Search results

The purpose of this study is to use visual and inertial sensors to achieve real-time location. How to provide an accurate location has become a popular research topic in the field of indoor navigation. Although the complementarity of vision and inertia has been widely applied in indoor navigation, many problems remain, such as inertial sensor deviation calibration, unsynchronized visual and inertial data acquisition and large amount of stored data.

First, this study demonstrates that the vanishing point (VP) evaluation function improves the precision of extraction, and the nearest ground corner point (NGCP) of the adjacent frame is estimated by pre-integrating the inertial sensor. The Sequential Similarity Detection Algorithm (SSDA) and Random Sample Consensus (RANSAC) algorithms are adopted to accurately match the adjacent NGCP in the estimated region of interest. Second, the model of visual pose is established by using the parameters of the camera itself, VP and NGCP. The model of inertial pose is established by pre-integrating. Third, location is calculated by fusing the model of vision and inertia.

In this paper, a novel method is proposed to fuse visual and inertial sensor to locate indoor environment. The authors describe the building of an embedded hardware platform to the best of their knowledge and compare the result with a mature method and POSAV310.

This paper proposes a VP evaluation function that is used to extract the most advantages in the intersection of a plurality of parallel lines. To improve the extraction speed of adjacent frame, the authors first proposed fusing the NGCP of the current frame and the calibrated pre-integration to estimate the NGCP of the next frame. The visual pose model was established using extinction VP and NGCP, calibration of inertial sensor. This theory offers the linear processing equation of gyroscope and accelerometer by the model of visual and inertial pose.

How to model blind image deblurring that arises when a camera undergoes ego-motion while observing a static and close scene. In particular, this paper aims to detail how the blurry image can be restored under a sequence of the linear model of the point spread function (PSF) that are derived from the 6-degree of freedom (DOF) camera’s accurate path during the long exposure time.

There are two existing techniques, namely, an estimation of the PSF and a blind image deconvolution. Based on online and short-period inertial measurement unit (IMU) self-calibration, this motion path has discretized a sequence of the uniform speed of 3-DOF rectilinear motion, which unites with a 3-DOF rotational motion to form a discrete 6-DOF camera’s path. These PSFs are evaluated through the discrete path, then combine with a blurry image to restoration through deconvolution.

This paper describes to build a hardware attachment, which is composed of a consumer camera, an inexpensive IMU and a 3-DOF motion mechanism to the best of the knowledge, together with experimental results demonstrating its overall effectiveness.

First, the paper proposes that a high-precision 6-DOF motion platform periodically adjusts the speed of a three-axis rotational motion and a three-axis rectilinear motion in a short time to compensate the bias of the gyroscope and the accelerometer. Second, this paper establishes a model of 6-DOF motion and emphasizes on rotational motion, translational motion and scene depth motion. Third, this paper addresses a novel model of the discrete path that the motion during long exposure time is discretized at a uniform speed, then to estimate a sequence of PSFs.

The magnetometer measurement update plays a key role in correcting yaw estimation in fusion algorithms, and hence, the yaw estimation is vulnerable to magnetic disturbances. The purpose of this study is to improve the ability of the fusion algorithm to deal with magnetic disturbances.

In this paper, an adaptive measurement equation based on vehicle status is derived, which can constrain the yaw estimation from drifting when vehicle is running straight. Using this new measurement, a Kalman filter-based fusion algorithm is constructed, and its performance is evaluated experimentally.

The experiments results demonstrate that the new measurement update works as an effective supplement to the magnetometer measurement update in the present of magnetic disturbances, and the proposed fusion algorithm has better yaw estimation accuracy than the conventional algorithm.

The paper proposes a new adaptive measurement equation for yaw estimation based on vehicle status. And, using this measurement, the fusion algorithm can not only reduce the weight of disturbed sensor measurement but also utilize the character of vehicle running to deal with magnetic disturbances. This strategy can also be used in other orientation estimation fields.

The purpose of this paper is to study the tribological performance and anti‐wear mechanism of Cu nanoparticles as lubricating oil additives.

An end‐face wear testing apparatus is used to measure the tribological properties of Cu nanoparticles as lubricating oil additives and using a commercial SJ 15W/40 gasoline engine oil for comparison. Electrical contact resistance (ECR) is measured on a universal nano and micro tester‐2 tribometer to detect the formation of tribo‐film generated by Cu nanoparticulate additive. The worn steel surfaces are investigated by scanning electron microscope (SEM), energy dispersive spectra (EDS) and X‐ray photoelectron spectroscopy (XPS).

The results show that Cu nanoparticles used as an oil additive can improve the anti‐wear and friction‐reduction performance of SJ 15W/40 gasoline engine oil remarkably. The results of SEM, EDS and XPS show that a deposit film containing metallic copper can form on the worn surface, which has a film thickness of about 120 nm.

This investigation establishes a baseline of Cu nanoparticles used as lubricating oil additives under face‐to‐face contact work conditions. Thus, the results are reliable and can be very useful for further applications of Cu nanoparticle additives in industry.

The purpose of this paper is to show which models, uncertain or certain, simple or complicated, are more suitable when they are faced with incomplete information and inaccurate data.

The characteristics of fuzzy mathematics, grey system theory, rough set theory and the basic characteristics of incomplete information and inaccurate data in uncertain systems are analysed.

The similarities and differences among fuzzy mathematics, grey system theory, rough set theory and probability statistics are compared. The principle of simplicity of scientific theories, methods, and models are discussed.

It is suggested that the tendency to concentrate on a complicated model isn't always necessary when faced with the condition of incomplete information and inaccurate data.

The paper shows that a more satisfied result can be obtained with an uncertain model than with a meticulous model on a certain situation.

Between 1860 and 1945, the Chinese port city of Tianjin was the site of up to nine foreign-controlled concessions, functioning side by side. Rogaski defined it as a ‘hyper-colony’, a term which reflects Tianjin's socio-political intricacies and the multiple colonial discourses of power and space. This essay focuses on the transformation of the Tianjin cityscape during the last 150 years, and aims at connecting the hyper-colonial socio-spatial forms with the processes of post-colonial identity construction. Tianjin is currently undergoing a massive renovation program: its transmogrifying cityscape unveils multiple layers of ‘globalizing’ spatialities and temporalities, throwing into relief processes of power and capital accumulation, which operate via the urban regeneration's experiment. This study uses an ‘interconnected history’ approach and traces the interweaving ‘worlding’ nodes of today's Tianjin back to the global connections established in the city during the hyper-colonial period. What emerges is Tianjin's simultaneous tendency towards ‘world-class-ness’ and ‘China-class-ness’.

The purpose of this paper is to introduce the elementary concepts and fundamental principles of grey systems and the main components of grey systems theory. Also to discuss the astonishing progress that grey systems theory has made in the world of learning and its wide‐ranging applications in the entire spectrum of science.

The characteristics of unascertained systems including incomplete information and inaccuracies in data are analysed and four uncertain theories: probability statistics, fuzzy mathematics, grey system and rough set theory are compared. The scientific principle of simplicity and how precise models suffer from inaccuracies are also shown.

The four uncertain theories, probability statistics, fuzzy mathematics, grey system and rough set theory are examined with different research objects, different basic sets, different methods and procedures, different data requirements, different emphasis, different objectives and different characteristics.

The scientific principle of simplicity and how precise models suffer from inaccuracies are shown. So, precise models are not necessarily an effective means to deal with complex matters, especially in the case that the available information is incomplete and the collected data inaccurate.

The elementary concepts and fundamental principles of grey systems and the main components of grey systems theory are introduced briefly. The reader is given a general picture of grey systems theory as a new method for studying problems where partial information is known, partial information is unknown; especially for uncertain systems with few data points and poor information.

The purpose of this paper is to prepare water‐soluble TiO₂ nanoparticles and evaluate the tribological properties as additives in water.

Nanoparticles present excellent friction‐reducing and antiwear properties as additives in base oils. However, there are seldom literatures about the nanoparticles as additives in water as yet. In this work, water‐soluble TiO₂ nanoparticles were prepared by sol‐gel method and characterized with transmission electron microscopy and selected area electron diffraction. The tribological properties as additives in water were investigated by SRV and the surface analysis by scanning electron microscope and X‐ray photon electron spectroscope.

TiO₂ nanoparticles modified with polyethylene glycol have uniform size about 10 nm and easily dissolve in water. The tribological experiments showed TiO₂ nanoparticles exhibit excellent friction‐reducing and antiwear properties.

The paper is restricted to only TiO₂ nanoparticles. Some other water‐soluble nanoparticles also should be prepared and their tribological properties investigated.

Water‐soluble TiO₂ nanoparticles could be used as water additives and improve the tribological properties.

This paper emphasises that the water‐soluble nanoparticles are prepared and could be used as water additives.

The wind speed is very fluctuant and contains a significant energy. Taking into account the turbulent component in the energy management would increase the profitability of the wind‐diesel hybrid system. Sometimes, a diesel generator is used to compensate the requested energy but the storage devices are required to prevent disturbances induced by the wind generator current on the DC‐bus. The purpose of this paper is to show how the battery and flywheel (or ultracapacitors (UCs)) are used to mitigate the fluctuations of the wind generator current. The proposed method is based on the filtering of the wind generator current. The high power density sources (flywheel and UCs) are used in aims to improve the batteries' lifetime, which is estimated, in this paper, by using the rainflow cycles counting method. Spectral studies are made and the simulation and experimental results are analyzed.

This study is organized according to the following main and sub‐topics: wind speed characteristics, hybrid system energy management, behavioral simulations results, spectral analysis and batteries' lifetime estimation and experimental setup and results.

The simulations results highlight the interest in using a second‐order filter. The experimental results show that the fluctuations induced by the wind generator current are effectively mitigated by the storage devices.

The spectral analysis of the current for different filters parameters is realized and the application of the rainflow cycles counting method, in this context, is presented. This paper is interesting for the experimental hybrid system design according to the method proposed to control the DC‐DC converters.