Smooth Movements Research Articles

Coupled Motion Response Analysis for Dynamic Target Salvage under Wave Action

The strategic recovery of buoys is a critical task in executing deep-sea research missions, as nations extend their exploration of marine territories. This study primarily investigates the dynamics of remotely operated vehicle (ROV)-assisted salvage operations for floating bodies during the recovery of dynamic maritime targets. It focuses on the hydrodynamic coefficients of dual floating bodies in this salvage process. The interaction dynamics of the twin floats are examined using parameters such as the kinematic response amplitude operator (RAO), added mass, damping coefficient, and mean drift force. During the “berthing stage”, when the double floats are at Fr = 0.15–0.18, their roll and yaw Response Amplitude Operators are diminished, resulting in smoother motion. Thus, the optimal berthing speed range for this stage is Fr = 0.15–0.18. During the “side-by-side phase”, the spacing between the ROV and FLOAT under wave action should be approximately 0.4 L to 0.5 L. The coupled motion of twin floating bodies under the influence of following waves can further enhance their stability. The ideal towing speed during the “towing phase” is Fr = 0.2. This research aims to analyze the mutual influence between two floating bodies under wave action. By simulating the coupled motion of dual dynamic targets, we more precisely assess the risks and challenges inherent in salvage operations, thus providing a scientific basis for the design and optimization of salvage strategies.

Deep Learning based Road Traffic Assessment for Vehicle Rerouting: An Extensive Experimental Study of RetinaNet and YOLO Models

Currently, there is a notable prevalence of substantial traffic congestion and frequent vehicular accidents on roadways in contemporary times. Amalgamation of latest front-line technologies involving Internet of Things (IoT) and image classification has immense potential to advance the progress of a proficient traffic regulation system. To mitigate the occurrence of vehicular accidents, our research endeavors revolve around the comprehensive analysis of the prevailing road conditions. This meticulous examination allows us to effectively automate traffic routes orchestration, ensuring smooth vehicular movement across all lanes of the road network. The analysis of traffic patterns is conducted through the utilization of visual data images. The real time captured traffic images undergo processing using various object detection models named RetinaNet and the YOLO (You Only Look Once) models. A series of comparative evaluations suggests an improved traffic object identification capacity for the RetinaNet model as compared to all YOLO models.

Development and construction of a mechanized moving platform for human service

The purpose of the proposed article is the development and construction of a mechanized mobile platform for serving people, which is caused by the need to increase the safety of the operation of such technical means, in particular, in the case of the need for mass customer service. The methodology is based on search, research and creative approaches. The methods of development analysis, patent search, synthesis of technical solutions, simulation modelling was used. Scientific novelty. The study of the features of various approaches to the creation of effective mechanized moving platforms, the analysis of solutions and the dynamics of patenting made it possible to substantiate the directions of development of technical solutions and the prospects of developments. The authors proposed constructive solutions for mobile platforms, developed approaches to the technical implementation of increasing the safety of their operation, proposed energy-saving approaches aimed at reducing the energy consumption of mechanized means, which is especially relevant in the mass implementation of platforms for serving people. Research results. The article solves important safety issues of human service, in particular in the entertainment industry through the development of structural parts, drives and rules for the operation of mechanized moving platforms. Synthesized constructive solutions obtained in the course of patent research, analysis of modern technical solutions, rational technical design, and expert evaluation are presented. It was determined that the safety of the operation of mechanized moving platforms, which are intended for the transport of people in the field of tourism, depends on effective approaches to the design and components of the technical system in the form of a moving platform, its structural components, elements of its mechanism and the drive system as a whole, which with the optimization of technical indicators the stability of the overall system, the smoothness of movement and braking of the platform, the optimization of the materiality of the structure in total allow to have a qualitative effect on improving the safety of human operation.

High-Precision Measurement of Microscales Based on Optoelectronics and Image Integration Method.

Currently, there are various types of microscales and the conventional line detection system usually has only one detection method, which is difficult to adapt to the diverse calibration needs of microscales. This article investigates the high-precision measurement method of a microscale based on optoelectronics and the image integration method to solve the diversified calibration needs of microscales. The automatic measurement and processing system integrates two methods: the photoelectric signal measurement method and the photoelectric image measurement method. This article studies the smooth motion method based on ordinary linear guides, investigates the method of reducing the cosine error of a small-range interference length measurement, proposes an image-based line positioning method, and studies the edge and center recognition algorithms of the line. According to the experimental data, the system's measurement accuracy was analyzed using the photoelectric signal measurement method to measure the 1 mm microscale, the maximum difference from the reference value was 0.105 μm, the standard uncertainty was 0.068 μm, and the absolute value of normalized error was less than 1. The accuracy of the image measurement method to measure the 1 mm microscale was consistent with that of the photoelectric signal method. The results show good consistency in the measurement results between the two methods of the integrated measurement system. The photoelectric signal method has the technical characteristics of high measurement efficiency and high accuracy, while the pixel-based measurement of the image method has two-dimensional measurement characteristics, which can realize measurements that cannot be realized by the photoelectric signal method; therefore, the measurement system of optoelectronics and image integration is characterized by high precision and a wide range of measurement adaptations.

A Pneumatic Flexible Linear Actuator Inspired by Snake Swallowing.

Soft robots spark a revolution in human-machine interaction. However, developing high-performance soft actuators remains challenging due to trade-offs among output force, driving distance, control precision, safety, and compliance. Here, addressing the lack of long-distance, high-precision flexible linear actuators, an innovative pneumatic flexible linear actuator (PFLA) is introduced, inspired by the smooth and controlled process observed in snakes ingesting sizable food, such as eggs. This PFLA combines a soft tube, emulating the snake's body cavity, with a pneumatically driven piston. Through the joint modulation of moving resistance and driving force by pneumatic pressure, the PFLA exhibits exceptional motion control capabilities, including self-holding without pressure supply, smooth low-speed motion (down to 0.004 m s-1), high-speed motion (up to 5.6 m s-1) with low air pressure demand, and a self-protection mechanism. Highlighting its adaptability and versatility, the PFLA finds applications in various settings, including a wearable assistive devices, a manipulator capable of precise path tracking and positioning, and rapid transportation in diverse environments for pipeline inspection and firefighting. This PFLA combines biomimetic principles with sophisticated fluidic actuation to achieve long-distance, flexible, precise, and safe actuation, offering a more adaptive solution for force/motion transmission, particularly in challengingenvironments.

Thrust ball bearing fault identification from visualized data using optimized deep network

Bearings are the most common components employed in machine parts. The bearings' movement facilitates the smooth motion. They also help with friction reduction. The faults in bearings are often caused by tribological parameters. Various methods have been developed to identify faults in bearings, but they often fail to predict these accurately. This work has concentrated on designing an effective fault-recognizing model. Therefore, a framework, the Zebra-based Radial Basis Prediction Mechanism (ZbRBPM), was proposed in this work. Initially, the bearing datasets are collected, and mineral oil (MO) lubrication is added to minimize wear and friction. The primary goal of the work is to detect and classify the fault in the thrust ball bearing. The bearing vibration data included a normal vibration signal, a ball fault, and inner and outer race faults. Hence, Zebra fitness is enhanced for the optimization of tribological parameters and fault identification. The proposed model is executed in the MATLAB system. Finally, performance criteria like accuracy, precision, recall, F-score, error rate, computation time, speed, specific wear rate, friction torque, and energy consumption are validated. The performance of the proposed ZbRBPM gains better accuracy rate as 99.5 %, 99 % of precision and f-score and 99.4 % of recall. Also it significantly reduced the prediction error rate into 0.5 % with lower computation time and very low wear and friction.

Further insights into anti-IgLON5 disease: a case with complex clinical presentation

BackgroundAnti-IgLON5 disease is an autoimmune encephalitis overlapping with neurodegenerative disorders due to pathological accumulation of hyperphosphorylated tau. It is characterized by several clinical manifestations determined by involvement of different brain areas, and mild response to first-line immunotherapies. We report a case of anti-IgLON5 disease with a multifaceted semiology and an unusually good response to glucocorticoid monotherapy.Case presentationA 68-year-old man with type 2 diabetes was evaluated for an 8-month history of progressive gait disorder causing frequent falls. He also suffered from obstructive sleep apneas and complained of dysphonia, dysarthria, occasional dysphagia, urinary incontinence, and upper limb action tremor. Neurological examination demonstrated bilateral eyelid ptosis, limitation of ocular horizontal smooth pursuit movements, slow horizontal saccades, and lack of inhibition of the vestibulo-ocular reflex during rapid horizontal head torsions. The patient also displayed involuntary, slow, rhythmic movements of the left periorbital and perioral muscles, spreading to the ipsilateral hemipalate and hemitongue, along with bilateral negative upper limb myoclonus. There were proximal muscle wasting in the upper limbs, proximal weakness of the four limbs, and diffuse fasciculations. Ataxia of stance and gait and of the four limbs was noted. MRI of the brain and spine was unremarkable; nerve conduction studies revealed a chronic, predominantly demyelinating, sensory-motor polyneuropathy, probably due to diabetes. Routine CSF examination was unrevealing and serum GFAP level was 89.6 pg/mL; however, the autoimmunity tests revealed a high-titer positivity for anti-IgLON5 autoantibodies in both CSF and serum, leading to the diagnosis of anti-IgLON5 disease. Symptoms improved significantly after intravenous methylprednisolone.ConclusionsHemifacial and hemiorolingual myorhythmia along with peculiar oculomotor abnormalities characterizes the multifaceted clinical picture of our case. The complex semiology of our patient may reflect multifocal targeting of the autoimmune process or sequential spreading of tau inclusions in different brain areas. Our patient’s optimal response to glucocorticoid monotherapy could be underpinned by a slightly different phenotype in which autoimmunity plays a greater pathogenic role than tauopathy, with a lower burden of tau deposition. In such patients, neurodegeneration and tau accumulation could be merely secondary to immune-mediated neuronal dysfunction, supporting the existence of a group of glucocorticoid-responsive patients.

Perceived Trajectories of Cyclic Sound Movement

Binaural beats are a phenomenon that occurs during dichotic stimulation due to binaural integration. It takes the form of cyclic movement of the sound image in the listener’s acoustic space when the beat frequency range is below 3 Hz. Our subjects used the inserted earphones to listen to the stimuli that created a sense of sound movement due to changes in the interaural time difference (ITD). We used three types of dichotic stimuli which simulated smooth azimuthal cyclic movement and cyclic abrupt shifts. The ITD changes determined central or lateral positions of movement trajectories. The results confirm that both types of movement created the effect of binaural beats. The range of beats depended on the spatial position of the trajectory: in the frontal sector of acoustic space, the range of beats was greater than on the left or right. The perceived trajectories of smooth motion were shorter than the trajectories of abrupt shift. The influence of spatial position on the perceived trajectory length is interpreted from the standpoint of nonlinear features of lateralization. It is suggested that the effect of ITD pattern on the perceived trajectory length is mediated by temporal integration mechanisms of binaural hearing.

Fuzzy Logic-Based Autonomous Lane Changing Strategy for Intelligent Internet of Vehicles: A Trajectory Planning Approach

The autonomous lane change maneuver is a critical component in the advancement of intelligent transportation systems (ITS). To enhance safety and efficiency in dynamic traffic environments, this study introduces a novel autonomous lane change strategy leveraging a quintic polynomial function. To optimize the trajectory, we formulate an objective function that balances the time required for lane changes with the peak acceleration experienced during the maneuver. The proposed method addresses key challenges such as driver discomfort and prolonged lane change durations by considering the entire lane change process rather than just the initiation point. Utilizing a fifth-order polynomial for trajectory planning, the strategy ensures smooth and continuous vehicle movement, reducing the risk of collisions. The effectiveness of the method is validated through comprehensive simulations and real-world vehicle tests, demonstrating significant improvements in lane change performance. Despite its advantages, the model requires further refinement to address limitations in mixed traffic conditions. This research provides a foundation for developing intelligent vehicle systems that prioritize safety and adaptability.

Smooth joint motion planning for redundant fiber placement manipulator based on improved RRT*

In automated fiber placement (AFP), addressing the continuous motion planning challenge of redundant layup manipulators in complex environments, this paper proposes an offline redundancy optimization algorithm based on improved RRT* (Rapidly-exploring Random Trees). This algorithm maximizes the utilization of kinematic redundancy to derive smooth joint trajectories devoid of collisions and singularities. Firstly, the algorithm entails constructing a search map by eliminating joint configurations that violate constraints, and subsequently planning and optimizing the joint path by minimizing a multi-objective cost under the map constraint. Furthermore, several strategies are introduced to enhance RRT* for redundancy optimization. These strategies include a piecewise Gaussian sampling strategy (PGSS) to guide efficient tree growth within complex channels and enable joint sampling constrained by task coordinates. Additionally, the improved Steering and Local Optimization method are proposed to plan joint motion while considering intermediate task sequences. The effectiveness of the proposed algorithm is demonstrated in handling complex motion planning scenarios, such as layup involving complex path curves or dense obstacles. Experimental results validate the algorithm's capability to find feasible collision-free and singularity-free paths in relevant scenarios, provided such paths exist. Moreover, trajectory smoothness is optimized with increasing iterations.

Prediction of prognosis in supramalleolar osteotomy with or without additional fibula osteotomy by approaching a biomechanical study: a finite element analysis.

Supramalleolar osteotomy (SMO) is a representative procedure to restore a malalignment in the varus ankle deformity by shifting the concentrated pressure on the medial ankle joint to the lateral area. Additionally, fibula osteotomy (FO) is selectively selected and performed according to the surgeon's preference. However, it is controversial whether FO is effective in shifting the abnormal pressure from the medial to the lateral area on the ankle joint. Some cadaveric studies have been performed to prove this. However, it is difficult to consistently reconstruct amount of the varus ankle deformities angle in cadavers and to guarantee reliable contact pressure between the ankle joint. Thus, the aim of this study was predicted and quantitatively compared a peak pressure between single SMO and SMO with FO procedure by using a finite element analysis as a powerful biomechanical tool to those limitations of cadaveric study. This study reconstructed total 4 3D foot and ankle models including a normal and pre-op model and 2 post-op models. The pre-op model was modified by assigning 10° varus tilting corresponding to stage 3b in the classification of varus ankle osteoarthritis based on the validated normal model. Also, the post-op models were reconstructed by applying single SMO and SMO with FO, respectively. All of the models were assumed as one-leg standing position and to mimic smooth ankle joint motion. Peak contact pressure change was predicted at the medial ankle joint by using computational simulation. As a result, 2 post-op models showed a remarkably peak pressure reduction by up to 5.5 times on the medial tibiotalar joint. However, a comparison between single SMO and SMO with FO model showed no appreciable differences. In conclusion, this study predicted that single SMO may be as effective as SMO with FO in reducing peak contact pressure on the medial tibiotalar joint in varus ankle osteoarthritis.

Optimizing PID control for enhanced stability of a 16‐DOF biped robot during ditch crossing

AbstractThe current research article discusses the design of a proportional–integral–derivative (PID) controller to obtain the optimal gait planning algorithm for a 16‐degrees‐of‐freedom biped robot while crossing the ditch. The gait planning algorithm integrates an initial posture, position, and desired trajectories of the robot's wrist, hip, and foot. A cubic polynomial trajectory is assigned for wrist, hip, and foot trajectories to generate the motion. The foot and wrist joint angles of the biped robot along the polynomial trajectory are obtained by using the inverse kinematics approach. Moreover, the dynamic balance margin was estimated by using the concept of the zero‐moment point. To enhance the smooth motion of the gait planner and reduce the error between two consecutive joint angles, the authors designed a PID controller for each joint of the biped robot. To design a PID controller, the dynamics of the biped robot are essential, and it was obtained using the Lagrange–Euler formulation. The gains, that is, KP, KD, and KI of the PID controller are tuned with nontraditional optimization algorithms, such as particle swarm optimization (PSO), differential evolution (DE), and compared with modified chaotic invasive weed optimization (MCIWO) algorithms. The result indicates that the MCIWO‐PID controller generates more dynamically balanced gaits when compared with the DE and PSO‐PID controllers.

Analysis and control of an active balance tail for the tilting dual-rotor UAV

PurposeCompared to quad-rotor unmanned aerial vehicle (UAV), the tilting dual-rotor UAV is more prone to instability during exercises and disturbances. The purpose of this paper is using an active balance tail to enhance the hovering stability and motion smoothness of tilting dual-rotor UAV.Design/methodology/approachA balance tail is proposed and integrated into the tilting dual-rotor UAV to enhance hovering stability and motion smoothness. By strategically moving, the balance tail generates additional force and moment, which can promote the rapid stability of the UAV. Subsequently, the control strategy of the UAV is designed, and the influence of the swing of the balance tail at different installation positions with different masses on the dual-rotor UAV is analyzed through simulation. The accompany motion law and the active control, which is based on cascade Proportion Integration Differentiation (PID) control to enhance the hovering stability and motion smoothness of the UAV, are proposed.FindingsThe results demonstrate that active control has obvious adjustment effectiveness when the UAV moves to the target position or makes an emergency stop compared with the results of balance tail no swing and accompany motion.Practical implicationsThe balance tail offers a straightforward means to enhance the motion smoothness of tilting dual-rotor UAV, rendering it safer and more reliable for practical applications.Originality/valueThe novelty of this works comes from the application of an active balance tail to improve the stability and motion smoothness of dual-rotor UAV.

Flexible control and trajectory planning of medical two-arm surgical robot.

This paper introduces the flexible control and trajectory planning medical two-arm surgical robots, and employs effective collision detection methods to ensure the safety and precision during tasks. Firstly, the DH method is employed to establish relative rotation matrices between coordinate systems, determining the relative relationships of each joint link. A neural network based on a multilayer perceptron is proposed to solve FKP problem in real time. Secondly, a universal interpolator based on Non-Uniform Rational B-Splines (NURBS) is developed, capable of handling any geometric shape to ensure smooth and flexible motion trajectories. Finally, we developed a generalized momentum observer to detect external collisions, eliminating the need for external sensors and thereby reducing mechanical complexity and cost. The experiments verify the effectiveness of the kinematics solution and trajectory planning, demonstrating that the improved momentum torque observer can significantly reduce system overshoot, enabling the two-arm surgical robot to perform precise and safe surgical tasks under algorithmic guidance.

Intubating Laryngeal Mask Airway for Airway Management and Blind Tracheal Intubation Through It From 360° Around a Supine Patient: A Randomized Controlled Clinical Study in a Simulated Prehospital Emergency Scenario.

Introduction In emergency situations, airway management is often given priority over other treatment methods. The preferred technique for airway management of unconscious patients is endotracheal intubation, which has become the standard of care. Intubation of the trachea not only enables controlled ventilation even for extended periods and in any position but also allows for the removal of tracheal secretions. Supraglottic airways have several advantages over endotracheal intubation, including faster insertion,less need for neuromuscular blockade, and less hemodynamic instability. They can also be used as a bridge to intubation or as a rescue device when intubation fails or is contraindicated. The aim of this randomized controlled clinical study is to simulate a prehospital emergency/disaster scenario to evaluate and study the feasibility and effectiveness of the use of intubating laryngeal mask airway (ILMA) for onsite airway management from 360 degrees around the patient's head as in such situations, there may be limited or no access behind the head of the victim. Such a scenario can be extrapolated to disaster conditions where the victims may be trapped under the rubble following a building collapse /earthquake or are trapped in a vehicular road traffic/ train accident. It may take substantial time for extrication and evacuation of such patients to a hospital and hence it may be life-saving to provide prompt and early onsite airway management from wherever access is possible around the victim. We believe that the provision of a steel handle integrated with the airway tube may provide an opportunity for successful insertion of the device from 360 degrees around the patient merely by suitably changing the way the handle is gripped, so as to allow a single-handed smooth arc-like movement of the device for insertion, irrespective of the position of the rescuer relative to the patient's head. Objectives Our objective is to study the ease and time of insertion of ILMA, the number of attempts for successful ILMA insertion, and oropharyngeal leak pressure attained from unconventional positions in a supine patient. Materials and methods This prospective, randomized, observer-blinded controlled trial included 90 patients undergoing elective surgery under general anesthesia. Patients were randomized using a chit and box system for group allocation. Groups were as follows: Group 1 (n=30) - Investigator standing on the back of the head of the patient (0°); Group 2 (n=30) - Investigator standing on the left side facing the patient (120°); Group 3 (n=30) - Investigator standing on the right side facing the patient (240°). Then ease and time of insertion of ILMA, number of attempts for successful ILMA insertion and oropharyngeal leak pressure were noted, and intergroup comparison was done. Conclusion ILMA has proved to be an effective ventilatory device and a suitable conduit for intubation in patients lying in the supine position from a conventional standard position standing behind the head of the patient, as well as non-conventional position, facing the patient at 120° or 240° from the standard position.

Force-Based Modeling of Heterogeneous Roles in the Coordinated Behavior of a Triad

Group coordination is defined as interactions with other members to implement a task that is difficult to do alone or to achieve higher performance than an individual. Meanwhile, the adjustment process in coordination is not uniquely determined because each individual has many degrees of freedom. It is more difficult to explain and model complex and dynamic coordination, such as nonverbal behavior of three or more members than pair or verbal interaction. Hence, we previously introduced a coordinated drawing task and conducted the behavioral experiment. The triads operated reels to change the tensions of threads connected to a pen, shared three heterogeneous roles (pulling, relaxing, and adjusting), and moved the pen to draw an equilateral triangle. The results indicated that the adjusting role was related to high task performance by helping resiliently without disturbing the pen’s smooth movement while avoiding great pen deviation. However, this experiment alone cannot explain details of the adjustment process of tension. To supplement these findings, this study formulated the three roles using equations of motion. The multi-agent simulation results showed that the adjusting role might use the degree of pen deviation reflected by the others’ motor information, such as the operating procedures and forces, to change the tension and draw at least three sides. Although it is necessary to consider that we used the experimental task, our study contributes to the fundamental understanding of resilient adjustment in coordination by sharing heterogeneous roles as the first step.

A sliding mode based foot-end trajectory consensus control method with variable topology for legged motion of heavy-duty robot

Rational foot-end trajectory planning and control are of great significance for stable-legged walking of heavy-duty multi-legged robots. To achieve a fast, active, and compliant response of the leg actuator to disturbances for improvement of the stability and flexibility of the heavy-duty legged robot system during continuous walking on rough roads, a legged consensus control method (LCC) is proposed. Firstly, the LCC includes a foot-end trajectory planner model for designing the trajectory during the swing phase to ensure that the robot’s feet are always in a safe workspace during legged motion with continuously variable direction. Secondly, LCC constructs a consensus control method for encoding foot-end position and velocity consensus error based on variable topology networks. Six legs are treated as six intelligent agents and divided into two fully connected networks: the swing phase and stance phase, to achieve smooth and consistent motion that satisfies the geometric constraints of the robot. The foot-end agent can switch between swing and stance groups according to the state of the contact with the environment accompanied by the amendment topology, to enhance the robustness of the robot system through fast compliance control of the foot-end kinematics state. Then, the sliding mode control method based on consensus velocity and position error is deduced in LCC. The sliding mode surface is designed to make the three control variables realize stable movement with a consistent state of foot-end in three X,Y,Z-axis respectively, thereby enhancing the stability of foot-end state and fuselage posture. Finally, simulation and experiments have verified that the proposed LCC can assist legged-robot perform relatively steady legged motion with continuously variable direction on various rugged roads. The body attitude Root Mean Square Error (RMSE) is quickly reduced by 81.0% compared with independent PI control. The LCC algorithm code is publicly available at https://github.com/bjmyX/LCC_code.

A Method of Dual-AGV-Ganged Path Planning Based on the Genetic Algorithm

The genetic algorithm (GA) is a metaheuristic inspired by the process of natural selection, and it is known for its iterative optimization capabilities in both constrained and unconstrained environments. In this paper, a novel method for GA-based dual-automatic guided vehicle (AGV)-ganged path planning is proposed to address the problem of frequent steering collisions in dual-AGV-ganged autonomous navigation. This method successfully plans global paths that are safe, collision-free, and efficient for both leader and follower AGVs. Firstly, a new ganged turning cost function was introduced based on the safe turning radius of dual-AGV-ganged systems to effectively search for selectable safe paths. Then, a dual-AGV-ganged fitness function was designed that incorporates the pose information of starting and goal points to guide the GA toward iterative optimization for smooth, efficient, and safe movement of dual AGVs. Finally, to verify the feasibility and effectiveness of the proposed algorithm, simulation experiments were conducted, and its performance was compared with traditional genetic algorithms, Astra algorithms, and Dijkstra algorithms. The results show that the proposed algorithm effectively solves the problem of frequent steering collisions, significantly shortens the path length, and improves the smoothness and safety stability of the path. Moreover, the planned paths were validated in real environments, ensuring safe paths while making more efficient use of map resources. Compared to the Dijkstra algorithm, the path length was reduced by 30.1%, further confirming the effectiveness of the method. This provides crucial technical support for the safe autonomous navigation of dual-AGV-ganged systems.

Object Weight and Hand Dominance Impact Kinematics in a Functional Reach-to-Drink Task in School-Aged Children.

This study evaluates the effects of object weight and hand dominance on the end-point kinematics of the hand-to-mouth (withdrawal) movement in a functional reach-to-drink task for typically developing school-aged children. Using 3D motion capture, speed (average velocity and peak velocity), straightness (ratio), and smoothness (number of velocity peaks and log dimensionless jerk) of hand movements were calculated for the withdrawal motion with three different bottle weights (empty, half-filled, and full). Average velocity (550.4 ± 142.0 versus 512.1 ± 145.6 mm/s) and peak velocity (916.3 ± 234 versus 842.7 ± 198.4 mm/s) were significantly higher with the empty versus half-filled bottle and with the non-dominant (average: 543.5 ± 145.2 mm/s; peak: 896.5 ± 207 mm/s) versus dominant (average: 525.2 ± 40.7 mm/s; peak: 864.2 ± 209.2 mm/s) hand. There were no differences in straightness or smoothness. These findings indicate that increasing weight in reach-to-drink task puts greater constraints on the task. The slower movements with the dominant hand might denote better precision control than the non-dominant hand. The quantitative motion capture results show average values for the kinematic variables for a functional reach-to-drink task in a typically developing population of school-aged children with changing weights of the bottles that are relevant to a real-life scenario. These results could inform the design of individualized therapeutic interventions to improve functional upper-extremity use in children with neurodevelopmental motor disorders.

The Effect of Time Pressure on Motion Economy and Smoothness of Interventional Radiology Trainee Performance in Simulated Central Venous Line Placement.

To evaluate the effect of being under time pressure on procedural performance using hand motion analysis. Eight radiology trainees performed central venous access on a phantom while recording video and hand motion data using an electromagnetic motion tracker. Each trainee performed the procedure six times: the first three trials without any prompts (control), while for the next three, they were asked to perform the task as fast as possible (time pressure). Validated hand motion metrics were analyzed, and two blinded and independent evaluators rated procedural performance using a previously validated task-specific global rating scale (GRS). Motion/time ratios and linear mixed-effect methods were used to control for time, and constants for both strategies were compared. Hand motion analysis showed that trainees completed the simulated procedure faster under time pressure (46 ± 18s vs. 56 ± 27s, p = 0.008) than during the control strategy. However, when controlling for time, trainees moved their hands 79 more centimeters (p = 0.04), made 15 more translational movements (p = 0.003) and 18 more rotational movements (p = 0.01) when under time pressure compared to at their own pace. Although trainees could perform the procedure faster under time pressure, there was a deterioration in hand motion economy and smoothness. This suggests that hand motion metrics offer a more comprehensive assessment of technical performance than time alone.