:共享轨迹,控制策略和结果的机器人; 4)人工计算:利用众包来挖掘人类的技能,以分析图像和视频,分类,学习和错误修复。通过提供对以下内容的访问,云还可以改善机器人和自动化系统:a)数据集,出版物,模型,基准和仿真工具; b)公开设计和系统竞赛; c)开源软件。这项调查包括150多个关于结果和公开挑战的参考。具有新发展和更新的网站可在以下位置找到:

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