Search Results (7)

This study addresses the challenges of human–robot interactions in real-time environments with adaptive field-programmable gate array (FPGA)-based accelerators. Predicting human posture in indoor environments in confined areas is a significant challenge for service robots. The proposed approach works on two levels: the estimation of human location and the robot’s intention to serve based on the human’s location at static and adaptive positions. This paper presents three methodologies to address these challenges: binary classification to analyze static and adaptive postures for human localization in indoor environments using the sensor fusion method, adaptive Simultaneous Localization and Mapping (SLAM) for the robot to deliver the task, and human–robot implicit communication. VLSI hardware schemes are developed for the proposed method. Initially, the control unit processes real-time sensor data through PIR sensors and multiple ultrasonic sensors to analyze the human posture. Subsequently, static and adaptive human posture data are communicated to the robot via Wi-Fi. Finally, the robot performs services for humans using an adaptive SLAM-based triangulation navigation method. The experimental validation was conducted in a hospital environment. The proposed algorithms were coded in Verilog HDL, simulated, and synthesized using VIVADO 2017.3. A Zed-board-based FPGA Xilinx board was used for experimental validation. Full article

Turbulent free-surface flows are encountered in several engineering applications and are typically characterized by the entrainment of air bubbles due to intense mixing and surface deformation. The resulting complex multiphase structure of the air–water interface presents a challenge in precise and reliable measurements of the free-water-surface topography. Conventional methods by manometers, wave probes, point gauges or electromagnetic/ultrasonic devices are proven and reliable, but also time-consuming, with limited accuracy and are mostly intrusive. Accurate spatial and temporal measurements of complex three-dimensional free-surface flows in natural and man-made hydraulic structures are only viable by high-resolution non-contact methods, namely, LIDAR-based laser scanning, photogrammetric reconstruction from cameras with overlapping field of view, or laser triangulation that combines laser ranging with high-speed imaging data. In the absence of seeding particles and optical calibration targets, sufficient flow aeration is essential for the operation of both laser- and photogrammetry-based methods, with local aeration properties significantly affecting the measurement uncertainty of laser-based methods. Full article

The acoustic emission (AE) technique is one of the most widely used in the field of structural monitoring. Its popularity mainly stems from the fact that it belongs to the category of non-destructive techniques (NDT) and allows the passive monitoring of structures. The technique employs piezoelectric sensors to measure the elastic ultrasonic wave that propagates in the material as a result of the crack formation’s abrupt release of energy. The recorded signal can be investigated to obtain information about the source crack, its position, and its typology (Mode I, Mode II). Over the years, many techniques have been developed for the localization, characterization, and quantification of damage from the study of acoustic emission. The onset time of the signal is an essential information item to be derived from waveform analysis. This information combined with the use of the triangulation technique allows for the identification of the crack location. In the literature, it is possible to find many methods to identify, with increasing accuracy, the onset time of the P-wave. Indeed, the precision of the onset time detection affects the accuracy of identifying the location of the crack. In this paper, two techniques for the definition of the onset time of acoustic emission signals are presented. The first method is based on the Akaike Information Criterion (AIC) while the second one relies on the use of artificial intelligence (AI). A recurrent convolutional neural network (R-CNN) designed for sound event detection (SED) is trained on three different datasets composed of seismic signals and acoustic emission signals to be tested on a real-world acoustic emission dataset. The new method allows taking advantage of the similarities between acoustic emissions, seismic signals, and sound signals, enhancing the accuracy in determining the onset time. Full article

The indoor positioning system (IPS) is becoming increasing important in accurately determining the locations of objects by the utilization of micro-electro-mechanical-systems (MEMS) involving smartphone sensors, embedded sources, mapping localizations, and wireless communication networks. Generally, a global positioning system (GPS) may not be effective in servicing the reality of a complex indoor environment, due to the limitations of the line-of-sight (LoS) path from the satellite. Different techniques have been used in indoor localization services (ILSs) in order to solve particular issues, such as multipath environments, the energy inefficiency of long-term battery usage, intensive labour and the resources of offline information collection and the estimation of accumulated positioning errors. Moreover, advanced algorithms, machine learning, and valuable algorithms have given rise to effective ways in determining indoor locations. This paper presents a comprehensive review on the positioning algorithms for indoors, based on advances reported in radio wave, infrared, visible light, sound, and magnetic field technologies. The traditional ranging parameters in addition to advanced parameters such as channel state information (CSI), reference signal received power (RSRP), and reference signal received quality (RSRQ) are also presented for distance estimation in localization systems. In summary, the recent advanced algorithms can offer precise positioning behaviour for an unknown environment in indoor locations. Full article

In social situations, people who use a powered wheelchair must divide their attention between navigating the chair and conversing with people. These conversations could lead to increased mental stress when navigating and distraction from maneuvering the chair. As a solution that maintains a good conversation distance between the wheelchair and the accompanying person (Social Following), a wheelchair control system was developed to provide automated side-by-side following by wirelessly connecting the wheelchair to the person. Two ultrasonic range sensors and three piezoelectric ultrasonic transducers were used to identify the accompanying person and determine their position and heading. Identification involved an ultrasonic beacon worn on the person’s side, at hip level, and receivers on the wheelchair. A drive control algorithm maintained a constant conversation distance along the person’s trajectory. A plug-and-play prototype was developed and connected to a Permobil F5 Corpus wheelchair with a modified Eightfold Technologies SmartChair Remote. Results demonstrated that the system can navigate a wheelchair based on the accompanying person’s trajectory, which is advantageous for users who require hands-free wheelchair control during social activities. Full article

The structural health monitoring (SHM) of critical structures is a complex task that involves the use of different sensors that are also aimed at the identification of the location of the impact point using ultrasonic sensors. For the evaluation of the impact position, reference is often made to the well-known triangulation method. This method requires the estimation of the differential time of arrival (DToA) and the group velocity of the Lamb waves propagating into a plate-like structure: the uncertainty of these two parameters is taken into consideration as main cause of localization error. The work proposes a simple laboratory procedure based on a set-up with a pair of sensors that are symmetrically placed with respect to the impact point, to estimate the uncertainty of the DToA and the propagation velocity estimates. According to a theoretical analysis of the error for the impact position, the experimental uncertainties of DToA and the propagation velocity are used to estimate the overall limit of the SHM system for the impact positioning. Because the error for the DToA estimate depends also on the adopted signal processing, three common methods are selected and compared: the threshold, the correlation method, and a likelihood algorithm. Finally, the analysis of the positioning error using multisensory configuration is reported as useful for the design of the SHM system. Full article

The position determination inside a building where no GPS signal is beingreceived can be ascertained using laser transmitters in industrial situations where there areno people or using triangulation of the signal strength, normally electro-magnetic signals,if the required accuracy is more than a metre. Our solution is aimed at situations wherepeople are present and where the required accuracy is less than 30 cm, such as in shoppingprecincts or supermarkets. To achieve this, a network of ultrasonic transmitters is fittedinto the ceiling which receives a synchronised time signal. Each transmitter has a uniqueidentifier code and emits its code with a delay with respect to the common time signalwhich is proportional to its code number with an ASK modulation over the ultrasonic bandcentred on 40 KHz. The receivers circulating beneath the transmitters receive the codes ofthose within their detection range, translate the time delays into distances and then obtaintheir position by triangulation since the receivers know the position of every transmitter.Since the receivers are not synchronised with the common time signal or the actual speedof the sound, whose value varies appreciably with temperature, relative humidity andatmospheric pressure, a consecutive approximation algorithm has been introduced. This isbased on the fact that the Z coordinator of the receiver is known and constant and thus it is possible, with only three different identifiers received, to deduce the phase of the common time signal and estimate the speed of the sound with a fourth identifier. Full article