scholarly journals An Outline of Multi-Sensor Fusion Methods for Mobile Agents Indoor Navigation

Sensors ◽  
2021 ◽  
Vol 21 (5) ◽  
pp. 1605
Author(s):  
Yuanhao Qu ◽  
Minghao Yang ◽  
Jiaqing Zhang ◽  
Wu Xie ◽  
Baohua Qiang ◽  
...  

Indoor autonomous navigation refers to the perception and exploration abilities of mobile agents in unknown indoor environments with the help of various sensors. It is the basic and one of the most important functions of mobile agents. In spite of the high performance of the single-sensor navigation method, multi-sensor fusion methods still potentially improve the perception and navigation abilities of mobile agents. This work summarizes the multi-sensor fusion methods for mobile agents’ navigation by: (1) analyzing and comparing the advantages and disadvantages of a single sensor in the task of navigation; (2) introducing the mainstream technologies of multi-sensor fusion methods, including various combinations of sensors and several widely recognized multi-modal sensor datasets. Finally, we discuss the possible technique trends of multi-sensor fusion methods, especially its technique challenges in practical navigation environments.

2021 ◽  
Vol 4 (1) ◽  
pp. 3
Author(s):  
Parag Narkhede ◽  
Rahee Walambe ◽  
Shruti Mandaokar ◽  
Pulkit Chandel ◽  
Ketan Kotecha ◽  
...  

With the rapid industrialization and technological advancements, innovative engineering technologies which are cost effective, faster and easier to implement are essential. One such area of concern is the rising number of accidents happening due to gas leaks at coal mines, chemical industries, home appliances etc. In this paper we propose a novel approach to detect and identify the gaseous emissions using the multimodal AI fusion techniques. Most of the gases and their fumes are colorless, odorless, and tasteless, thereby challenging our normal human senses. Sensing based on a single sensor may not be accurate, and sensor fusion is essential for robust and reliable detection in several real-world applications. We manually collected 6400 gas samples (1600 samples per class for four classes) using two specific sensors: the 7-semiconductor gas sensors array, and a thermal camera. The early fusion method of multimodal AI, is applied The network architecture consists of a feature extraction module for individual modality, which is then fused using a merged layer followed by a dense layer, which provides a single output for identifying the gas. We obtained the testing accuracy of 96% (for fused model) as opposed to individual model accuracies of 82% (based on Gas Sensor data using LSTM) and 93% (based on thermal images data using CNN model). Results demonstrate that the fusion of multiple sensors and modalities outperforms the outcome of a single sensor.


2007 ◽  
Vol 61 (1) ◽  
pp. 45-62 ◽  
Author(s):  
Hui Yu ◽  
Enrique Aguado ◽  
Gary Brodin ◽  
John Cooper ◽  
David Walsh ◽  
...  

In densely-populated cities or indoor environments, limited visibility to satellites and severe multipath effects significantly affect the accuracy and reliability of satellite-based positioning systems. To meet the needs of “seamless navigation” in these challenging environments an advanced terrestrial positioning system is under development. This system is based upon Ultra-Wideband (UWB) technology, which is a promising candidate for this application due to good time domain resolution and immunity to multipath. This paper presents a detailed analysis of two key aspects of the UWB signal design that will allow it to be used as the basis of such a high performance positioning system: the modulation scheme and the multiple access technique. These two aspects are evaluated in terms of spectral efficiency and synchronisation performance over multipath channels. Thus this paper identifies optimal modulation and multiple access techniques for a long range, high performance terrestrial positioning system using UWB.


2013 ◽  
Vol 20 (4) ◽  
pp. 40-48 ◽  
Author(s):  
Shaojie Shen ◽  
Nathan Michael ◽  
Vijay Kumar

2021 ◽  
Vol 15 (03) ◽  
pp. 337-357
Author(s):  
Alexander Julian Golkowski ◽  
Marcus Handte ◽  
Peter Roch ◽  
Pedro J. Marrón

For many application areas such as autonomous navigation, the ability to accurately perceive the environment is essential. For this purpose, a wide variety of well-researched sensor systems are available that can be used to detect obstacles or navigation targets. Stereo cameras have emerged as a very versatile sensing technology in this regard due to their low hardware cost and high fidelity. Consequently, much work has been done to integrate them into mobile robots. However, the existing literature focuses on presenting the concepts and algorithms used to implement the desired robot functions on top of a given camera setup. As a result, the rationale and impact of choosing this camera setup are usually neither discussed nor described. Thus, when designing the stereo camera system for a mobile robot, there is not much general guidance beyond isolated setups that worked for a specific robot. To close the gap, this paper studies the impact of the physical setup of a stereo camera system in indoor environments. To do this, we present the results of an experimental analysis in which we use a given software setup to estimate the distance to an object while systematically changing the camera setup. Thereby, we vary the three main parameters of the physical camera setup, namely the angle and distance between the cameras as well as the field of view and a rather soft parameter, the resolution. Based on the results, we derive several guidelines on how to choose the parameters for an application.


Author(s):  
Weiyan Chen ◽  
Fusang Zhang ◽  
Tao Gu ◽  
Kexing Zhou ◽  
Zixuan Huo ◽  
...  

Floor plan construction has been one of the key techniques in many important applications such as indoor navigation, location-based services, and emergency rescue. Existing floor plan construction methods require expensive dedicated hardware (e.g., Lidar or depth camera), and may not work in low-visibility environments (e.g., smoke, fog or dust). In this paper, we develop a low-cost Ultra Wideband (UWB)-based system (named UWBMap) that is mounted on a mobile robot platform to construct floor plan through smoke. UWBMap leverages on low-cost and off-the-shelf UWB radar, and it is able to construct an indoor map with an accuracy comparable to Lidar (i.e., the state-of-the-art). The underpinning technique is to take advantage of the mobility of radar to form virtual antennas and gather spatial information of a target. UWBMap also eliminates both robot motion noise and environmental noise to enhance weak reflection from small objects for the robust construction process. In addition, we overcome the limited view of single radar by combining multi-view from multiple radars. Extensive experiments in different indoor environments show that UWBMap achieves a map construction with a median error of 11 cm and a 90-percentile error of 26 cm, and it operates effectively in indoor scenarios with glass wall and dense smoke.


2006 ◽  
Vol 532-533 ◽  
pp. 333-336 ◽  
Author(s):  
Bok Choon Kang ◽  
Chathura Nalendra Herath ◽  
Jong Kwang Park ◽  
Yong Hwang Roh

Carbon, aramid and glass fibers are inherently superior to conventional textile fibers in terms of mechanical properties and other characteristics. However, each material has its inherent advantages and disadvantages and it is usually recommended to hybridize them to fully benefit of their high performance in practical applications to many products. This paper is concerned with an air texturing process for hybridization of different reinforcement filament yarns. A normal air texturing machine was selected for process development and modified to suit testing purposes. The modified process for hybridization was introduced mainly in terms of air-jet nozzles employed in experiments. With the proposed air texturing process machine, three types of air-nozzle were applied to the experimental work. Three different filament materials were employed in experiments and they are carbon (CF), aramid (AF), and glass (GF). As matrix materials, polyether-ether (PEEK), polyester (PES), and polypropylene (PP) were selected and experimented. Hybrid yarns produced form the proposed process was evaluated optically in terms of bulkiness, arranging, breaking, and mixing, respectively. The experimental results were also summarized in terms of relationships between applied air pressure and yarn count, and variation in count. As a whole, it was concluded from the experiments that the proposed texturing process could be successfully applied to the practical hybridization of different reinforcement filament yarns. It was also revealed from the experiments that the air pressure in the proposed process is not a significant parameter on the pressing in terms of yarn count.


Author(s):  
Marius Beul ◽  
Nicola Krombach ◽  
Yongfeng Zhong ◽  
David Droeschel ◽  
Matthias Nieuwenhuisen ◽  
...  

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