CAD2SLAM: Adaptive Projection Between CAD Blueprints and SLAM Maps

IF 4.6 2区 计算机科学 Q2 ROBOTICS
Martín Bayón-Gutiérrez;Natalia Prieto-Fernández;María Teresa García-Ordás;José Alberto Benítez-Andrades;Héctor Alaiz-Moretón;Giorgio Grisetti
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引用次数: 0

Abstract

Robotic mobile platforms are key building blocks for numerous applications and cooperation between robots and humans is a key aspect to enhance productivity and reduce labor cost. To operate safely, robots typically rely on a custom map of the environment that depends on the sensor configuration of the platform. In contrast, blueprints stand as an abstract representation of the environment. The use of both CAD and SLAM maps allows robots to collaborate using the blueprint as a common language, while also easing the control for non-robotics experts. In this work we present an adaptive system to project a 2D pose in the blueprint to the SLAM map and vice-versa. Previous work in the literature aims at morphing a SLAM map to a previously available map. In contrast, CAD2SLAM does not alter the internal map representation used by the SLAM and localization algorithms running on the robot, preserving its original properties. We believe that our system is beneficial for the control and supervision of multiple heterogeneous robotic platforms that are monitored and controlled through the CAD map. Finally, we present a set of experiments that support our claims as well as open-source implementation.
CAD2SLAM: CAD蓝图和SLAM地图之间的自适应投影
机器人移动平台是众多应用的关键组成部分,机器人与人之间的合作是提高生产力和降低劳动力成本的关键方面。为了安全操作,机器人通常依赖于平台传感器配置的自定义环境地图。相比之下,蓝图是对环境的抽象表现。CAD和SLAM地图的使用允许机器人使用蓝图作为通用语言进行协作,同时也简化了非机器人专家的控制。在这项工作中,我们提出了一个自适应系统,将蓝图中的2D姿势投影到SLAM地图,反之亦然。先前文献中的工作旨在将SLAM地图变形为先前可用的地图。相比之下,CAD2SLAM不会改变SLAM和机器人上运行的定位算法所使用的内部地图表示,保留了其原始属性。我们相信,我们的系统有利于控制和监督多个异构机器人平台,通过CAD地图进行监测和控制。最后,我们提出了一组实验来支持我们的主张以及开源实现。
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来源期刊
IEEE Robotics and Automation Letters
IEEE Robotics and Automation Letters Computer Science-Computer Science Applications
CiteScore
9.60
自引率
15.40%
发文量
1428
期刊介绍: The scope of this journal is to publish peer-reviewed articles that provide a timely and concise account of innovative research ideas and application results, reporting significant theoretical findings and application case studies in areas of robotics and automation.
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