We are on the cusp of a new era of connected autonomous vehicles with unprecedented user experiences, tremendously improved road safety and air quality, highly diverse transportation environments and ...use cases, and a plethora of advanced applications. Realizing this grand vision requires a significantly enhanced vehicle-to-everything (V2X) communication network that should be extremely intelligent and capable of concurrently supporting hyperfast, ultrareliable, and low-latency massive information exchange. It is anticipated that the sixth-generation (6G) communication systems will fulfill these requirements of the next-generation V2X. In this article, we outline a series of key enabling technologies from a range of domains, such as new materials, algorithms, and system architectures. Aiming for truly intelligent transportation systems, we envision that machine learning (ML) will play an instrumental role in advanced vehicular communication and networking. To this end, we provide an overview of the recent advances of ML in 6G vehicular networks. To stimulate future research in this area, we discuss the strength, open challenges, maturity, and enhancing areas of these technologies.
Automatic Welding Seam Tracking and Identification Xinde Li; Xianghui Li; Shuzhi Sam Ge ...
IEEE transactions on industrial electronics (1982),
2017-Sept., 2017-9-00, 20170901, Letnik:
64, Številka:
9
Journal Article
Recenzirano
In the automatic welding process on mid/thick plates, the precision of the welding position has an important effect on welding quality, which mainly relies on the identification of the welding seam. ...However, due to some possible disturbances in complex unstructured welding environments, e.g., strong arc lights, welding splashes, thermal-induced deformations, etc., it is a great challenge to identify the welding seam. In this paper, we propose a robust automatic welding seam identification and tracking method by utilizing structured-light vision. First, after the preprocessing of the welding image, the gray distribution of the laser stripe is tracked and the profile of the welding seam is searched in a small area by using the Kalman filter, with the aim to avoid some disturbances. Second, in order to extract the welding seam profile, a series of centroids obtained by scanning the columns in the rectangular window are fitted using the least-squares method. Third, a character string method is proposed to qualitatively describe the welding seam profile, which might consist of different segment and junction relationship elements. And then, these character strings acquired from the object image are matched with those from the model, so that the position of the welding seam can be determined. Finally, the advantages of the new algorithm are testified and compared through several experiments.
Deformation is a crucial factor to be employed for evaluating the health state of the equipment structure. Electrical-based sensors have been widely used for structural deformation monitoring. ...However, they are difficult to achieve accurate measurements in some harsh environments, such as those with strong magnetic fields, corrosion, and high-speed rotations. Compared with electrical-based sensors, fiber optic sensors (FOSs) possess the inherent advantages of being small and having passive sensing, anti-electromagnetic interference, etc ., which endows them with great potential for deformation sensing. In this review, fiber optic deformation sensors (FODSs) are divided into contact and non-contact types according to the spatial location relationship between them and the objects being monitored. Related FOS sensing principles, including wavelength, phase, and intensity modulations are introduced. Also, cutting-edge designs of contact and non-contact FODS are discussed. Recent achievements in applying FODS are investigated and their limitations and development prospects analyzed.
Multisensor fusion strategies have been widely applied in human activity recognition (HAR) in body sensor networks (BSNs). However, the sensory data collected by BSNs systems are often uncertain or ...even incomplete. Thus, designing a robust and intelligent sensor fusion strategy is necessary for high-quality activity recognition. In this article, Dezert-Smarandache theory (DSmT) is used to develop a novel sensor fusion strategy for HAR in BSNs, which can effectively improve the accuracy of recognition. Specifically, in the training stage, the kernel density estimation (KDE)-based models are first built and then precisely selected for each specific activity according to the proposed discriminative functions. After that, a structure of basic belief assignment (BBA) can be constructed, using the relationship between the test data of unknown class and the selected KDE models of all considered types of activities. In order to deal with the conflict between the obtained BBAs, proportional conflict redistribution-6 (PCR6) is applied to fuse the acquired BBAs. Moreover, the missing data of the involved sensors are addressed as ignorance in the framework of the DSmT without manual interpolation or intervention. Experimental studies on two real-world activity recognition datasets (The OPPORTUNITY dataset; Daily and Sports Activity Dataset (DSAD)) are conducted, and the results shows the superiority of our proposed method over some state-of-the-art approaches proposed in the literature.
In the process of automatic welding based on structured light vision, the precise localization of the welding seam in an image has an important influence on the quality of the welding. However, in ...practice, there is much interference, such as spatter and arc, which introduces great challenges for accurate welding seam localization. In this paper, we considered welding seam localization problem as visual target tracking and based on that, we proposed a robust welding seam tracking algorithm. Prior to the start of welding, the seam is separated using a cumulative gray frequency, which is utilized to adaptively determine the initial position and size of the search window. During the welding process, large seam motion range may result in only a portion of the welding seam exists in the search window. To prevent that, a tracking-by-detection method is used to calculate the location of the search window. Usually, the intersection of seam and noise, e.g., spatter, has a severe influence on the accuracy of feature points localization. In order to solve this problem, a sequence gravity method (SGM) for extracting a smoother center line of welding seam is proposed, which is able to reduce the impact of interference. The double-threshold recursive least square method is used to fit the curve obtained by SGM with the aim of improving the real-time performance and accuracy of the system. Finally, the superiority of the proposed algorithm is well demonstrated by comparison with other solutions for seam tracking and recognition through extensive experiments.
Accurate ranging using narrow-band ultrasonic transducers in small-scale environments can be used for indoor localization, human motion capture, and robotic navigation. One of the main problems faced ...by the ultrasonic localization systems is the ranging error due to the Doppler shift. Existing methods for Doppler correction employ a bank of matched filters at the receiver end which is computationally intense and complex. On the other hand, enabling multiple access for the ultrasonic localization systems is a challenging task due to multiple access interference. We propose a method to measure the range between multiple ultrasonic mobile nodes and static anchors in which we track the Doppler velocity and correct the errors between the transmitted and the received signals due to the Doppler effect. We utilize range-Doppler coupling to estimate the Doppler shift and adjust the range values calculated by correlation. In our method, a unique set of two chirp signals are used for each transmitter to get one sample reading. The simulation results show high ranging accuracy and robustness using the proposed method as the Doppler velocity increases. A pendulum experiment was conducted to validate the method using narrowband ultrasonic sensors. The multiple access interference problem was tackled by orthogonal coding, the chirp signals and Doppler correction. An improvement in the ranging accuracy was observed over traditional methods using chirp signals without Doppler correction.
This paper presents a chirp based ultrasonic positioning system (UPS) using orthogonal chirp waveforms. In the proposed method, multiple transmitters can simultaneously transmit chirp signals, as a ...result, it can efficiently utilize the entire available frequency spectrum. The fundamental idea behind the proposed multiple access scheme is to utilize the oversampling methodology of orthogonal frequency-division multiplexing (OFDM) modulation and orthogonality of the discrete frequency components of a chirp waveform. In addition, the proposed orthogonal chirp waveforms also have all the advantages of a classical chirp waveform. Firstly, the performance of the waveforms is investigated through correlation analysis and then, in an indoor environment, evaluated through simulations and experiments for ultrasonic (US) positioning. For an operational range of approximately 1000 mm, the positioning root-mean-square-errors (RMSEs) &90% error were 4.54 mm and 6.68 mm respectively.
In ultrasonic positioning systems (UPSs) chirp waveforms have attracted much attention due to its high range resolution. However, the multiple-access schemes for the chirp-based UPS are limited. In ...its application to multiple-access ultrasonic positioning, effective waveform diversity design is a prerequisite. In a multiple-access UPS, each transmitter should transmit a unique waveform with impulse-like auto-correlation and relatively flat cross-correlations to the waveforms transmitted by other transmitters. Proposed in this paper is a methodology whereby multiple transmitters can transmit chirp signals simultaneously. The chirp waveforms are constructed by concatenating a number of linear sub-chirps of the same durations and bandwidths but different starting and stopping frequencies. This process is optimized by selecting sequences with impulse-like auto-correlations and relatively flat cross-correlations. First, the efficiency of the proposed methodology is evaluated by several metrics and, then, in an indoor environment, through simulations and experiments for ultrasonic positioning.
Gait analysis in unrestrained environments can be done with a single wearable ultrasonic sensor node on the lower limb and four fixed anchor nodes. The accuracy demanded by such systems is very high. ...Chirp signals can provide better ranging and localization performance in ultrasonic systems. However, we cannot neglect the multi-path effect in typical indoor environments for ultrasonic signals. The multi-path components closer to the line of sight component cannot be identified during correlation reception which leads to errors in the estimated range and which in turn affects the localization and tracking performance. We propose a novel method to reduce the multi-path effect in ultrasonic sensor networks in typical indoor environments. A gait analysis system with one mobile node attached to the lower limb was designed to test the performance of the proposed system during an indoor treadmill walking experiment. An optical motion capture system was used as a benchmark for the experiments. The proposed method gave better tracking accuracy compared to conventional coherent receivers. The static measurements gave 2.45 mm standard deviation compared to 10.45 mm using the classical approach. The RMSE between the ultrasonic gait analysis system and the reference system improved from 28.70 mm to 22.28 mm. The gait analysis system gave good performance for extraction of spatial and temporal parameters.
Ranging based on ultrasonic sensors can be used for tracking wearable mobile nodes accurately for a long duration and can be a cost-effective method for human movement analysis in rehabilitation ...clinics. In this paper, we present a Doppler-tolerant ultrasonic multiple access localization system to analyze gait parameters in human subjects. We employ multiple access methods using linear chirp wave-forms and narrow-band piezoelectric transducers. A Doppler shift compensation Technique is also incorporated without compromising on the tracking accuracy. The system developed was used for tracking the trajectory of both lower limbs of five healthy adults during a treadmill walk. An optical motion capture system was used as the reference to compare the performance. The average Root Mean Square Error values between the 3D coordinates estimated from the proposed system and the reference system while tracking both lower limbs during treadmill walk experiment by 5 subjects were found to be 16.75, 14.68 and 20.20 mm respectively along X, Y and Z-directions. Errors in the estimation of spatial and temporal parameters from the proposed system were also quantified. These promising results show that narrowband ultrasonic sensors can be utilized to accurately track more than one mobile node for human gait analysis.
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