Simple and robust localization system using ceiling landmarks and infrared light

Author(s):  
Joel Vidal ◽  
Chyi-Yeu Lin
Sensors ◽  
2019 ◽  
Vol 19 (22) ◽  
pp. 4946 ◽  
Author(s):  
David Alejo ◽  
Fernando Caballero ◽  
Luis Merino

Sewers represent a very important infrastructure of cities whose state should be monitored periodically. However, the length of such infrastructure prevents sensor networks from being applicable. In this paper, we present a mobile platform (SIAR) designed to inspect the sewer network. It is capable of sensing gas concentrations and detecting failures in the network such as cracks and holes in the floor and walls or zones were the water is not flowing. These alarms should be precisely geo-localized to allow the operators performing the required correcting measures. To this end, this paper presents a robust localization system for global pose estimation on sewers. It makes use of prior information of the sewer network, including its topology, the different cross sections traversed and the position of some elements such as manholes. The system is based on a Monte Carlo Localization system that fuses wheel and RGB-D odometry for the prediction stage. The update step takes into account the sewer network topology for discarding wrong hypotheses. Additionally, the localization is further refined with novel updating steps proposed in this paper which are activated whenever a discrete element in the sewer network is detected or the relative orientation of the robot over the sewer gallery could be estimated. Each part of the system has been validated with real data obtained from the sewers of Barcelona. The whole system is able to obtain median localization errors in the order of one meter in all cases. Finally, the paper also includes comparisons with state-of-the-art Simultaneous Localization and Mapping (SLAM) systems that demonstrate the convenience of the approach.


IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 62495-62504
Author(s):  
Yongliang Shi ◽  
Weimin Zhang ◽  
Fangxing Li ◽  
Qiang Huang

2021 ◽  
Vol 18 (5) ◽  
pp. 172988142110476
Author(s):  
Jibo Wang ◽  
Chengpeng Li ◽  
Bangyu Li ◽  
Chenglin Pang ◽  
Zheng Fang

High-precision and robust localization is the key issue for long-term and autonomous navigation of mobile robots in industrial scenes. In this article, we propose a high-precision and robust localization system based on laser and artificial landmarks. The proposed localization system is mainly composed of three modules, namely scoring mechanism-based global localization module, laser and artificial landmark-based localization module, and relocalization trigger module. Global localization module processes the global map to obtain the map pyramid, thus improve the global localization speed and accuracy when robots are powered on or kidnapped. Laser and artificial landmark-based localization module is employed to achieve robust localization in highly dynamic scenes and high-precision localization in target areas. The relocalization trigger module is used to monitor the current localization quality in real time by matching the current laser scan with the global map and feeds it back to the global localization module to improve the robustness of the system. Experimental results show that our method can achieve robust robot localization and real-time detection of the current localization quality in indoor scenes and industrial environment. In the target area, the position error is less than 0.004 m and the angle error is less than 0.01 rad.


2020 ◽  
Vol 48 (6) ◽  
pp. 2657-2667
Author(s):  
Felipe Montecinos-Franjola ◽  
John Y. Lin ◽  
Erik A. Rodriguez

Noninvasive fluorescent imaging requires far-red and near-infrared fluorescent proteins for deeper imaging. Near-infrared light penetrates biological tissue with blood vessels due to low absorbance, scattering, and reflection of light and has a greater signal-to-noise due to less autofluorescence. Far-red and near-infrared fluorescent proteins absorb light >600 nm to expand the color palette for imaging multiple biosensors and noninvasive in vivo imaging. The ideal fluorescent proteins are bright, photobleach minimally, express well in the desired cells, do not oligomerize, and generate or incorporate exogenous fluorophores efficiently. Coral-derived red fluorescent proteins require oxygen for fluorophore formation and release two hydrogen peroxide molecules. New fluorescent proteins based on phytochrome and phycobiliproteins use biliverdin IXα as fluorophores, do not require oxygen for maturation to image anaerobic organisms and tumor core, and do not generate hydrogen peroxide. The small Ultra-Red Fluorescent Protein (smURFP) was evolved from a cyanobacterial phycobiliprotein to covalently attach biliverdin as an exogenous fluorophore. The small Ultra-Red Fluorescent Protein is biophysically as bright as the enhanced green fluorescent protein, is exceptionally photostable, used for biosensor development, and visible in living mice. Novel applications of smURFP include in vitro protein diagnostics with attomolar (10−18 M) sensitivity, encapsulation in viral particles, and fluorescent protein nanoparticles. However, the availability of biliverdin limits the fluorescence of biliverdin-attaching fluorescent proteins; hence, extra biliverdin is needed to enhance brightness. New methods for improved biliverdin bioavailability are necessary to develop improved bright far-red and near-infrared fluorescent proteins for noninvasive imaging in vivo.


1999 ◽  
Vol 09 (PR2) ◽  
pp. Pr2-161
Author(s):  
F. H. Julien ◽  
P. Boucaud ◽  
S. Sauvage ◽  
O. Gauthier-Lafaye ◽  
Z. Moussa

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