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The overall results point towards the potential for our method to accelerate the testing procedures for autonomous vehicles.

Recent robotic innovations have opened up possibilities for employing humanoid robots in tasks that demand physical human interaction, exemplified by robot-assisted care. The physical contact inherent in physical human-robot interaction (pHRI) can be enhanced by employing effective sensing technologies. The flexible tactile sensing array is integrated as the tactile skin of humanoid robot HRP-4C, as detailed in this paper. Given the sensor’s flexible form, enabling it to assume any shape, precise spatial calibration—determining the positions and surface orientations of the sensor cells when mounted on the robot—becomes paramount. Employing B-spline surfaces, a novel spatial calibration method has been created for this task. Two methods are employed to demonstrate that this sensor calibration yields an accurate approximation of position. Concurrently, our adaptable tactile sensor’s full integration onto a robot, and subsequent use for control tasks, is highlighted. These contributions pave the way for flexible tactile sensor implementation within pHRI applications.

Tracking a mobile object, as employed in a radio signal-based wireless communication system, is a subject of interest. We use a strategy involving multiple signal receivers to track a non-cooperative transmitter situated inside a confined workspace containing various uncharted impediments. A non-cooperative transmitter is characterized by its unknown signal emission time. A time difference of arrival (TDOA) localization method is employed to ascertain the transmitter’s location, leveraging signal reception time disparities across multiple receivers. A moving, non-cooperative transmitter’s tracking suffers from non-line-of-sight (NLOS) errors when obstructions block the line of sight (LOS) connection to the receiver. Tracking a moving transmitter, while mitigating NLOS errors in TDOA-only measurements, is the focus of this article. To improve the accuracy of time difference of arrival (TDOA) measurements, a novel algorithm is proposed to pinpoint a transmitter’s location while minimizing errors associated with non-line-of-sight (NLOS) situations. The interacting multiple model Kalman filter (IMM KF) is combined with our proposed localization algorithm for real-time monitoring of a moving transmitter. Our article, as far as we’re aware, is novel in its approach to tracking a moving transmitter solely from TDOA measurements in an unidentified environment featuring a blend of line-of-sight and non-line-of-sight conditions. The proposed filter, performing quickly, significantly decreases the prevalence of NLOS errors in TDOA-only measurements. Subsequently, the proposed tracking methodology is demonstrably appropriate for real-time monitoring of a moving transmitter’s movement. Our MATLAB simulations provide conclusive evidence of the proposed filter’s superior performance compared to existing state-of-the-art TDOA filters, both in terms of processing time and tracking accuracy.

The intricate dance of ship collision avoidance is heavily influenced by a multitude of factors. The Optimal Collision Avoidance Point (OCAP), a novel methodology, is proposed in this study for unmanned surface vehicles (USVs) to calculate the optimal time for evasive maneuvers to prevent collisions. This approach employs a method for obstacle detection and avoidance that incorporates a model of USV dynamics, considering two degrees of freedom, along with a velocity obstacle method. The USV’s navigation state transition is determined by the method, using the critical collision avoidance standard. To determine the optimal collision avoidance point’s coordinates in the current ship encounter, the relative velocities and kinematic parameters of the USV and any obstacles are employed as the basis. The vessel’s linear velocity and heading angle increments, capable of reaching the optimal collision avoidance point, are established as constraints within the dynamic window sampling process. Ultimately, the algorithm assesses the likelihood of collision risks for trajectories meeting the crucial criteria, employing the resultant collision avoidance probability as a benchmark for navigational evaluation. For USVs, a dynamic collision avoidance algorithm is developed, effectively addressing multiple moving obstructions in real-time. cetp signal Experimental results confirm that the OCAP algorithm possesses a higher and more robust path-finding efficiency than the competing two algorithms when dynamic obstacle density increases.

The rising popularity of energy-optimal adaptive cruise control (EACC) is attributable to its ability to reduce energy expenditure. For enhanced EACC performance, despite system noise, an improved model predictive control (MPC) scheme is introduced, which combines the Sage-Husa adaptive Kalman filter (SHAKF), the cubature Kalman filter (CKF), and the backpropagation neural network (BPNN). The MPC’s proposed design boosts safety, tracking, and energy efficiency simultaneously. The simulation’s final results demonstrate that the proposed algorithm exhibits superior energy-saving capabilities than those of prior studies, while consistently maintaining an appropriate relative distance and speed from the preceding vehicle. This confirms the algorithm’s effectiveness.

To develop a method for quantifying sound amplification ratios in sealed air chambers of diverse configurations, a body-conduction microphone for measuring animal scratching sounds was designed. Quantitative scrutiny of scratching actions in dogs has become mandatory in recent times. Our prior development involved a collar with a body-conduction microphone; its purpose is to evaluate body-conducted scratching sounds. The air chamber, one part of the body-conduction microphone, is not adequately designed. This research investigated amplification ratios of air chambers possessing different shapes, via a blend of numerical analysis and experimentation. Sound frequencies below 3 kHz saw the horn-shaped air chamber outperform all others in terms of amplification, as indicated by the results. Simulation results show that the horn-shaped air chamber, with a 1 mm height and a 15 mm diameter, achieved a simulated amplification ratio of 525 dB. Distortion of the air chamber’s foundation affected the amplification coefficient. Ensuring consistent amplification in the margined horn shape hinges on precisely adjusting the horn’s marginal extent at all pressing levels. Regarding the margined horn-shaped air chamber, its simulated amplification ratio stood at 534 dB, while its experimental counterpart measured 194 dB.

The importance of magnetic sensors extends to several sectors, including industrial, security, military, and biomedical. Due to their adjustable magnetic properties and substantial spin polarization, Heusler alloys show considerable promise for use in magnetic sensors. The dynamic field range a magnetic sensor can achieve is strongly correlated with the material’s perpendicular magnetic anisotropy (PMA). The PMA provides a means to modify the directionality, sensitivity, and accuracy characteristics of the magnetic sensors. We present a study on the tuning of PMA in a Co2MnGa Heusler alloy film, achieved by exposure to argon (Ar) ion irradiation. 30 keV 40Ar+ ions were used to irradiate MgO/Co2MnGa/Pd films, featuring an initial PMA. The fluences employed, ranging from 10^13 to 10^15 ions/cm^2, corresponded to displacement per atom values estimated between 0.17 and 17, based on Monte Carlo simulations. The magneto-optical results, complemented by magnetization measurements, pointed to a decrease in the effective anisotropy energy (Keff) from ~153 kJ/m³ in the non-irradiated film to ~14 kJ/m³ in the 1×10¹⁴ Ar/cm² irradiated film. Ion irradiation’s effect on the interface, causing intermixing, is the reason for the decrease in Keff and PMA, along with the reduced interfacial anisotropy. Magnetic sensor applications benefit from ion irradiation’s capacity to effectively modify the PMA characteristics of Co2MnGa Heusler alloy.

Using the antenna gain array manifold, a directional multiple signal classification (Dir-MUSIC) algorithm has been presented for the purpose of determining the direction of partial discharge (PD) sources inside substations. Nevertheless, PD signals encompass a broad frequency range, and antenna gain patterns exhibit variability across frequencies; consequently, a wideband Dir-MUSIC algorithm can enhance precision. The paper delves into wideband Dir-MUSIC algorithms, culminating in a novel proposal: the strength proportion-based Dir-MUSIC (DirSP) algorithm. Based on the proportional strength of signals from diverse directions, this algorithm estimates a targeted phase difference (PD) signal at a particular frequency. This concentrated PD signal at that frequency can then be further processed by the Dir-MUSIC algorithm. Computer simulations reveal that significant discrepancies in antenna gain functions between frequency bins can negatively impact the precision of the Dir-MUSIC algorithm, contrasting favorably with the superior performance of DirDP. Six sets of samples were part of the experiments, and the calculated mean error and standard deviation were both less than 4, hence exceeding the performance of other methods.

The swift advancement of deep learning technology has led to its application in detecting welding defects. Potential welding defects in the manufacturing process of power batteries for new energy vehicles can be linked to the high directivity, convergence, and substantial penetration of the laser beam. The precision of deep learning predictions concerning welding defects is heavily dependent on substantial datasets, yet assembling a balanced dataset of welding defects at battery production sites is a considerable hurdle. The authors of this paper created RIAM, a dataset composed of images taken from an industrial environment specializing in laser welding for power battery modules. The four image types found in RIAM are: Normality, Lack of fusion, Surface porosity, and Scaled surface.