An Autonomous Vehicle Navigation System Based on Inertial and Visual Sensors

Guang, Xingxing; Gao, Yanbin; Leung, Henry; Liu, Pan; Li, Guangchun

doi:10.3390/s18092952

Cited by 17 publications

(8 citation statements)

References 25 publications

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“…The high-speed rotation missile is a conventional missile which relies on its own rotating motion to eliminate machining errors and achieve flight stability [20], and there is a high-speed rotational motion around its own roll axis. In order to complete the high-precision navigation and positioning requirements of the missile, the accurate measurement of the roll angle cannot be completed by relying on the large-range sensor, under the condition that the existing sensor fabrication process is unchanged [21,22].…”

Section: Design Principle and Optimal Quality Selection Methods Of Sspmentioning

confidence: 99%

Optimization Design Method of a New Stabilized Platform Based on Missile-borne Semi-Strap-down Inertial Navigation System

Jing

Zhang

et al. 2018

Sensors

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At present, existing wide range Micro-Electro-Mechanical-Systems (MEMS) inertial sensors have relatively lower precision and direct measurement of the missile’s high-rotation motion inevitably uses a large-range sensor. To achieve high-precision navigation, this paper proposes a novel Semi-strap-down Stabilized Platform (SSP) based on the Missile-borne Semi-Strap-down Inertial Navigation System, which is used to mount sensors and lowers sensor range requirements through isolating the high-rotational motion of missile. First, the author innovatively puts forward a dynamic model under missile-borne environment, then analyses the influence of SSP quality on the range of gyro according to the dynamic model of the SSP. Finally, when the angle of attack of the missile is 2°, the best quality of the SSP with minimum roll angular rate amplitude was calculated through the Runge-Kutta method and the mass gradient control method. Experiments have been carried out by using a high-precision, tri-axial flight simulation turntable to validate the viability of the method. Experiments show that under the same conditions, the angular velocity of the new optimized SSP with the best quality design is reduced to 1/3 of the unoptimized SSP, and the measured roll angle error is reduced to 60% of the unoptimized measurement. The results indicate that the novel SSP has better performance segregating the high-speed rotational motion, and provides theoretical guidance for the high-precision small-range sensor instead of the low-precision wide-range sensor. In addition, the first proposed SSP quality selection method creates a new idea for the improvement of the positioning accuracy in the missile-borne environment.

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Section: Design Principle and Optimal Quality Selection Methods Of Sspmentioning

confidence: 99%

Optimization Design Method of a New Stabilized Platform Based on Missile-borne Semi-Strap-down Inertial Navigation System

Jing

Zhang

et al. 2018

Sensors

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“…The successful use of autonomous vehicles will have a significant impact on human life. It will bring more comfortable and more accessible driving experiences for people [29]. With AVs, drivers do not need to drive or sit behind the wheel all the time, and thus the driver has free time to perform non-driving activities [30].…”

Section: Perceived Advantagementioning

confidence: 99%

Do People Prefer Cars That People Don’t Drive? A Survey Study on Autonomous Vehicles

Meidutė‐Kavaliauskienė

Yıldız

Çiğdem

et al. 2021

Energies

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Only recently, smart cities are taking shape, thanks to the rapid development of Internet of Things (IoT), cloud computing, and other similar technologies. Given the high demands placed on advanced technologies such as autonomous driving, cloud data services, and high-precision sensors, smart cities are creating an intelligent transportation environment conducive to the introduction of autonomous vehicles (AVs). In this context, the use of AVs in transportation is also considered a form of transportation innovation. As a result, AVs are considered more favorable to people interested in new technologies because they appear to be technologically superior. Their association with the most up-to-date technology can serve as a symbol for those who wish to demonstrate their interest in new technologies through their appearance. The positive image of technological innovation projected by AVs may influence their acceptance among technology enthusiasts to a significant degree. In this context, this study investigates the effects of perceived advantage, perceived risk, and perceived safety on the intention to use autonomous vehicles. For this purpose, data were collected from vehicle users living in Turkey by survey method. Secondly, factor analyses and regression analyses were performed with the data set obtained from 611 participants. As a result of the analyses, it has been determined that the perceived advantage and perceived security increase the intention to use autonomous vehicles. In contrast, the perceived risk reduces this intention to use. According to these results, recommendations were made to the companies about the level of acceptance of this technology by the users to assess their investments in autonomous vehicles better.

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“…Nowadays, the growing demand for servant robots has prompted researchers to improve technologies for automating these platforms. One of the most fundamental technologies for automating these platforms is their navigation system [1]. Autonomous mobile robot navigation is an active area of research and has gained the great attention of numerous researchers in the recent past [2,3].…”

Section: Introductionmentioning

confidence: 99%

A CNN-Based System for Mobile Robot Navigation in Indoor Environments via Visual Localization with a Small Dataset

Foroughi

Chen

Wang

2021

WEVJ

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Deep learning has made great advances in the field of image processing, which allows automotive devices to be more widely used in humans’ daily lives than ever before. Nowadays, the mobile robot navigation system is among the hottest topics that researchers are trying to develop by adopting deep learning methods. In this paper, we present a system that allows the mobile robot to localize and navigate autonomously in the accessible areas of an indoor environment. The proposed system exploits the Convolutional Neural Network (CNN) model’s advantage to extract data feature maps for image classification and visual localization, which attempts to precisely determine the location region of the mobile robot focusing on the topological maps of the real environment. The system attempts to precisely determine the location region of the mobile robot by integrating the CNN model and topological map of the robot workspace. A dataset with small numbers of images is acquired from the MYNT EYE camera. Furthermore, we introduce a new loss function to tackle the bounded generalization capability of the CNN model in small datasets. The proposed loss function not only considers the probability of the input data when it is allocated to its true class but also considers the probability of allocating the input data to other classes rather than its actual class. We investigate the capability of the proposed system by evaluating the empirical studies based on provided datasets. The results illustrate that the proposed system outperforms other state-of-the-art techniques in terms of accuracy and generalization capability.

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An Autonomous Vehicle Navigation System Based on Inertial and Visual Sensors

Cited by 17 publications

References 25 publications

Optimization Design Method of a New Stabilized Platform Based on Missile-borne Semi-Strap-down Inertial Navigation System

Optimization Design Method of a New Stabilized Platform Based on Missile-borne Semi-Strap-down Inertial Navigation System

Do People Prefer Cars That People Don’t Drive? A Survey Study on Autonomous Vehicles

A CNN-Based System for Mobile Robot Navigation in Indoor Environments via Visual Localization with a Small Dataset

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