3D self-localization for humanoid robots using view regression and odometry

R. Mendoza, P. Bustamante, B. Medrano, Eric Hernández Castillo, J. Zannatha
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引用次数: 3

Abstract

The ambience of research in VSLAM and relocalization algorithms in the last few years allure with real-time localization and increased precision for RGBD or stereo cameras but with ambivalence requesting higher computational capacity or more expensive sensors. The aim of this paper is to present a gentle algorithm to locate a humanoid robot using relocalization view based algorithms and odometry information using general regression with Nadayara-Watson kernel for applications where the area is already known such as RoboCup competitions or service robots.
基于视图回归和里程计的仿人机器人三维自定位
在过去的几年里,VSLAM和重新定位算法的研究环境吸引了RGBD或立体相机的实时定位和更高的精度,但也存在要求更高的计算能力或更昂贵的传感器的矛盾心理。本文的目的是提出一种温和的算法来定位人形机器人,该算法使用基于重新定位视图的算法和使用Nadayara-Watson内核的通用回归的测程信息,用于已经已知区域的应用,如机器人世界杯比赛或服务机器人。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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