Attitude Error Research Articles

Design of Motion Attitude Measurement System and Correction Method in Semi‐Airborne Frequency Domain Electromagnetic Detection

In the semi‐airborne frequency domain electromagnetic detection, strong noise will be generated due to the attitude change of the receiving coil sensor. However, the existing attitude measurement system cannot be directly used in the semi‐airborne frequency domain electromagnetic system because of the requirement on the volume and accuracy of the instrument. In order to reduce the effect of attitude noise, this paper analyzes the cause and influence of attitude noise in the semi‐airborne frequency domain electromagnetic system, and presents the attitude noise correction method based on coefficient rotation matrix and Kalman algorithm. A high‐performance attitude sensor based on (Micro‐Electro‐Mechanical System (MEMS) technology is used to design an attitude measurement system for the semi‐airborne frequency domain electromagnetic system. The calculated result shows that the required accuracy of the roll angle and pitch angle of the attitude measurement system is less than 0.1°, whereas the required accuracy of the yaw angle is lower. In the field application, the apparent resistivity results show that the imaging profile corrected by attitude error is more consistent with local geological data than that without correction. Consequently, the attitude measurement system and correction method proposed in this paper can improve the detection accuracy of the semi‐airborne frequency domain electromagnetic system significantly. © 2024 Institute of Electrical Engineer of Japan and Wiley Periodicals LLC.

Adaptive Predefined-Time Attitude Stabilization Control of Space Continuum Robot

This brief investigates the predefined-time stabilization attitude control for multi-segment cable-driven space continuum robot system in the presence of external time-varying disturbances. By utilizing the theorem of practical predefined-time stability, an adaptive attitude controller based on a nonsingular terminal sliding mode is developed, so that the attitude error can converge into a small neighborhood of the origin within a predefined time. A suitable Lyapunov function is chosen to prove the stability of the robot system. The numerical simulation results demonstrate the effectiveness and superiority of the proposed control strategy.

An unmanned aerial vehicle light detection and ranging Simultaneous Localisation And Mapping algorithm based on factor graph optimisation for tunnel 3D mapping

AbstractThe current mature Simultaneous Localisation And Mapping (SLAM) algorithms, when applied to tunnel scenarios with point cloud degradation and poor lighting conditions, often lead to a sharp increase in the estimated attitude error of the unmanned aerial vehicle (UAV), or even prevent the UAV from moving autonomously due to severe feature degradation. To address the above problems, the authors propose a SLAM algorithm based on factor graph optimisation, Iterative Closest Point and Normal Distributions Transform algorithms. A front‐end point cloud registration module and a back‐end construction algorithm based on filtering and graph optimisation are designed. To verify the effectiveness of the proposed algorithm, experiments are conducted on KITTI dataset and real tunnel scenes, and compared with LiDAR Odometry and Mapping (LOAM) and lightweight and ground optimised (LeGO)‐LOAM algorithms. The results show that the average processing time of the proposed method is about 75 ms, which can meet the real‐time requirements of autonomous aerial vehicles. Compared with LOAM and LeGO‐LOAM in the real tunnel experiment, the proposed method shows the tunnel 3D map construction.

Hitchhiker: A Quadrotor Aggressively Perching on a Moving Inclined Surface Using Compliant Suction Cup Gripper

Perching on the surface of moving objects, like vehicles, could extend the flight time and range of quadrotors. Suction cups are usually adopted for surface attachment due to their durability and large adhesive force. To seal on a surfaces, suction cups must be aligned with the surface and possess proper relative tangential velocity. However, quadrotors’ attitude and relative velocity errors would become significant when the object surface is moving and inclined. To address this problem, we proposed a real-time trajectory planning algorithm. The time-optimal aggressive trajectory is efficiently generated through multimodal search in a dynamic time-domain. The velocity errors relative to the moving surface are alleviated. To further adapt to the residual errors, we design a compliant gripper using self-sealing cups. Multiple cups in different directions are integrated into a wheel-like mechanism to increase the tolerance to attitude errors. The wheel mechanism also eliminates the requirement of matching the attitude and tangential velocity. Extensive tests are conducted to perch on static and moving surfaces at various inclinations. Results demonstrate that our proposed system enables a quadrotor to reliably perch on moving inclined surfaces (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">$1.07m/s$</tex-math> </inline-formula> and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$90^\circ$</tex-math> </inline-formula> ) with a success rate of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$70\%$</tex-math> </inline-formula> or higher. The efficacy of the trajectory planner is also validated. Our gripper has larger adaptability to attitude errors and tangential velocities than conventional suction cup grippers. The success rate increases by 45% in dynamic perches. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —This paper was motivated by the problem of perching on moving inclined surfaces using quadrotors. It can be used for perching on the various angled surfaces of an automobile to save energy and enlarge flight distance. It can also be exploited in air-ground cooperative tasks. In recent years, various grippers and trajectory planning methods have been devised to enable quadrotors to perch on static inclined surfaces. These strategies can not be used for perching on moving inclined surfaces. The task poses high requirements for the efficiency of trajectory planning and the grippers’ adaptability to pose errors. This paper proposes a real-time planning method to generate trajectories. The trajectories respect kinematic and motor lift constraints. They allow large attitude maneuvering of quadrotors. A multimodal search in a dynamic time-domain is developed to seek the minimum feasible time for the trajectory planner. Considering large pose errors in dynamic perching, a compliant gripper based on multiple independent suction cups is designed. The wheel and multidirectional layout of cups increase the adaptability to attitude and velocity errors. Results suggest that the proposed system is effective and reliable. In practice, our multiple cups would add weight penalty and increase the drag. The suction cups should be placed close to a quadrotor’s central axis to reduce the drag and disturbance in flow. The proposed system relies on an external motion capture system. In future research, we will focus on onboard sensing and control methods to achieve perching on moving inclined surfaces outdoors.

Analysis of Attitude Errors Effect on the Measurement of Interferometric Radar Altimeter Based on the Imaging Principle

Analysis of Attitude Errors Effect on the Measurement of Interferometric Radar Altimeter Based on the Imaging Principle

Analysis of Repetitive Positioning Accuracy of Parallel Mechanisms Based on Monte Carlo Method

Based on the inverse kinematics model of the Stewart parallel mechanism, a motion platform pose error model was constructed through differential transformation. The error model shows that the motion platform pose error comes from the length error of 6 struts and the position error of 12 hinge centers, with a total of 42 error terms. Monte Carlo simulation was used to analyze the effects of struts length error on the pose error of the moving platform. The results show that when the length error of the struts follows a normal distribution, the posture error of the moving platform approximately follows a normal distribution. Monte Carlo simulation is a highly effective error analysis method that can analyze the error distribution pattern of the mechanism before processing and assembly, which provides a method for error analysis of Stewart parallel mechanisms.

Rotation matrix-based finite-time trajectory tracking control of AUV with output constraints and input quantization

This study investigated a rotation-matrix-based finite-time trajectory tracking problem for autonomous underwater vehicles (AUVs) in the presence of output constraints, input quantization, and uncertainties. First, a rotation matrix-based attitude representation is introduced, which allow attitude dynamics to be globally and uniquely represented without unwinding. To satisfy the finite-time stability of AUV tracking control and the output constraints imposed by introducing the new attitude error vector, a novel finite-time command-filtered backstepping controller (FTCFBC) is proposed based on the asymmetrical time-varying barrier Lyapunov function (TVBLF). Subsequently, a second-order auxiliary dynamic system (ADS) is proposed to estimate the negative effects that of input quantization errors. Because the quantized control inputs can be switched at an appropriate earlier or later switching timing depending on the output of the ADS, the negative impact of quantization errors on the control accuracy is reduced. Moreover, an adaptive finite-time disturbance observer (AFTDO) is developed to estimate the lumped uncertainties without prior information on the bounds of the uncertainties. Finally, the results of the theoretical analysis verified that the tracking errors can converge within a finite time. Numerical simulations confirmed the effectiveness of the proposed control scheme.

Fixed-time nonsingular adaptive attitude control of spacecraft subject to actuator faults

In this article, a fixed-time adaptive fault-tolerant control approach is presented for the attitude tracking of rigid spacecraft subject to inertia uncertainties, external disturbances, and actuator faults. The designed controller is developed as a combination of the fixed-time integral sliding mode control and parametric adaptation technique. The fixed-time integral sliding mode controller has no singularity problem naturally by constructing a novel integral sliding mode surface based on the bi-limit homogeneous method. Moreover, the parametric adaptation technique is incorporated to estimate the total uncertainty indirectly. Benefiting from this development, the designed controller is smooth with no obvious chattering phenomenon and does not require any information on the upper bound of the total uncertainty. The attitude and angular velocity tracking errors under the designed controller can regulate to the minor fields about zero in fixed time. A remarkable feature of the designed controller is that it is not only robust against inertia uncertainties and external disturbances, but also insensitive to multiple types of actuator faults. Finally, simulation results show the effectiveness and merits of the presented control approach.

Optimal Pose Estimation and Covariance Analysis with Simultaneous Localization and Mapping Applications

This work provides a theoretical analysis for optimally solving the pose estimation problem using total-least-squares for vector observations from landmark features, which is central to applications involving simultaneous localization and mapping. First, the optimization process is formulated with observation vectors extracted from point-cloud features. Then, error-covariance expressions are derived. The attitude and position estimates obtained via the derived optimization process are proven to reach the bounds defined by the Cramér–Rao lower bound under the small-angle approximation of attitude errors. A fully populated observation noise-covariance matrix is assumed as the weight in the cost function to cover the most general case of the sensor uncertainty. This includes more generic correlations in the errors than previous cases involving an isotropic noise assumption. The proposed solution is verified using Monte Carlo simulations, a Gazebo simulation in a robotics operating system, and an experiment with an actual light detection and ranging sensor to validate the error-covariance analysis.

Attitude control of multi-spacecraft systems on SO(3) with stochastic links failure

In this paper, for Multi-Spacecraft System (MSS) with a directed communication topology link and a static virtual leader, a controller is proposed to realize attitude consensus and attitude stabilization with stochastic links failure and actuator saturation. First, an MSS attitude error model suitable for a directed topology link and with a static virtual leader based on SO(3) is derived, which considers that the attitude error on SO(3) cannot be defined based on algebraic subtraction. Then, we design a controller to realize the MSS on SO(3) with attitude consensus and attitude stabilization under stochastic links failure and actuator saturation. Finally, the simulation results of a multi-spacecraft system with stochastic links failure and a static virtual leader spacecraft are demonstrated to illustrate the efficiency of the attitude controller.

Hierarchical Error Compensation Method for Two-Degree-of-Freedom Manipulator Positioning Error in Hybrid Robots

In this paper, taking a two-degree-of-freedom parallelogram serial manipulator of a hybrid robot as an example, a hierarchical error compensation method that combines geometric and non-geometric error compensation is proposed. First, we establish the geometric kinematic modeling and error model and use the Levenberg-Marquardt (L-M) method to identify the geometric error parameters. Then, we use the grid interpolation method to compensate for non-geometric errors, thereby improving the overall positioning accuracy of the manipulator. Finally, a simulation is presented to verify the correctness and effectiveness of the proposed method. The results show that the positioning accuracy is improved from 4.8568 mm to 0.0036 mm, and the attitude error is improved from 0.9437° to 0.0105°.

Robust spacecraft relative pose estimation via CNN-aided line segments detection in monocular images

Autonomous spacecraft relative navigation via monocular images became a hot topic in the past few years and, recently, received a further push thanks to the constantly growing field of artificial neural networks and the publication of several spaceborne image datasets. Despite the proliferation of spacecraft relative-state initialization algorithms developed, most architectures adopt computationally expensive solutions relying on convolutional neural networks (CNNs) that provide accurate output at the cost of a high computational burden that seems unfeasible for current spaceborne hardware. The paper addresses this issue by proposing a novel pose initialization algorithm based on lightweight CNNs. Inspired by previous state-of-the-art algorithms, the developed architecture leverages a fast and accurate target detection CNN followed by a line segment detection CNN capable of running with low inference time on mobile devices. The line segments and their junctions are grouped into complex geometrical groups, reducing the solution search space, and subsequently, they are adopted to extract the final pose estimate. As a main outcome, the analyses demonstrate that the lightweight architecture developed scores high accuracy in the pose estimation task, with a mean estimation error of less than 10 cm in translation and 2.5°in rotation. The baseline algorithm scores a mean SLAB error of 0.04552 with a standard deviation of 0.22972 in the test dataset. Detailed analyses demonstrate that the uncertainties on the overall pose score are driven mainly by errors in the relative attitude, which gives the highest contribution to the pose error metric adopted. The analyses on the error distributions point out that the uncertainties on the estimated relative position are higher in the camera boresight axis direction. Concerning the relative attitude, the algorithm proposed has higher uncertainties in estimating directions of the target x and y axes due to ambiguities related to the target geometry. Notably, the target detection CNN trained in this work outperforms the previous top scores in the benchmark dataset. The performances of the proposed algorithm have been investigated further by analyzing the effects on the accuracy due to the relative distance and the presence of background in the images. Lastly, the paper delves into the possibility of adopting a sub-portion of the 2D-to-3D match matrix made by the most complex perceptual groups identified that positively affects the overall run-time, pointing out the performances in terms of accuracy of the estimates and providing a comparison of both the baseline and the reduced match matrix versions against state-of-the-art algorithms concerning relative position and attitude errors and solution availability, highlighting the high accuracy and solution availability of the proposed architectures.

Kinematics Parameter Calibration of Serial Industrial Robots Based on Partial Pose Measurement

The kinematics parameter error is the main error factor that affects the absolute accuracy of industrial robots. The absolute accuracy of industrial robots can be effectively improved through kinematics calibration. The error model-based method is one of the main methods for calibrating the kinematics parameter error. This paper presents a kinematics parameter calibration method for serial industrial robots based on partial pose measurement. Firstly, the kinematics and the pose error models have been established based on the modified Denavit–Hartenberg (MDH) model. By introducing the concept of error sensitivity, the average significance index is proposed to quantitatively analyze the effects of the kinematics parameter error on the pose error of a robot. The results show that there is no need to measure the full pose error of the robot. Secondly, a partial pose measurement device and method have been presented. The proposed device can measure the position error and the attitude error on the x-axis or y-axis. Finally, the full pose error model, the NP-type partial pose error model, and the OP-type partial pose error model have been applied for calibrating the kinematics parameter errors. The experimental results show that the effectiveness of the OP-type partial pose error model is consistent with the full pose error model.

Research on Positioning Accuracy of Mobile Robot in Indoor Environment Based on Improved RTABMAP Algorithm

Visual simultaneous localization and mapping is a widely used technology for mobile robots to carry out precise positioning in the environment of GNSS technology failure. However, as the robot moves around indoors, its position accuracy will gradually decrease over time due to common and unavoidable environmental factors. In this paper, we propose an improved method called RTABMAP-VIWO, which is based on RTABMAP. The basic idea is to use an Extended Kalman Filter (EKF) framework for fusion attitude estimates from the wheel odometry and IMU, and provide new prediction values. This helps to reduce the local cumulative error of RTABMAP and make it more accurate. We compare and evaluate three kinds of SLAM methods using both public datasets and real indoor scenes. In the dataset experiments, our proposed method reduces the Root-Mean-Square Error (RMSE) coefficient by 48.1% compared to the RTABMAP, and the coefficient is also reduced by at least 29.4% in the real environment experiments. The results demonstrate that the improved method is feasible. By incorporating the IMU into the RTABMAP method, the trajectory and posture errors of the mobile robot are significantly improved.

Spacecraft attitude reorientation control method based on potential function under complex constraints

A large number of sensors carried by spacecraft are facing the risk of irradiation, which may lead to the failure of sensors and affect the mission of the spacecraft. Therefore, it is significant to make the sensor work safely by attitude maneuvers. This article proposes a guidance algorithm for the attitude reorientation of rigid spacecraft, which aims to reduce the conservativeness of the traditional potential function and to solve the problem of the goal being non reachable with obstacles nearby (GNRON). While the rationality of the form design of the potential function is analyzed from the view of numerical calculation, a modified inverse-proportional potential function is designed based on it. Additionally, the anti-unwinding attitude error function is established to avoid the unwinding phenomenon of quaternions. In this paper, a set of weight assignment schemes for the potential function is proposed to obtain the maneuver path close to the edge of the attitude-forbidden zone, which reduces the conservativeness and energy consumption compared with the traditional method. Finally, the scheme can also solve the GNRON phenomenon. In the fourth section, the form design of the potential function is studied by numerical simulation, and the performance of the proposed algorithm is shown by comparative experiments.

A Roadheader Positioning Method Based on Multi-Sensor Fusion

In coal mines, accurate positioning is vital for roadheader equipment. However, most roadheaders use a standalone strapdown inertial navigation system (SINS) which faces challenges like error accumulation, drift, initial alignment needs, temperature sensitivity, and the demand for high-quality sensors. In this paper, a roadheader Visual–Inertial Odometry (VIO) system is proposed, combining SINS and stereo visual odometry to adjust to coal mine environments. Given the inherently dimly lit conditions of coal mines, our system includes an image-enhancement module to preprocess images, aiding in feature matching for stereo visual odometry. Additionally, a Kalman filter merges the positional data from SINS and stereo visual odometry. When tested against three other methods on the KITTI and EuRoC datasets, our approach showed notable precision on the EBZ160M-2 Roadheader, with attitude errors less than 0.2751° and position discrepancies within 0.0328 m, proving its advantages over SINS.

Detumbling of Underactuated Tethered Satellite System Based on Hierarchical Sliding Mode Control

Millions of space debris pose a significant risk to operational spacecraft, making active debris removal (ADR) missions an urgent priority. Net capturing is a promising method to remove space debris objects due to its multiple advantages. However, once a target has been captured, a combined tethered system comprising the chaser, the target, and the tethers is formed, which requires effective stabilization. In this paper, stabilization of the entire postcapture system is realized by solely controlling the active chaser satellite. Such a control strategy can attenuate system hardware facilities compared with those by applying additional tether control such as using a winding mechanism, which were mostly discussed in the literature. Further, for the first time, considering the uncertainties during the capture process, including inaccurate target parameters, initial attitude error of the target, and external disturbances, a hierarchical sliding mode controller (HSMC) with two sublayers is developed to detumble this underactuated system. Additionally, a hybrid position controller is proposed to eliminate the undesired swing motion within the system. Numerical simulations demonstrate that HSMC method delivers better performance over the proportional-derivative controller in efficiency and robustness for postcapture stabilization of the combined tethered system. Overall, our proposed control strategy offers a promising solution for future ADR missions, contributing to a safer and more sustainable space environment.

Work Posture Analysis with REBA and RULA Method on Production Operators Repair and Maintenance of LPG 3Kg at PT. XYZ

Wrong posture while working has an impact on productivity. One of them is the operator's work position in the production department at PT. XYZ pays little attention to natural work attitudes and there are activities that have a fairly high ergonomic risk. As a result, complaints such as pain in the legs, shoulders, knees, neck and even the arms occur. At worst, it can lead to long-term sprains and fractures. It is necessary to analyze work posture using the Rapid Entire Body Assessment (REBA) and Rapid Upper Limb Assessment (RULA) methods to determine the level of musculoskeletal hazards and provide improvements to work methods or rearrangement of the work environment. The final score results in the application of REBA and RULA are on the working posture of the both painting sections with scores of 4 and 9, on screen printing on the bottom of the tube scores of 9 and 10, on ring painting results of scores of 10 and 9, on welding results of scores of 7 and 8, and on the installation of seal tape the results of scores 5 and 6 which need to be repaired immediately. Recommendations are given by changing work postures, adding tables and chairs. The operator's attitude and work position are calculated again using the REBA and RULA checksheets. The result is 3 and 3 both painting, 3 and 3 on tube bottom screen printing, 2 and 3 on ring painting, 2 and 3 on welding, 2 and 2 on seal tape installation, which are (acceptable) or acceptable. Keywords: Working Posture Error, REBA, RULA.

Pedestrian Inertial Positioning Method Based on Foot Quasi-Zero Velocity Observation Under Multiple Motion Modes

As the traditional zero velocity update (ZUPT) algorithm based on fixed threshold is difficult to solve the problem of effective positioning for pedestrians under multiple motion modes, a simpler, flexible and stable inertial positioning algorithm is proposed in this paper. A foot kinematic model based on rotating “L" shaped rigid body is proposed to describe the process from heel landing to heel off the ground. The quasi-zero velocity interval (QZVI) of foot motion is defined, and a method to determine the QZVI based on peak detection and gait cycle constraint is proposed to avoid the dependence of system on predetermined threshold. The proposed foot kinematic model is used to calculate the “near zero" velocity in the QZVI. Then difference between the calculated “near zero" velocity and the inertial navigation solution velocity is used as the observation of Kalman filter to estimate the position error, velocity error and attitude error of inertial navigation system (INS). Experiments show that the proposed algorithm has positioning error relative to the mileage of less than 2% under the mileage of 500m or less, effectively adapting to different motion modes such as fast walking, slow walking and running, so as to realize the accurate autonomous positioning under the condition of multiple motion modes.

Orbit-attitude-structure coupled modelling method in local translational coordinate frame for multibody systems

The absolute coordinate-based (ACB) method, including absolute nodal coordinate formulation and natural coordinate formulation, is a widely-used dynamic modelling method for multibody systems. However, the problem of accuracy loss would arise when multi-scale motions are described in the same global coordinate system, such as large-scale orbital motions, small-scale attitude motions and structural vibrations, and micro-scale contact/collision. To address this problem, an ACB method in local translational coordinate system is proposed such that the large-scale orbital motions can be separated from other smaller-scale motions. The dynamic equations are derived by the Hamilton's equations and the Kronecker product. The validity of the proposed method is studied using an orbit-attitude coupled model of an orbiting rigid plate. It is found that the attitude errors of the original ACB method increase as time step size decreases. The reason for this counterintuitive phenomenon is that more serious accuracy loss is encountered for smaller time step size. In addition, more iterations are required for the original ACB method to obtain the prescribed tolerable error in each time step due to accuracy loss. In comparison, the proposed method is more accurate and efficient in numerical simulations. Finally, the proposed method is applied to the orbit-attitude-structure coupled simulation of a space robotic system.