Sensor Orientation Research Articles

Self-Calibration of a Network of Radar Sensors for Autonomous Robots

Radar sensor networks are today widely used in the field of autonomous driving and for generating high-precision images of the environment. The accuracy of the environmental representation depends to a large extent on the accurate knowledge of the sensor's mounting orientation. Both the relative orientation of the sensors to each other and the relative sensor orientation in relation to the vehicle coordinate system are determining factors. For the first time, the orientation estimation of the radar sensors of a network is possible exclusively on the basis of radar target lists without additional localization and orientation devices such as an IMU or GNSS. In this work, two algorithms for determining the orientation of incoherently networked radar sensors with respect to the vehicle coordinate system and with respect to each other are derived and characterized. With the presented algorithms orientation accuracies up to <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$0.25 \,\mathrm{^{\circ }}$</tex-math></inline-formula> are achieved. Furthermore, the algorithms do not impose any requirements on the positioning or the orientation of the radar sensors, such as overlapping field of views (FOVs) or the detection of identical targets. The presented algorithms are applicable to arbitrary driving trajectories as well as for point targets and extended targets which enables the use in regular road traffic.

Novel Manufacturing Techniques for Multifunctional Composites: Integration of Sensors and Actuators

In the rapidly evolving realm of advanced materials, multifunctional composites have emerged as a pivotal frontier, offering unprecedented capabilities in structural and functional integration. This research delves into innovative manufacturing techniques tailored for the seamless integration of sensors and actuators within these composites. Traditional manufacturing methods often compromise the intrinsic properties of composites when embedding functional elements. To address this, our study introduces a novel approach that synergistically combines additive manufacturing and nanotechnology, ensuring the preservation of structural integrity while enhancing functionality. We demonstrate that through strategic placement and orientation of sensors and actuators, it is possible to achieve real-time monitoring, adaptive response, and self-healing capabilities in the composite structures. The developed techniques not only bolster the mechanical performance but also endow the composites with smart functionalities, paving the way for their application in next-generation aerospace, automotive, and biomedical sectors. This paper elucidates the underlying principles, the meticulous process optimizations, and potential applications, marking a significant stride in the convergence of materials science and intelligent systems.

A bioinspired flexible optical sensor for force and orientation sensing

A bioinspired flexible optical sensor for force and orientation sensing

Measurement of Hand Joint Angle Using Inertial-Based Motion Capture System

The inertial sensor motion capture system has significant advantages over the classical optical motion capture system, including its high versatility, portability, and affordability. However, its accuracy is over one order of magnitude lower than the optical system. The measurement error of the finger joint angle is mainly due to sensor drift and misalignment of sensor to finger segment. In this article, we propose a method that includes both orientation estimation and calibration for accurate joint angle estimation. Specifically, at first, the accuracy of the sensor orientation is greatly improved using the square root cubature Kalman filter (SRCKF) to fuse the magnetic and inertial measurement units (MIMUs) data. Second, the kinematic restrictions of the finger joints are used for initial and in-process calibration to achieve sensor-to-segment (StoS) calibration throughout the process. Finally, the difference between the orientation of the two adjacent segments is the joint angle. Experiments show that our proposed system improves joint measurement accuracy compared with the existing inertial sensor-based systems. Evaluation of ten participants showed that the average root mean square error (RMSE) of finger joint measurements is <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$5.5^{\circ }(\pm 4.0^{\circ })$ </tex-math></inline-formula> . Our proposed system provides accurate information in measuring hand joint angles and quantifying hand movement function in clinical practice.

IMU Shoulder Angle Estimation: Effects of Sensor-to-Segment Misalignment and Sensor Orientation Error.

Accurate shoulder joint angle estimation is crucial for analyzing joint kinematics and kinetics across a spectrum of movement applications including in athletic performance evaluation, injury prevention, and rehabilitation. However, accurate IMU-based shoulder angle estimation is challenging and the specific influence of key error factors on shoulder angle estimation is unclear. We thus propose an analytical model based on quaternions and rotation vectors that decouples and quantifies the effects of two key error factors, namely sensor-to-segment misalignment and sensor orientation estimation error, on shoulder joint rotation error. To validate this model, we conducted experiments involving twenty-five subjects who performed five activities: yoga, golf, swimming, dance, and badminton. Results showed that improving sensor-to-segment misalignment along the segment's extension/flexion dimension had the most significant impact in reducing the magnitude of shoulder joint rotation error. Specifically, a 1° improvement in thorax and upper arm calibration resulted in a reduction of 0.40° and 0.57° in error magnitude. In comparison, improving IMU heading estimation was only roughly half as effective (0.23° per 1°). This study clarifies the relationship between shoulder angle estimation error and its contributing factors, and identifies effective strategies for improving these error factors. These findings have significant implications for enhancing the accuracy of IMU-based shoulder angle estimation, thereby facilitating advancements in IMU-based upper limb rehabilitation, human-machine interaction, and athletic performance evaluation.

Влияние термоупругой деформации на точность измерения в звёздных датчиках ориентации

Влияние термоупругой деформации на точность измерения в звёздных датчиках ориентации

TASKED: Transformer-based Adversarial learning for human activity recognition using wearable sensors via Self-KnowledgE Distillation

Wearable sensor-based human activity recognition (HAR) has emerged as a principal research area and is utilized in a variety of applications. Recently, deep learning-based methods have achieved significant improvement in the HAR field with the development of human–computer interaction applications. However, most of them are limited to operating in a local neighborhood in the process of a standard convolution neural network, and correlations between different sensors on body positions are ignored. In addition, even though several recent existing works considered the correlations between different sensor positions, they still face significant challenging problems with performance degradation due to large gaps in the distribution of training and test data, and behavioral differences between subjects. In this work, we propose a novel Transformer-based Adversarial learning framework for human activity recognition using wearable sensors via Self-KnowledgE Distillation (TASKED), that accounts for individual sensor orientations and spatial and temporal features. The proposed method is capable of learning cross-domain embedding feature representations from multiple subjects datasets using adversarial learning and the maximum mean discrepancy (MMD) regularization to align the data distribution over multiple domains. In the proposed method, we adopt the teacher-free self-knowledge distillation to improve the stability of the training procedure and the performance of human activity recognition. Experimental results show that TASKED not only outperforms state-of-the-art methods on the four real-world public HAR datasets (alone or combined) but also improves the subject generalization effectively.

A New Intraoral Six-Degrees-of-Freedom Jaw Movement Tracking Method Using Magnetic Fingerprints.

We proposed a novel jaw movement tracking method that can measure in six degrees of freedom. The magnetic field generated by a permanent magnet paired with a small, low-power-consumption Hall effect magnetic sensor is used to estimate the relative distance between two objects-in this instance, the lower and upper jaws. By installing a microelectromechanical system (MEMS) orientation sensor in the device, we developed a mouthpiece-type sensing device that can measure voluntary mandibular movements in three-dimensional orientation and position. An evaluation of individuals wearing this device demonstrated its ability to measure mandibular movement with an accuracy of approximately 3 mm. Using the movement recording feature with six degrees of freedom also enabled the evaluation of an individual's jaw movements over time in three dimensions. In this method, all sensors are built onto the mouthpiece and the sensing is completed in the oral cavity. It does not require the fixation of a large-scale device to the head or of a jig to the teeth, unlike existing mandibular movement tracking devices. These novel features are expected to increase the accessibility of routine measurements of natural jaw movement, unrestricted by an individual's physiological movement and posture.

Seafloor depth controls seismograph orientation uncertainty

SUMMARY This study evaluates the seafloor ambient noise environment that varies with the water depth based on a correction analysis of the horizontal sensor orientation for ocean-bottom seismographs. As ocean-bottom seismographs are mainly deployed as ‘free-fall’ installations, we have no information on which direction a horizontal sensor faces at the seafloor. An accurate sensor orientation is crucial for data processing based on seismic wavefields. Among several seismological approaches that use passive sources to correct the horizontal sensor azimuth, the particle motion of teleseismic Rayleigh waves is widely used for broad-band ocean-bottom seismographs. We performed seafloor seismic observations in the Hyuga-nada region at the western end of the Nankai subduction zone and deployed broad-band and short-period seismographs. However, studies have yet to investigate whether orientation correction via the Rayleigh-wave polarization method is valid for short-period data. The results of the Rayleigh wave method from our campaign observation data showed that the estimation uncertainty of short-period sensor orientations increased with a decreasing water depth; we observed a transition depth for the uncertainty at 2200–2600 m. The measurement quality, or the cross-correlation coefficient between the radial and Hilbert-transformed vertical components, also decreased at depths shallower than 2000 m. Moreover, an analysis of the noise power spectral densities showed that ambient noise levels during long periods (&amp;gt;10 s) increased with decreasing depth. Infragravity waves controlled vertical long-period noise levels, while ocean currents dominated horizontal long-period noise; both of these reduced the Rayleigh-wave signals as a function of environmental noise. Infragravity waves also likely distorted the Rayleigh waveforms. Both mechanisms contributed to the sudden rise in orientation uncertainty and low measurement quality at shallow stations (i.e. &amp;lt;2000 m). We confirmed that the variation in orientation uncertainty with the water depth can be used as an index for the ambient noise environment of the seafloor.

Sensor Acquisition and Allocation for Real-Time Monitoring of Articulated Construction Equipment in Digital Twins.

The visibility available to an equipment operator on a dynamic construction site can often be blocked by various obstacles such as materials, temporary or permanent facilities, other equipment, and workers. Equipment monitoring in real-time digital twins can thus play a crucial role in accident prevention. This paper develops a scalable technical approach and presents a prototype application framework for transmitting real world sensor data to update 3D equipment models inside a graphical digital twin for concurrent visualization of a monitored construction operation. The developed framework and workflow can be extended to visualize any construction operation, as it occurs, inside a dynamic 3D world simply by outfitting the real equipment with appropriate sensors and connecting them to their virtual counterparts. The implemented proof-of-concept interface is described in the context of a real-time 3D digital twin for assisting excavator operators prevent unintended strikes with underground utilities. Experiments to validate the proposed technical approach by simulating the real-time motion of a backhoe loader’s articulated arm using orientation sensors installed on its boom, stick, and bucket are described. The experimental results characterize the scope and potential reasons for spatio-temporal discrepancies that can occur between a monitored real operation and its replicated digital twin. The effect of an operator warning mechanism based on preset safety thresholds is also investigated and described.

Improvement of Baro Sensors Matrix for Altitude Estimation.

The article presents the use of barometric sensors to precisely determine the altitude of a flying object. The sensors are arranged in a hexahedral spatial arrangement with appropriately spaced air inlets. Thanks to the solution used, the range of measurement uncertainty can be reduced, resulting in a lower probability of error during measurement by improving the accuracy of estimation. The paper also describes the use of pressure sensors in complex Tracking Vertical Velocity and Height systems, integrating different types of sensors to highlight the importance of this single parameter. The solution can find application in computational systems using different types of data in Kalman filters. The impact of pressure measurements in a geometric system with different spatial orientations of sensors is also presented. In order to compensate for local pressure differences, e.g., in the form of side wind gusts, an additional reference sensor was used, making the developed solution relevant for applications such as industrial ones.

Quick and concise land boundary mapping using a drone at Villa Buccu, Kerobokan, Badung, Bali

The effective measurement and mapping of the land is retrieval of accurate data according to position, in accordance with mapping provisions and efficient in both cost and time. One way that data can be retrieved effectively and efficiently is by using a drone, commonly called an unmanned aerial vehicle (UAV).Drone is a vehicle equipped with a wave control system, precision navigation (Global Positioning System/GPS) and flight control electronics so that it is able to fly according to flight planning (autopilot). This drone makes it possible to track the position and orientation of sensors implemented in local or global coordinate systems. With the drone itself, it saves time because it can have an image of an area. Premark / Ground Control Point (GCP) is a point that is commonly used to improve measurement accuracy in mapping using drones, in this case using the Global Positioning System (GPS) Geodetic / RTK Hi Target tool. Mapping Using Drones was then used by many people, including for the purposes of villa spatial planning, so to support this activity a land boundary mapping was carried out at Villa Buccu, Kerobokan, Badung Bali.

Transformational Perceptive of Data Recorder for UAV Flight Automation Control System using Image Processing Techniques

Flight Data Recorders (FDRs) are readily available in the market, to be used on the Unmanned Aerial Vehicles (UAV) for onboard data recording. They have their own inbuilt sensors and characteristics and can be easily placed within the cockpit of the UAV. However, they have umpteen drawbacks. They do not have sufficient sampling rate for rapid and accurate flight automation, are either very bulky, or do not incorporate some of the necessary sensors required for post-flight analysis and are very costly. Hence, the need arises where the FDR needs to be designed to suit the requirements. We go about designing one such FDR. Our FDR incorporates a MicroStrain’s 3DM- GX1 Gyro Enhanced Orientation Sensor, a Texas Instrument’s GPS module and four servo motors each controlling the rudder, elevator, ailerons. The data from these devices are interpolated to increase the sampling rate and are simultaneously stored into a Secure Digital (SD) / Micro Memory Card (MMC) during the flight of the UAV. Greater sampling rates allow more rapid and accurate flight automation. SD/MMC cards allow faster and efficient data retrieval for post flight processing. Our FDR is designed to be compact, cheap and overcomes most of the drawbacks mentioned above. Therefore, we call this FDR as Smart Data Recorder(SDR).

Solar radiation performance adjusting to PV system

The first section of this paper presents the conditions of solar radiation orientation in Kosovo. The sheer existence of the sunlight is indeed an inexhaustible source of renewable energy having ample potential to meet all humankind’s needs for it when innovative technology is used in compliance with modern standards appropriate to economic and social environment and to the nature itself, too. The research conducted for the purpose of the present paper reveals that the greatest amount of radiant energy is focused on the absorber of the collector sensor which transmits the entire moving space at right angles to the sunlight. It is important to note that the collector angle in relation to the horizontal plane cannot be less than 20°, because there is a possibility that the collector, due to the small angle, is covered in dirt and aerosol pollution. These data ensure that best performance in high generation efficiency is reached by improving harnessing patterns in solar cell response. The objective of the Kosovo Plan in 10 years’ period has stimulated the support policy for renewable energy sources, set to be at least 10% at the national level. This paper examines radiation efficiency assessments under sensor monitoring over the absorption space where all time, high absorption power PV system panels are located. Experimental study shows that Kosovo has radiation potential due to its Geographical position equal to 1400kWh, with the optimal sensor orientation angle of 25° in the Gjakova Region. The solar radiation efficiency for one-year period has resulted in increased performance under sensor monitoring during the months of March - September, from 0.89 kWh/m2/y to 0.92 kWh/m2/y, when the equinox provides the longest sunlight intervals.

Improved state estimation of a robot end-effector using laser tracker and inertial sensor fusion

An increased focus on automation in the aerospace industry has led to a demand for flexible manipulators that can achieve high trajectory following accuracy for tasks like machining, joining, and painting. These tasks require an accurate, real-time state estimation of the robot’s end-effector. Currently, the most accurate methods of estimating the end-effector state involve using high-end position and orientation sensors such as laser trackers and camera-based metrology systems and tend to focus on accurately estimating the end-effector position and orientation. This paper investigates the potential benefits and practical considerations in supplementing the data from these kinds of sensors with acceleration and angular velocity measurements obtained from an inertial measurement unit (IMU) to improve the overall robot end-effector state estimation including its velocity and angular acceleration. The sensor fusion is achieved using a Kalman Filter for motions with no rotation and using a Particle Filter for motions with rotation. Simulation results indicate that up to 95% improvement in velocity estimation accuracy, and up to 45% improvement in angular acceleration estimation accuracy can be achieved by fusing IMU data with laser tracker data. In addition, the paper analyzes the thresholds of sensor accuracy beyond which fusion no longer provides significant benefits. Finally, hardware experiments are conducted using a fusion of robot encoder data with IMU measurements. These experiments indicate up to 40% improvement in velocity estimation accuracy from the sensor fusion.

The Modeling of Magnetic Detection of Iron Oxide Nanoparticles in the Stream of Patient-Specific Artery With Stenotic Lesion: The Effects of Vessel Geometry and Particle Concentration

Magnetic nanoparticles (MNPs) prepared as stable colloidal suspensions dispersed in water have attracted special interest for biological applications. MNPs of iron oxide synthesized by a laser target evaporation (LTE) technique are excellent candidates for biomedical purposes. Magnetic fluid flowing through the blood vessel creates magnetic fields which can be detected by magnetic field sensor. In this work, the finite element method modeling (FEM) was used for calculation of the flow of ferrofluid containing magnetic iron oxide MNPs through a real coronary artery reconstructed from the routine angiography examination of a patient. The main objective of the study is to validate the possibility of the application of magnetic field sensor for the blood vessel geometry evaluation. The contribution of the magnetic susceptibility of MNPs, blood vessel diameter, and particular geometry as well as the orientation of the magnetic field sensor working on the principle of giant magnetoimpedance (GMI) were comparatively analyzed.

Automatic path planning for high performance measurement by laser plane sensors

The Fourth Industrial Revolution (4IR) has led to a wide development of laser sensors and their use in inspection processes to achieve high performance is becoming more and more common. High measurement performance implies high measurement quality of surfaces in a short time. Generally, the quality is evaluated on the basis of indicators such as noise and trueness. Recently, it has been found that these indicators are mostly affected by the scanning strategy defined by two main parameters: the scanning angle and distance. Indeed, the path planning of laser sensors ensuring a high level of quality is based on the definition of the scanning strategy allowing scanning well-known surfaces with reduced noise and trueness. In this paper, an original approach for the generation of automatic path planning is proposed. The originality lies in the high performance obtained by optimizing the quality and the measurement time based on the optimal path planning. First, the laser sensor is qualified in order to evaluate the quality indicators as a function of the scanning distance and angle. Configurations that provide better quality are determined. By analyzing all laser sensor orientations held by the CMM's rotating head, a set of minimum orientations allowing high quality measurement is determined based on an optimization algorithm regarding quality, accessibility, visibility and collision detection criteria. The laser sensor path is based on the determination of the path levels in each sensor orientation. An original method is proposed to generate the optimal levels guaranteeing a high quality in terms of scanning distance. The laser sensor crossing points are then calculated in each level. An improvement of the method is proposed through the connection of levels using connection lines. Finally, collisions are studied and fixed by adding translation points. The proposed approach is applied to a part defined by its CAD model. The path is generated and executed on the CMM with a laser sensor. The measurement performance is compared to previous approaches in the literature. The methodology allows an adapted planning and can be used for automated dimensional inspection.

Three-Dimensional Lower-Limb Kinematics from Accelerometers and Gyroscopes with Simple and Minimal Functional Calibration Tasks: Validation on Asymptomatic Participants.

The use of inertial measurement units (IMUs) to compute gait outputs, such as the 3D lower-limb kinematics is of huge potential, but no consensus on the procedures and algorithms exists. This study aimed at evaluating the validity of a 7-IMUs system against the optoelectronic system. Ten asymptomatic subjects were included. They wore IMUs on their feet, shanks, thighs and pelvis. The IMUs were embedded in clusters with reflective markers. Reference kinematics was computed from anatomical markers. Gait kinematics was obtained from accelerometer and gyroscope data after sensor orientation estimation and sensor-to-segment (S2S) calibration steps. The S2S calibration steps were also applied to the cluster data. IMU-based and cluster-based kinematics were compared to the reference through root mean square errors (RMSEs), centered RMSEs (after mean removal), correlation coefficients (CCs) and differences in amplitude. The mean RMSE and centered RMSE were, respectively, 7.5° and 4.0° for IMU-kinematics, and 7.9° and 3.8° for cluster-kinematics. Very good CCs were found in the sagittal plane for both IMUs and cluster-based kinematics at the hip, knee and ankle levels (CCs > 0.85). The overall mean amplitude difference was about 7°. These results reflected good accordance in our system with the reference, especially in the sagittal plane, but the presence of offsets requires caution for clinical use.

Magnetoacoustic waves controlled by in-plane uniaxial magnetic anisotropy

Controlling the magnetoacoustic wave transmission with various equivalent magnetic fields is a key technology for future hybrid surface acoustic wave (SAW) devices. In this work, we experimentally and theoretically display acoustically driven spin wave resonance in Ni films with in-plane uniaxial magnetic anisotropy at an arbitrary angle relative to the SAW vector. Our experimental results show that by adjusting the angle between the hard axis and the SAW vector, we achieve the excitation of magnetoacoustic waves in any in-plane orientation. Moreover, we clearly prove that the anisotropic effective field can be utilized to optimize the applied field configuration for driving magnetoacoustic waves and design orientation sensors due to the angle-sensitive performance of acoustic spin wave resonance.

Free-Surface Velocity Measurement Using Direct Sensor Orientation-Based STIV.

Particle image velocimetry (PIV) is a quantitative flow visualization technique, which greatly improves the ability to characterize various complex flows in laboratory and field environments. However, the deployment of reference objects or ground control points (GCPs) for velocity calibration is still a challenge for in situ free-surface velocity measurements. By combining space-time image velocimetry (STIV) with direct sensor orientation (DSO) photogrammetry, a laser distance meter (LDM)-supported photogrammetric device is designed, to realize the GCPs-free surface velocity measurement under an oblique shooting angle. The velocity calibration with DSO is based on the collinear equation, while the lens distortion, oblique shooting angle, water level variation, and water surface slope are introduced to build an imaging measurement model with explicit physical meaning for parameters. To accurately obtain the in situ position and orientations of the camera utilizing the LDM and its embedded tilt sensor, the camera’s intrinsic parameters and relative position within the LDM are previously calibrated with a planar chessboard. A flume experiment is designed to evaluate the uncertainty of optical flow estimation and velocity calibration. Results show that the proposed DSO-STIV has good transferability and operability for in situ measurements. It is superior to propeller current meters and surface velocity radars in characterizing shallow free-surface flows; this is attributed to its non-intrusive, whole-field, and high-resolution features. In addition, the combined uncertainty of free-surface velocity measurement is analyzed, which provides an alternative solution for error assessment when comparing measurement failures.