Angular Trajectory Research Articles

Differential drive kinematics and odometry for a mobile robot using TwinCAT

<abstract><p>In this paper, we propose a motion control system for a low-cost differential drive mobile robot. The robotic platform is equipped with two driven wheels powered by Beckhoff motors, instrumented with incremental encoders. The control system is designed and implemented using Beckhoff's TwinCAT 3 automation software, running on an industrial PC. The system is tested and experimentally tuned to achieve optimal performance. The method allows addressing both odometry motion accuracy and motion correction in order to obtain minimum trajectory errors. Test results on linear and angular robot trajectories show errors below 0.02 and 0.03%, respectively, after tuning of the motion parameters. The proposed approach can be expanded, tweaked and applied to other differential drive TwinCAT 3 based robotic solutions. This will contribute to expanding mobile robot applications to a variety of fields, such as industrial automation, logistics, warehouse management, health care, ocean and space exploration and a variety of other industrial and non-industrial activities.</p></abstract>

Robust Control Based on a Time-varying UDE for an Under-actuated 3-DOF Helicopter

The UDE (uncertainty and disturbance estimator) based control approach has received increasing attention in recent years due to its simplicity and effectiveness to attenuate the influence of uncertainties and disturbances. Despite this fact, the trade-off issue of its steady-state performance and transient performance has not been addressed explicitly. A novel time-varying UDE (TV-UDE) is proposed to resolve the trade-off issue in this paper. The main idea behind the design is to use a differential equation with a time-varying parameter, rather than a transfer function, to represent the underlying filtering relationship. By changing the UDE gain smoothly, the performance limitations of a fixed-gain UDE are avoided. Moreover, the TV-UDE is reduced to a classic UDE when its parameter value is finally frozen. Two design specifications are provided to guide the design of the time-varying parameter. We then apply this design to the angular trajectory tracking problem of a 3-DOF helicopter model, and reveal the four time-scales property of the closed-loop dynamics. The advantages of the proposed approach are shown by simulation comparisons.

FRACTIONAL ORDER PIλDμ FOR TRACKING CONTROL OF A NOVEL REHABILITATION ROBOT BASED ON IIMO-BP NEURAL NETWORK ALGORITHM

In this study, we develop a novel multi-posture lower limb rehabilitation robot with three postures, which can provide different amplitudes and frequencies of rehabilitation training for hip, knee and ankle joints, respectively. The kinematic and dynamic analyses of the robot are carried out to solve the kinematic forward and backward solutions and the Lagrangian dynamics equations of the lower limbs. The angle, angular velocity and angular acceleration ideal trajectory curves of the rehabilitation motion are derived by using a quintic polynomial trajectory planning scheme. An improved ions motion optimization (IIMO) algorithm is proposed and applied to optimize the initial weight of back propagation (BP) neural network, and algorithm is used to adjust five parameters of fractional order [Formula: see text] ([Formula: see text]) control in controller design. The passive training experiment results of prototype show that the designed controller has the largest average error of angle and angular velocity of hip, knee and ankle joints in high amplitude and high frequency movement mode, which are 1.091∘, 0.716∘, 0.412∘, 1.551∘/s, 1.394∘/s, 1.498∘/s, respectively. At low amplitude and low frequency, the maximum average errors are the smallest, which are 0.351∘, 0.341∘, 0.167∘; 0.833∘/s, 0.842∘/s, 0.398∘/s, respectively. The actual trajectory curve fits well with the designed one. The highest accuracy of angle and angular velocity can reach 99.165% and 99.116% through comprehensive comparison of all motion modes. Therefore, the overall error is small. The stability of rehabilitation training process is ensured, and the rationality and effectiveness of trajectory planning and control design are verified.

What Is Next in Computer-Assisted Spine Surgery? Advances in Image-Guided Robotics and Extended Reality

Background: This article provides a scoping review on the current status of Image-Guided Navigation with various forms of digital technologies, including Extended Reality, Augmented Reality Head-Mounted Displays (AR–HMDs) and Robot-Assisted Surgery (RAS) for Pedicle Screw Placement in orthopedics and spine surgery. Methods: A scoping literature review was performed in the PubMed, Scopus, Embase, Web of Science, Google Scholar and IEEE Xplore databases to collect clinical and user satisfaction data on AR–HMDs and compare those with RAS outcomes. In vivo patient, cadaver and phantom trial accuracy data reports were identified and grouped through the analysis. Over the past two years, 14 publications were retrieved and analyzed. Pedicle screw placement accuracy was described with Linear Tip Error (LTE), Angular Trajectory Error (ATE) and Gertzbein–Robbins Scale (GRS) outcomes. Results: The Pedicle Screw Placement accuracy was seen to increase in the in vivo, cadaver and phantom model groups using AR-HMD compared to the Free-Hand insertion technique. User experience and satisfaction data were limited; however, a clear advantage for the operative results was described when it was added. RAS screwing showed similar accuracy outcomes. The need for benchmarking and quantified situation awareness for AR–HMDs is recognizable. The authors present a method for standardized scoring and visualization of surgical navigation technologies, based on measurements of the surgeon (as the end-users) user satisfaction, clinical accuracy and operation time. Conclusions: computer-technology driven support for spine surgery is well-established and efficient for certain procedures. As a more affordable option next to RAS, AR–HMD navigation has reached technological readiness for surgical use. Ergonomics and usability improvements are needed to match the potential of RAS/XR in human surgeries.

Markerless Motion Capture System Based on Webcams Using OpenPose

Recently, webcam-based motion capture systems have attracted tremendous attention as alternative low-cost motion analysis tools, owing to the rapid advancement of markerless technologies. Although the upper and lower limbs are moved simultaneously in most function activities in daily life, most existing studies focused on kinematic data observed in the hip and knee joints during gait. The purpose of this study was to measure the kinematic data of the upper and lower limb simultaneously during modified squat, using low-cost webcams and to compare them to those of the 3D marker-based motion capture system. The modified squat was performed nine times in total without rest in between. The modified squat consisted of hip and knee flexion with elbow flexion. During modified squat, the kinematic data were collected using 4 RGB cameras and 13 Vicon cameras. The positions of the joints were obtained using OpenPose and the 3D positions were reconstructed using OpenCV. Angular trajectories from the Vicon motion capture system tended to be very similar to the ones from the webcam-based motion capture system. There was no significant difference in the kinematic data at the elbow between two different capture systems. Additionally, the minimum joint angles at the hip and knee were not significantly different. It was confirmed that the markerless motion capture system based on webcam can measure angular joint motions at the same level as the Vicon 3D motion capture system with markers. The webcam-based motion capture system will enhance the usability in clinical settings.

Angular Trajectory Design for MR-SPS Using Bezier Shaping Approach

Solar power satellite (SPS) is a kind of large-scale on-orbit servicing spacecraft collecting solar energy in space and transmitting energy to the earth. The solar arrays of the SPS must point to the sun to collect enough solar energy and the antenna must point to the rectenna on the ground to transmit energy. But due to the limitation of the control effort, accurate solar and earth orientation may not be achieved. This paper focuses on the MR-SPS, and establishes the attitude kinematics and dynamics model of a MW-level MR-SPS. Angular trajectory based on Bezier shaping approach is generated at different time of a year to satisfy the control constraints. The simulation results demonstrate the effectiveness of the proposed method. Even if the control torque is limited to a small amount, the optimal angular trajectory can still ensure high average energy receiving efficiency.

Validation of Magneto-Inertial Measurement Units for Upper-Limb Motion Analysis Through an Anthropomorphic Robot

Kinematic analysis of human movement is paramount for medical and working scenarios, such as rehabilitation or ergonomic evaluation of workers. Recent studies in the state-of-the-art highlight the importance of assessing the performance of M-IMUs as tools for objective kinematic analysis before exploiting them in any context. This work aims at proposing a method grounded on the use of an anthropomorphic robot, to characterize the behavior of M-IMUs for specific frequency and amplitude ranges, typical of human upper limb movements. The use of a robot allows generating controlled and repeatable angular trajectories, thus providing a gold standard to evaluate the capability of the sensors to accurately track target angular trajectories. The Root Mean Square Error is adopted as a performance indicator. An experimental validation of the proposed method is carried out on two different sets of M-IMUs. The 87.96% and 71.30% of the performed trials exhibit errors lower than 0.087 rad for the WISE and Xsens sensors, respectively. The proposed workflow can be exploited to characterize the sensor behavior for different applications as well as the sensor fusion algorithms implemented into the measurement unit.

The difference in the corridor of the antegrade posterior column screw according to the presence of pelvic dysmorphism

IntroductionAntegrade posterior column screw (aPCS) fixation via the anterior approach has been widely used for separated the posterior columns in acetabular fracture treatment. Although the relationship between pelvic dysmorphism and sacroiliac screws has been widely studied, no studies have reported on the clinical impact of pelvic dysmorphism on acetabular fractures. This study aimed to reveal the difference in the insertion angle and entry point of aPCS between the dysmorphic and normal pelvises. MethodsPatients diagnosed with unilateral acetabular fractures and who underwent pelvic computed tomography scans between 2013 and 2019 in two institutes were enrolled in this study. Patients were divided into the dysmorphic and control groups according to the sacral dysmorphic score, which predicts the presence of pelvic dysmorphism, and each group enrolled 130 patients. The semitransparent 3D hemipelvis model was reconstructed using a 3D reconstruction program. The sagittal and coronal angles of a virtual cylinder that fill the safe corridor of the column screw the most were measured. The surface area of the safe corridor and distance of the optimal entry point from the anterior border of the sacroiliac joint were analyzed. The measurements were compared between the dysmorphic and control groups. ResultsThe average sacral dysmorphic score in the normal and dysmorphic pelvis groups was 56.1 and 81.0, respectively. There were no significant differences in demographic data, including age, sex, height, weight, and body mass index, between the dysmorphic and control groups. There was a significant difference in the average sagittal insertion angle of PCs, which was 38.3° in the control group and 27.2° in the dysmorphic group (P < 0.001). The coronal insertion angles were not significantly different. The dysmorphic group presented longer straight distances (25.9 vs 24.8 mm, P = 0.026) and had a smaller aPCS surface area (685 vs 757 mm2, P < 0.001) than the control group. ConclusionThe present study describes a difference in the corridor of aPCS between the dysmorphic and normal pelvis. Insertion of aPCS in the dysmorphic pelvis requires a more acute angular trajectory in the sagittal plane than that in the normal pelvis.

Ga2O3-Based Solar-Blind Position-Sensitive Detector for Noncontact Measurement and Optoelectronic Demodulation

As a kind of photodetector, position-sensitive-detectors (PSDs) have been widely used in noncontact photoelectric positioning and measurement. However, fabrications and applications of solar-blind PSDs remain yet to be harnessed. Herein, we demonstrate a solar-blind PSD developed from a graphene/Ga2O3 Schottky junction with a 25-nanometer-thick Ga2O3 film, in which the absorption of the nanometer-thick Ga2O3 is enhanced by multibeam interference. The graphene/Ga2O3 junction exhibits a responsivity of 48.5 mA/W and a rise/decay time of 0.8/99.8 μs at zero bias. Moreover, the position of the solar-blind spot can be determined by the output signals of the PSD. Using the device as a sensor of noncontact test systems, we demonstrate its application in measurement of angular, displacement, and light trajectory. In addition, the position-sensitive outputs have been used to demodulate optical signals into electrical signals. The results may prospect the application of solar-blind PSDs in measurement, tracking, communication, and so on.

Kinematic trajectories in response to speed perturbations in walking suggest modular task-level control of leg angle and length.

Navigating complex terrains requires dynamic interactions between the substrate, musculoskeletal and sensorimotor systems. Current perturbation studies have mostly used visible terrain height perturbations, which do not allow us to distinguish among the neuromechanical contributions of feedforward control, feedback-mediated and mechanical perturbation responses. Here, we use treadmill belt speed perturbations to induce a targeted perturbation to foot speed only, and without terrain-induced changes in joint posture and leg loading at stance onset. Based on previous studies suggesting a proximo-distal gradient in neuromechanical control, we hypothesized that distal joints would exhibit larger changes in joint kinematics, compared to proximal joints. Additionally, we expected birds to use feedforward strategies to increase the intrinsic stability of gait. To test these hypotheses, seven adult guinea fowl were video recorded while walking on a motorized treadmill, during both steady and perturbed trials. Perturbations consisted of repeated exposures to a deceleration and acceleration of the treadmill belt speed. Surprisingly, we found that joint angular trajectories and center of mass fluctuations remain very similar, despite substantial perturbation of foot velocity by the treadmill belt. Hip joint angular trajectories exhibit the largest changes, with the birds adopting a slightly more flexed position across all perturbed strides. Additionally, we observed increased stride duration across all strides, consistent with feedforward changes in the control strategy. The speed perturbations mainly influenced the timing of stance and swing, with the largest kinematic changes in the strides directly following a deceleration. Our findings do not support the general hypothesis of a proximo-distal gradient in joint control, as distal joint kinematics remain largely unchanged. Instead, we find that leg angular trajectory and the timing of stance and swing are most sensitive to this specific perturbation, and leg length actuation remains largely unchanged. Our results are consistent with modular task-level control of leg length and leg angle actuation, with different neuromechanical control and perturbation sensitivity in each actuation mode. Distal joints appear to be sensitive to changes in vertical loading but not foot fore-aft velocity. Future directions should include in vivo studies of muscle activation and force-length dynamics to provide more direct evidence of the sensorimotor control strategies for stability in response to belt speed perturbations.

Boat Detection in Marina Using Time-Delay Analysis and Deep Learning

An autonomous acoustic system based on two bottom-moored hydrophones, a two-input audio board and a small single-board computer was installed at the entrance of a marina to detect entering/exiting boat. Windowed time lagged cross-correlations are calculated by the system to find the consecutive time delays between the hydrophone signals and to compute a signal which is a function of the boats' angular trajectories. Since its installation, the single-board computer performs online prediction with a signal processing-based algorithm which achieved an accuracy of 80 %. To improve system performance, a convolutional neural network (CNN) is trained with the acquired data to perform real-time detection. Two classification tasks were considered (binary and multiclass) to both detect a boat and its direction of navigation. Finally, a trained CNN was implemented in a single-board computer to ensure that prediction can be performed in real time.

Application of the PSO for the construction of a 3-axis stable magnetically actuated satellite angular motion

Particle swarm optimization (PSO) is a non-gradient biologically inspired global optimization method. It utilizes direct calculation of the optimized cost function during the numerical simulation of the process in question. Significantly complex and implicit functions that prohibit clear gradient expression are effectively handled by PSO. This feature is utilized in the paper to construct specific angular trajectory of a magnetically actuated satellite. A cost function is suggested that confines the control torque corresponding to this trajectory to the plane orthogonal to the geomagnetic induction vector. Optimal trajectory coefficients are found by PSO. The control structure is based on the Lyapunov feedback approach and explicitly accommodates the gravitational and aerodynamic torques influence. PSO procedure provides the optimal control gains on this stage. Stability of the resulting motion is demonstrated. Numerical simulation example with different disturbance factors illustrates the expected stabilization accuracy of the order of few degrees.

ASTEMA: Design and preliminary performance assessment of a novel tele-microsurgery system

To overcome the challenges of reconstructive microsurgery, a teleoperated robot called ASTEMA was built to help surgeons performing microanastomoses. The surgeons’ needs are first analyzed then the design steps are summarized. This robot is composed of three orthogonal linear actuators and a spherical wrist with its remote center of motion at the instrument tip. Geometric model of the spherical wrist was calibrated through mathematical optimization in order to compensate for imperfections of machining and assembling. Two preliminary experiments were carried out to assess the ASTEMA performance. The first was performed with a simple circular position trajectory. The second was a complex angular trajectory. Results show a significant improvement of gesture precision with respect to manual trajectory execution. They also show that subjects instinctively compensate the errors from the non-ideal wrist, thanks to visual feedback from microscope.

Virtual constraint control of Knee-Ankle prosthesis using an improved estimate of the thigh phase-variable

In the human gait cycle, virtual constraints enforce a robust relationship between the thigh phase-variable and the knee/ankle angle. These constraints enable an accurate estimation and control of angular trajectory when the input phase-variable profile is low in gait aperiodicity and sensor noise. In this work, we present discrete Fourier transform (DFT) based virtual constraint schemes for estimating the knee/ankle trajectories using an improved monotonic and linear trajectory of the thigh phase-variable. To minimize the likely aberrations in the desired trajectory of the phase-variable, the contour of the thigh angle and its integral is amplitude scaled, time shifted, and interpolated over the complete stride. The processed contour is then refitted to an ideal circle using polynomial optimization via two different schemes. For both proposed schemes, estimated knee/ankle trajectories are compared with the benchmark gait kinematics of healthy persons and an amputee wearing three commercial prostheses. Simulation results, based on realistic prosthesis actuator parameters, show a 2.18 ± 0.83 times reduction in the mean trajectory tracking error for three contrasting walking speeds, validating the efficacy of proposed schemes.

A computer-vision method to estimate joint angles and L5/S1 moments during lifting tasks through a single camera

Weight lifting is a risk factor of work-related low-back musculoskeletal disorders (MSD). From the ergonomics perspective, it is important to measure workers’ body motion during a lifting task and estimate low-back joint moments to ensure the low-back biomechanical loadings are within the failure tolerance. With the recent development of advanced deep neural networks, an increasing number of computer vision algorithms have been presented to estimate 3D human poses through videos. In this study, we first performed a 3D pose estimation of lifting tasks using a single RGB camera and VideoPose3D, an open-source library with a fully convolutional model. Joint angle trajectories and L5/S1 joint moment were then calculated following a top-down inverse dynamic biomechanical model. To evaluate the accuracy of the computer-vision-based angular trajectories and L5/S1 joint moments, we conducted an experiment in which participants performed a variety of lifting tasks. The body motions of the participants were concurrently captured by an RGB camera and a laboratory-grade motion tracking system. The body joint angles and L5/S1 joint moments obtained from the camera were compared with those obtained from the motion tracking system. The results showed a strong correlation (r > 0.9, RMSE < 10°) between the two methods for shoulder flexion, trunk flexion, trunk rotation, and elbow flexion. The computer-vision-based method also yielded a good estimate for the total L5/S1 moment and the L5/S1 moment in the sagittal plane (r > 0.9, RMSE < 20 N·m). This study showed computer vision could facilitate safety practitioners to quickly identify the jobs with high MSD risks through field survey videos.

Modelling and Analysis of a Virtual Prototype of a Rotary Machine in MSC.ADAMS

The article presents an analysis of the virtual model of Laval (Jeffcott) rotor in the software environment MSC.ADAMS. The parameters describing the stability of the rotor operation were monitored and evaluated, i. j. critical angular velocity and trajectory of the rotor center of gravity (orbit). The results were compared with the values measured on the experimental equipment, as well as with the values obtained by analytical calculation. The paper further presents a simulation in which the second critical velocity was reached. The paper further presents a simulation in which the second critical velocity was reached.

PID Tuning Method Using Chaotic Safe Experimentation Dynamics Algorithm for Elastic Joint Manipulator

This paper proposed the chaotic safe experimentation dynamics algorithm (CSEDA) to regulate angular tracking and vibration of the self-tuning PID controller for elastic joint manipulators. CSEDA was a modified version of the safe experimentation dynamics algorithm (SEDA) that used a chaos function in the updated equation. The chaos function increased the exploration capability, thus improving the convergence accuracy. In this study, two self-tuning PID controllers were used to regulate the rotating angle tracking and vibration for elastic joint manipulators in this control challenge. The suggested self-tuning PID controller's performance was evaluated in angular motion trajectory tracking, vibration suppression, and the pre-determined control fitness function. A self-tuned PID controller based on CSEDA could achieve superior control accuracy than a traditional SEDA and its variants.

The compliance matrix method for the kinetostatic analysis of flexure-based compliant parallel mechanisms: Conventions and general force–displacement cases

In this paper, we present the mathematical formulation of the Compliance Matrix Method (CMM) for the kinetostatic analysis of Flexure-Based Compliant Mechanisms (FBCM). The formulation is achieved by integrating the different approaches found in literature, as an attempt of unification of the CMM. The CMM is combined with inverse kinematics in an analytical process, to be used in the kinetostatic analysis of Flexure-Based Compliant Parallel Mechanisms (FBCPM) with multiple actuation forces where the output displacements are not coincident, neither are parallel, with the input forces. This analytical process allows the total compliance matrix of the FBCPM to be obtained, which relates the input forces (commonly applied on the legs) with the output displacements (commonly desired in the moving platform). The effectiveness of the analytical process presented here, is validated using two FBCPM with Two-Dimensional and Three-Dimensional architectures as examples. Then, the analytical results are validated with Finite Element Analysis by comparing the capability of the FBCPM to follow complex trajectories: circular and angular trajectories for the 2D-FBCPM, and a spherical spiral trajectory for the 3D-FBCPM, showing excellent agreement (less than 5%).

Optimized Neural Networks-PID Controller with Wind Rejection Strategy for a Quad-Rotor

In this paper a full approach of modeling and intelligent control of a four rotor unmanned air vehicle (UAV) known as quad-rotor aircraft is presented. In fact, a PID on-line optimized Neural Networks Approach (PID-NN) is developed to be applied to angular trajectories control of a quad-rotor. Whereas, PID classical controllers are dedicated for the positions, altitude and speed control. The goal of this work is to concept a smart Self-Tuning PID controller, for attitude angles control, based on neural networks able to supervise the quad-rotor for an optimized behavior while tracking a desired trajectory. Many challenges could arise if the quad-rotor is navigating in hostile environments presenting irregular disturbances in the form of wind modeled and applied to the overall system. The quad-rotor has to quickly perform tasks while ensuring stability and accuracy and must behave rapidly with regards to decision making facing disturbances. This technique offers some advantages over conventional control methods such as PID controller. Simulation results are founded on a comparative study between PID and PID-NN controllers based on wind disturbances. These later are applied with several degrees of strength to test the quad-rotor behavior and stability. These simulation results are satisfactory and have demonstrated the effectiveness of the proposed PD-NN approach. In fact, the proposed controller has relatively smaller errors than the PD controller and has a better capability to reject disturbances. In addition, it has proven to be highly robust and efficient face to turbulences in the form of wind disturbances.

Kinematic differences between national and college level weightlifters during snatch technique

The aim of this study is to assess the suitability of a micro-processing unit of motion analysis (MPUMA), for monitoring, reproducing, and tracking upper limb movements. The MPUMA is based on an inertial measurement unit, a 16-bit digital signal controller and a customized algorithm. To validate the performance of the system, simultaneous recordings of the angular trajectory were performed with a video-based motion analysis system. A test of the flexo-extension of the shoulder joint during the active elevation in a complete range of 120º of the upper limb was carried out in 10 healthy volunteers. Additional tests were carried out to assess MPUMA performance during upper limb tracking. The first, a 3D motion reconstruction of three movements of the shoulder joint (flexo-extension, abduction–adduction, horizontal internal–external rotation), and the second, an upper limb tracking online during the execution of three movements of the shoulder joint followed by a continuous random movement without any restrictions by using a virtual model and a mechatronic device of the shoulder joint. Experimental results demonstrated that the MPUMA measured joint angles that are close to those from a motion-capture system with orientation RMS errors less than 3º.