Accurate 3D Localization Using RGB-TOF Camera and IMU for Industrial Mobile Robots

被引：7

作者：

Yekkehfallah, Majid ^{[1
,2
]}

Yang, Ming ^{[1
,2
]}

Cai, Zhiao ^{[1
,2
]}

Li, Liang ^{[1
]}

Wang, Chuanxiang ^{[1
,2
]}

机构：

[1] Shanghai Jiao Tong Univ, Dept Automat, Shanghai 200240, Peoples R China

[2] Minist Educ China, Key Lab Syst Control & Informat Proc, Shanghai 200240, Peoples R China

来源：

ROBOTICA | 2021年 / 39卷 / 10期

基金：

中国国家自然科学基金;

关键词：

RGB-TOF camera; Industrial mobile robots; Localization; SLAM; Sensor fusion; Extended Kalman filter; ROBUST; SCALE;

D O I：

10.1017/S0263574720001526

中图分类号：

TP24 [机器人技术];

学科分类号：

080202 ; 1405 ;

摘要：

Localization based on visual natural landmarks is one of the state-of-the-art localization methods for automated vehicles that is, however, limited in fast motion and low-texture environments, which can lead to failure. This paper proposes an approach to solve these limitations with an extended Kalman filter (EKF) based on a state estimation algorithm that fuses information from a low-cost MEMS Inertial Measurement Unit and a Time-of-Flight camera. We demonstrate our results in an indoor environment. We show that the proposed approach does not require any global reflective landmark for localization and is fast, accurate, and easy to use with mobile robots.

引用

页码：1816 / 1833

页数：18

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