机器人学
人工智能
点云
计算机科学
光学(聚焦)
透视图(图形)
计算机视觉
图像配准
对象(语法)
点(几何)
移动机器人
算法
图像(数学)
数学
机器人
几何学
物理
光学
作者
François Pomerleau,Francis Colas,Roland Siegwart
出处
期刊:Foundations and Trends in Robotics
[Now Publishers]
日期:2015-01-01
卷期号:4 (1): 1-104
被引量:590
摘要
The topic of this review is geometric registration in robotics.Registration algorithms associate sets of data into a common coordinate system.They have been used extensively in object reconstruction, inspection, medical application, and localization of mobile robotics.We focus on mobile robotics applications in which point clouds are to be registered.While the underlying principle of those algorithms is simple, many variations have been proposed for many different applications.In this review, we give a historical perspective of the registration problem and show that the plethora of solutions can be organized and differentiated according to a few elements.Accordingly, we present a formalization of geometric registration and cast algorithms proposed in the literature into this framework.Finally, we review a few applications of this framework in mobile robotics that cover different kinds of platforms, environments, and tasks.These examples allow us to study the specific requirements of each use case and the necessary configuration choices leading to the registration implementation.Ultimately, the objective of this review is to provide guidelines for the choice of geometric registration configuration.
科研通智能强力驱动
Strongly Powered by AbleSci AI