Position Trajectory Research Articles

Polynomial Attitude Trajectory Planning for Spacecraft with Movable Parts Using Decoupled Strategy

The problem of attitude planning for spacecraft with movable parts under complex pointing constraints is addressed in this paper. To avoid tackling the complex pointing constraints in the high-dimensional system, a novel decoupled strategy is proposed to map the pointing space to the attitude space. Path-planning algorithm Rapidly-exploring Random Tree (RRT)*-Smart is employed in pointing space to generate a collision-free pointing path, and piecewise quintic polynomials are used to represent the attitude path. By proving the differential flatness of spacecraft with movable parts, the inverse dynamics is used to acquire attitude state trajectory in state space. Benefiting from the decoupled strategy, the attitude state trajectory is optimized by a new heuristic time allocation algorithm using binary search with no gradient information needed. The simulation results are discussed, and the performance during each scenario is analyzed.

Empirical demonstration of the Matthew effect in scientific research careers

The Matthew effect qualitatively describes the social phenomenon that the impact and recognition of well-known scientists for their new accomplishments are relatively overpriced by the scientific community when compared to the similar output of researchers without fame or status. We quantify the manifestation of this phenomenon in scientific research careers. For this purpose, using a mixed survey-plus-bibliometrics method, we assembled a dataset containing detailed career information on scientists in the field of chemistry. The mathematical model of the Matthew effect in scientific research careers proposed in this paper identifies career distribution as the generalized extreme value distribution with the shape parameter q=0.5. This result is in good agreement with the obtained data: the empirical distribution of scientific careers can be approximated by the generalized extreme value distribution with q=0.423. We also find that the distribution of starting positions of social trajectories of scientists fits by the Pareto distribution. Our analysis deepens scientific insight into the emergence of the Matthew effect in scientific careers and its relationship to the distribution of citations and citation entropy.

Mode transition prescribed performance control of connected hybrid electric vehicles based on driver intention fuzzy prediction

A novel hierarchical mode transition control (NHMTC) algorithm utilizing traffic information is investigated for realizing a superior dynamic and ride comfort performance of a connected hybrid electric vehicle (CHEV). The upper level includes the target vehicle velocity planning by model predictive control (MPC) considering less vehicle jerk based on the vehicle-to-infrastructure (V2I) information and the driving intention prediction by a type-2 fuzzy neural network (T2FNN) model using the planned target velocity. The lower level involves the automatic clutch system’s prescribed performance fixed-time controller (PPFTC) design and the desired velocity of the clutch engagement calculated by the predicted driving intention to improve the clutch position trajectory’s tracking accuracy and stability under the actual mode transition process. The comparison results with existing schemes under a co-simulation environment demonstrate the advantage and effectiveness of the designed NHMTC method.

Improved ShuffleNetV2 for Action Recognition in BPPV Treatment

In clinical examination and repositioning for BPPV(benign paroxysmal positional vertigo), analyzing the head position trajectory at the algorithm level to obtain information on each examination and repositioning posture helps to provide guidance for subsequent treatment, which has important practical value in clinical applications. This paper uses the improved ShuffleNetV2 on the basic the data obtained by the swivel chair for action recognition, and locates the interval where the action occurs. Specific network improvements include: the introduction of the SE channel attention block, which improves the performance of the network with a small amount of parameters and computation; the Hardswish activation function is used instead of ReLU in the original network; by reducing the layers in the network, deleting the second 1*1 convolution in the right branch of the downsampling block, and changing the kernel size of the DW convolution, the network can be lightweight while maximizing the capability of action recognition. The network’s performance has been enhanced, resulting in an accuracy of 98.53% with only 71,444 parameters and 15.76M FLOPs, while maintaining a recognition speed of 97.1 images per second. It achieves a good balance between speed and accuracy, enabling it to effectively accomplish the task of action recognition.

Trajectory Kinematics Control for a Robotis Bioloid Premium Arm

This paper addresses the problem of trajectory tracking in one arm of the Bioloid Premium humanoid robot. The kinematics modeling of the left arm was obtained using the Denavit-Hartenberg methodology. A kinematics control strategy based on state feedback and Input-Output Linearization technique was employed to achieve accurate tracking of the desired trajectories. A C language code was written to reprogram the CM-530 controller of the Bioloid Premium to allow it to interpret and execute the trajectory positions. In addition, wireless communication was established using ROS as the development platform. The experimental results demonstrate the success of the proposed approach in applying kinematic control on the robotic arm, offering an accurate and advanced alternative to the mobility options natively enabled by the ROBOTIS software.

Assembly of low-stiffness parts through admittance control with adaptive stiffness

Existing studies on robot assembly mostly focus on high-stiffness metal parts, which are unsuitable for assembling low-stiffness parts. Additionally, when assembly is achieved by the conventional admittance control method, the number of parameters to be adjusted is significant, and unstable contact force may occur. This study proposes two algorithms, namely admittance control with variable stiffness (ACVS) and admittance control with adaptive stiffness (ACAS), which are suitable for robotic assembly of low-stiffness parts. The proposed ACVS is achieved without a position trajectory, which reduces the number of parameters that need to be adjusted by the user. Furthermore, overshoot is suppressed by calculating the stiffness parameter in real time. The ACAS scheme adjusts the stiffness value in ACVS through a multilayer feedforward neural network; therefore, its overshoot is lower than that of ACVS, and the contact force stability is enhanced. The ACAS scheme thus characterized by a slight overshoot and stable contact force enables stable assembly of low-stiffness parts via the maximum force generated by the robot.

Kehidupan Keagamaan Anak Ulama (Studi Kasus di Kecamatan Seunagan Kabupaten Nagan Raya)

Ulama are people who are pious and have an important and strategic position in the historical trajectory of the people of Aceh. Every generation needs scholars as protectors and guides for the community in various aspects of life, especially in the field of religion, so it is necessary to have successors who will continue this role in each generation. And theoretically, the children of these scholars are seen as having a chance to continue this continuity. In the early decades of the 21st century in Seunagan District, Nagan Raya Regency, there were seven well-known scholars and they had 18 sons who were considered able to continue their father's roles in the past. However, in this study only 5 people (27.70%) were found to be scholars, while 13 people (62.30%) did not become scholars. This is caused by several factors; including family factors, education and environmental factors.

A GES joint position trajectory tracking smooth controller of torque‐driven robot manipulators affected by disturbances

SummaryThis paper presents a controller for joint position tracking of torque‐driven robot manipulators affected by torque disturbances. In particular, the proposed approach allows concluding global exponential stability (GES) of the state‐space origin of the closed‐loop system when constant disturbances affect the robot dynamics. Besides, when time‐varying disturbances are presented, the trajectories of the closed‐loop system are proven to be bounded as result of the input‐to‐state stability. The main contribution is the design of the control law and a nonlinear observer based on an alternative energy shaping approach. The nonlinear observer is designed to compute and compensate for unknown disturbances, whether they are constant or time‐varying. Furthermore, a detailed stability analysis of the closed‐loop system based on Lyapunov theory and input‐to‐state stability is presented. As far as the authors know, this is the first energy‐shaping controller for trajectory tracking control of robot manipulators affected by constant disturbances that achieves global exponential stability. Real‐time experiments on a manipulator arm of two degrees‐of‐freedom illustrate the performance of the proposed controller.

Volitional EMG Control Enables Stair Climbing with a Robotic Powered Knee Prosthesis.

Existing controllers for robotic powered prostheses regulate the prosthesis speed, timing, and energy generation using predefined position or torque trajectories. This approach enables climbing stairs step-over-step. However, it does not provide amputees with direct volitional control of the robotic prosthesis, a functionality necessary to restore full mobility to the user. Here we show that proportional electromyographic (EMG) control of the prosthesis knee torque enables volitional control of a powered knee prosthesis during stair climbing. The proposed EMG controller continuously regulates knee torque based on activation of the residual hamstrings, measured using a single EMG electrode located within the socket. The EMG signal is mapped to a desired knee flexion/extension torque based on the prosthesis knee position, the residual limb position, and the interaction with the ground. As a result, the proposed EMG controller enabled an above-knee amputee to climb stairs at different speeds, while carrying additional loads, and even backwards. By enabling direct, volitional control of powered robotic knee prostheses, the proposed EMG controller has the potential to improve amputee mobility in the real world.

The Influence of Screw Positioning on Cage Subsidence in Patients with Oblique Lumbar Interbody Fusion Combined with Anterolateral Fixation.

Cage subsidence (CS) has been reported to be one of the most common complications following oblique lumbar interbody fusion (OLIF). To reduce the incidence of CS and improve intervertebral fusion rates, anterolateral fixation (AF) has been gradually proposed. However, the incidence of CS in patients with oblique lumbar interbody fusion combined with anterolateral fixation (OLIF-AF) is still controversial. Additionally, there is a lack of consensus regarding the optimal placement of screws for OLIF-AF, and the impact of screw placement on the incidence of CS has yet to be thoroughly investigated and validated. The objective of this investigation was to examine the correlation between screw placements and CS and to establish an optimized approach for implantation in OLIF-AF. A retrospective cohort study was undertaken. From October 2017 to December 2020, a total of 103 patients who received L4/5 OLIF-AF for lumbar spinal stenosis or spondylolisthesis or degenerative instability in our department were followed up for more than 12 months. Demographic and radiographic data of these patients were collected. Additionally, screw placement related parameters, including trajectory and position, were measured by anterior-posterior X-ray and axial CT. Analysis was done by chi-square, independent t-test, univariable and multivariable binary logistic regression to explore the correlation between screw placements and CS. Finally, the receiver operating characteristic (ROC) curve analysis was used to evaluate the predictive ability of screw placement-related parameters. A total of 103 patients were included, and CS was found in 28 (27.18%) patients. Univariable analysis was firstly performed for each parameter. Next, variables with p-value of <0.05, including bone mineral density (BMD), concave morphology, and screw placement-related parameters were included in the multivariate logistic regression analysis. Significant predictor factors for subsidence were coronal plane angle (CPA) (OR 0.580 ± 0.208, 95% CI 1.187-2.684), implantation point (IP) (L4) (OR 5.732 ± 2.737, 95% CI 1.445-12.166), and IP (L5) (OR 7.160 ± 3.480, 95% CI 1.405-28.683). Furthermore, ROC curves showed that the predictive accuracy of CS was 88.1% for CPA, 77.6% for IP (L4) and 80.9% for IP (L5). We demonstrate that the trajectory of vertebral screws, including angle and position, was closely related to CS. Inserting screws parallel to each other and as close to the endplate as possible while keeping the cage inside the range of the superior and inferior screws are an optimal implantation strategy for OLIF-AF.

Design of nonlinear control system for motion trajectory of industrial handling robot

AbstractIndustrial robot is a and multi‐output complex system with strong coupling and high nonlinearity. The motion control accuracy of the system is affected by many factors. To solve the difficulty in establishing the input and output characteristics of robot dynamics modeling, the robot motion model is established through the Lagrangian energy function. At the same time, the nonlinear relationship between angular velocity, angular acceleration, and robot torque is accurately expressed through improved cascaded neural network. In addition, the optimal time planning of the robot's trajectory in joint space is studied using multinomial interpolation method and the particle swarm optimization (PSO). In the simulation experiment, the effect of the proposed dynamic model fitting was outstanding. Under the mixed multinomial difference calculation planning, the angular position trajectories of the three joints changed very smoothly. In the data set application test, the average error of the PSO algorithm was 0.4061 mm and the average task time was 9.101 s, which were lower than other planning algorithms. Experiments showed that the Lagrangian dynamic model analysis based on genetic algorithm cascaded neural network and PSO trajectory scheduling method under mixed multinomial difference had better trajectory planning performance in handling tasks.

Task Assignment Optimization in Multi-UAV-Assisted WSNs Considering Energy Budget and Sensor Distribution Characteristics.

In emergency situations, such as disaster area monitoring, deadlines for data collection are strict. The task time minimization problem concerning multi-UAV-assisted data collection in wireless sensor networks (WSNs), with different distribution characteristics, such as the geographical or importance of the information of the sensors, is studied. Our goal is to minimize the mission time for UAVs by optimizing their assignment, trajectory, and deployment locations, while the UAV energy constraint is taken into account. For the coupling relationship between the task assignment, trajectory, and hover position, it is not easy to solve the mixed integer non-convex problem directly. The problem is divided into two sub-problems: (1) UAV task assignment problem and (2) trajectory and hover position optimization problem. To solve this problem, an assignment algorithm, based on sensor distribution characteristics (AASDC), is proposed. The simulation results show that the collection time of our scheme is shorter than that of existing comparison schemes when using the same data size.

Magnetic signature reproduction of ferromagnetic ships at arbitrary geographical position, direction and depth using a multi-dipole model

The reproduction of magnetic signatures is an important issue concerning the safety of ship traffic, as well as the identification and classification of vessels. Moreover, military applications of magnetic signatures and their reproduction refer to the activation or protection against activation of magnetic naval mines. Previous works on this subject focused on recording and replicating the signatures under the same conditions as those under which they were measured, e.g., on the same ship courses. In this article, much greater capabilities of the multi-dipole model are presented, including simultaneous identification of permanent and induced magnetism. Determining the dipole values using the data from cardinal directions gives the possibility of determining the magnetic field density at any trajectory (position), direction, or depth, with further reconstruction of the entire magnetic field on the basis of residual measurements. For the purpose of this article, a numerical test model of a corvette-type ship has been modelled in Opera simulation software for different geographical positions. The synthetic data from the simulator served as the data source for determining the parameters of the multi-dipole model and the reference data for the verification of the signatures reconstructed for other positions, directions, and depths than those used to determine the model parameters. To determine all permanent magnetization components, data sets were used for two different values of the external magnetic field vertical component. Finally, as a culmination of the demonstration of model universality, the entire magnetic field around the ship was reproduced for different control points on Earth, and for different courses and depths. Investigating the possibility of reconstructing the magnetic signature at a different geographic location than the place where the measurement was made for model synthesis is the main original issue considered in this paper.

Multivariable Linear Position Control Based on Active Disturbance Rejection for Two Linear Slides Coupled to a Mass

Active Disturbance Rejection Control (ADRC) is a promising approach that has emerged to deal with uncertainties, which has received many practical applications in motion controls. This paper presents a multivariable controller for active disturbance rejection (ADR) based on an extended state linear observer for tracking the linear position trajectory of a mass moved by two linear slides, each one driven by a DC motor. The linear extended state observer is used to estimate the endogenous and exogenous disturbances of the system, which are assumed to be unknown, but bounded. Therefore, the feedback system prevents each actuator from operating at different forward speeds, and thus a synchronization between the two actuators is achieved by moving the common mass smoothly. The simulation and the experimental results show the effectiveness and robustness of the controller proposal when moving the mass with both actuators.

Neural-optimal tuning of a controller for a parallel robot

In this article, a double strategy is proposed to find the optimal gains of a cascaded PI controller to minimize the trajectory position error in a five-bar parallel robot. The first strategy employs Differential Evolution to tune constant gains during the execution time of the desired trajectory. Once Differential Evolution achieves convergence on the solution by finding the vector of optimal gains that minimize the position tracking error, all the position error data and current of the two brushless motors are saved. In the second strategy, the data generated in the first strategy is used to train a Deep Neural Network. After that, the trained Deep Neural Network replaces the constant gains of the first strategy with time-varying gains for the desired trajectory. Three working scenarios are proposed to test the generalization of the Deep Neural Network. In the first scenario, a training trajectory is executed. In the second one, a testing trajectory of the Deep Neural Network is evaluated. In the third one, a mass change is generated in the middle of the cycle. The results show that the Deep Neural Network is robust to different trajectories and mass changes during the execution of pick and place tasks.

Time-optimal attitude planning for spacecraft with movable parts using second order cone programming

The objective of this paper is to plan a time-optimal attitude trajectory in a relatively short time for spacecraft with movable parts under complex pointing constraints. The constrained attitude planning problem is first established, then the constraints on attitude maneuvers are described. The time-optimal attitude planning for rigid spacecraft body is decoupled into geometric level and dynamic level through the addition of the path scalar. To obtain a given safe path in quaternion space, RRT*-Smart path planning and spherical and quadrangle (SQUAD) interpolation are carried out at the geometric level. The time-optimal parameterization for a given path is reformulated as a second order cone programming (SOCP) problem at the dynamic level through a nonlinear change in variables and the addition of various convexity-preserving extensions. In order to overcome the issue of high system dimension caused by the movable parts, a decoupled attitude planning method is designed to generate the quaternion trajectory of the spacecraft body and the rotation angle trajectory of the movable parts respectively. In comparison to GPOPS, the simulation results demonstrate that the proposed method can plan a suboptimal solution in milliseconds. Furthermore, the performance indicator for energy consumption is better.

The evolution of flame geometrical characteristics and air entrainment of inclined jet flames

This paper reported the jet fire issuing from different angles, a common hazard in pipeline leakage accidents during the gas storage and transportation process. The flame geometrical profiles including flame projection length in the horizontal direction, vertical height from the nozzle position and flame trajectory length as the essential parameters to evaluate jet fire risk and design safety distance between process equipment were measured experimentally. The result shows that flame projection length in the horizontal direction first increases to a maximum value at the horizontal jet flame condition and then decreases, flame vertical height from the nozzle position increases monotonously and the length of flame trajectory first decreases and then increases with the increasing inclined angle from downward to upward. Then, the normalized flame trajectory and its length for different inclined jet flames were obtained by plotting the flame tip location parameters normalized by a characteristic length representing the interaction between jet flow momentum and buoyant force generated by temperature variation. Finally, the air entrainment coefficients for different inclined jet flames were quantified by an integral model derived from the conservation equations showing a trend of first increase and then decrease with the increasing inclined angle from negative to positive. This work provides a good reference for quantifying the flame size of jet flame in inclined conditions.

Conditioned adaptive barrier-based double integral super twisting SMC for trajectory tracking of a quadcopter and hardware in loop using IGWO algorithm

Researchers working in the field of unmanned aerial vehicles are observing rapid developments in the field, such as the use of quadrotors to grasp, manipulate, and transport objects. These advancements are made possible through sophisticated control systems, new types of actuation and sensing technologies, and a greater understanding of the aerodynamic effects and gyroscopic moment generated by the rotating blades of the quadrotor involved. Therefore, this research work proposes four novel optimized control laws, i.e., conditioned adaptive barrier-based double integral super twisting sliding mode controller (CABDIST-SMC), BF double integral SMC (BF-DISMC), BF integral SMC, and barrier function-based SMC control laws, for attitude, heading, position, and altitude trajectory tracking of the quadcopter. The non-linear model of the quadcopter is developed using the Lagrange formalism in MATLAB ODE-45 environment, including the gyroscopic moments and aerodynamic effects, and a Lyapunov stability analysis is performed to ensure the asymptotic stability of the system. A 3D-helical complex trajectory is employed to analyze the performance and consistency of the proposed optimized controllers. For performance comparison, the proposed four variants of the SMC are compared with three traditional control strategies, i.e., backstepping SMC, optimized adaptive SMC via particle swarm optimization algorithm, and improved adaptive SMC. These traditional control strategies have also been developed and tested in MATLAB-Simulink. All the controllers are optimized using the improved grey wolf optimization algorithm, and to determine the best control law, six performance indexes, i.e., mean absolute percentage error (MAPE), root mean square error (RMSE), integral square error (ISE), integral absolute error (IAE), integral time absolute error (ITAE), and integral time square error (ITSE) are used. A hardware-in-loop (HIL) test is also performed to validate the performance of the designed novel control law. The C2000 Delfino MCU F28379D launchpad is used for performing the HIL validation test. The simulated results showed that the performance of optimized CABDIST-SMC surpassed all other control laws for altitude, heading, position, and attitude trajectory tracking. It has achieved MAPE of 0.02%, RMSE of 3.9912e−5, ISE of 3.1859e−8, IAE of 7.9823e−4, ITAE of 0.0080, and ITSE of 3.1849e−7 in case of yaw angle control. The proposed control laws have successfully passed the HIL validation test, and real-time implementation of the proposed control laws indicates no significant variations compared to the simulated results.

Simulation of a metal pellet spraying generator driven by micro-air pressure

Molten metal droplet techniques are one of the important technologies for printing micro-metal parts. At present, the equipment developed for this technology faces some challenges, such as the requirement for a micro-oxygen environment during operation and a complicated manufacturing process. Consequently, a micro-air-pressure driven metal pellet spraying (MPS) 3D printing generator was designed and manufactured using the drop-on-demand technique, which uses simple and low-cost equipment in an atmospheric environment. A 2D axisymmetric model has been proposed to study the mechanism of droplet generation by using a micro-pneumatic MPS generator. In addition, a proprietary pneumatic MPS generator was also used to conduct droplet generation experiments. The validity of the proposed model was verified through the simulation results of the droplet pattern and droplet diameter, which were in good agreement with the experimental ones. The analysis shows that in the droplet injection forming process, surface tension is dominant for low viscosity liquids at a very small Ohnesorge number (Oh &amp;lt; 0.01). The surface tension was conducive to the maintenance of the molten form of the projectile. During droplet injection, the phenomenon of oblate–prolate oscillation occurs due to the non-uniform distribution of pressure inside the droplet. This phenomenon exerts an influence on the accuracy of the droplet flight trajectory and deposition position. This study serves as a good reference for selecting the suitable settings for producing metal droplets using the MPS generator.

A Synthesized Sliding-Mode Control for Attitude Trajectory Tracking of Quadrotor UAV Systems

This article presents a practical synthesized sliding-mode control (SSMC) scheme and, then, applies it to quadrotor unmanned aerial vehicle (UAV) systems. A new adaptive law is developed to be suitable for real applications with small moment of inertia such as quadrotor UAV systems that become more sensitive to abrupt and external disturbances. Since it is designed to respond to both sliding variables and time-delayed estimation errors, it makes the switching gains provide remarkably fast convergence rate and high robustness while compensating for abrupt and external disturbances. Besides, the proposed SSMC scheme works together with the pole-placement control to enhance the system stability while yielding the desirable closed-loop dominant poles. Also, the proposed control scheme employs one-sample delayed information to cancel out the system uncertainties and disturbances so that it makes a simple and compact structure. It is shown that attitude trajectory tracking errors of the proposed SSMC scheme are guaranteed to be bounded by the bounded-input bounded-output stability theory. The practical effectiveness and feasibility of the proposed control scheme are illustrated in real implementation with a quadrotor UAV system, which are compared with those of the existing control schemes.