Displaying publications 1 - 20 of 85 in total

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  1. A'qilah Ahmad Dahalan, Azali Saudi, Jumat Sulaiman
    MyJurnal
    Mobile robots often have to discover a path of collision-free towards a specific goal point in their environment. We are trying to resolve the mobile robot problem iteratively by means of numerical technique. It is built on a method of potential field that count on the use of Laplace’s equation in the mobile robot’s configuration space to constrain/which reduces the generation of a potential function over regions. This paper proposed an iterative approach in solving robot path finding problem known as Accelerated Over-Relaxation (AOR). The experiment shows that these suggested approach can establish a smooth path between the starting and goal points by engaging with a finite-difference technique. The simulation results also show that a more rapidly solution with smoother path than the previous work is achieved via this numerical approach.
    Matched MeSH terms: Robotics
  2. Abd Razak NA, Abu Osman NA, Gholizadeh H, Ali S
    Biomed Eng Online, 2014 Apr 23;13:49.
    PMID: 24755242 DOI: 10.1186/1475-925X-13-49
    BACKGROUND: The design and performance of a new development prosthesis system known as biomechatronics wrist prosthesis is presented in this paper. The prosthesis system was implemented by replacing the Bowden tension cable of body powered prosthesis system using two ultrasonic sensors, two servo motors and microcontroller inside the prosthesis hand for transradial user.

    METHODS: The system components and hand prototypes involve the anthropometry, CAD design and prototyping, biomechatronics engineering together with the prosthetics. The modeler construction of the system develop allows the ultrasonic sensors that are placed on the shoulder to generate the wrist movement of the prosthesis. The kinematics of wrist movement, which are the pronation/supination and flexion/extension were tested using the motion analysis and general motion of human hand were compared. The study also evaluated the require degree of detection for the input of the ultrasonic sensor to generate the wrist movements.

    RESULTS: The values collected by the vicon motion analysis for biomechatronics prosthesis system were reliable to do the common tasks in daily life. The degree of the head needed to bend to give the full input wave was about 45°-55° of rotation or about 14 cm-16 cm. The biomechatronics wrist prosthesis gave higher degree of rotation to do the daily tasks but did not achieve the maximum degree of rotation.

    CONCLUSION: The new development of using sensor and actuator in generating the wrist movements will be interesting for used list in medicine, robotics technology, rehabilitations, prosthetics and orthotics.

    Matched MeSH terms: Robotics/instrumentation*
  3. Abdul Rahman H, Khor KX, Yeong CF, Su EL, Narayanan AL
    Biomed Mater Eng, 2017;28(2):105-116.
    PMID: 28372264 DOI: 10.3233/BME-171660
    BACKGROUND: Clinical scales such as Fugl-Meyer Assessment (FMA) and Motor Assessment Scale (MAS) are widely used to evaluate stroke patient's motor performance. However, there are several limitations with these assessment scales such as subjectivity, lack of repeatability, time-consuming and highly depend on the ability of the physiotherapy. In contrast, robot-based assessments are objective, repeatable, and could potentially reduce the assessment time. However, robot-based assessments are not as well established as conventional assessment scale and the correlation to conventional assessment scale is unclear.

    OBJECTIVE: This study was carried out to identify important parameters in designing tasks that efficiently assess hand function of stroke patients and to quantify potential benefits of robotic assessment modules to predict the conventional assessment score with iRest.

    METHODS: Twelve predictive variables were explored, relating to movement time, velocity, strategy, accuracy and smoothness from three robotic assessment modules which are Draw I, Draw Diamond and Draw Circle. Regression models using up to four predictors were developed to describe the MAS.

    RESULTS: Results show that the time given should be not too long and it would affect the trajectory error. Besides, result also shows that it is possible to use iRest in predicting MAS score.

    CONCLUSION: There is a potential of using iRest, a non-motorized device in predicting MAS score.

    Matched MeSH terms: Robotics/instrumentation*
  4. Abdul Wahit MA, Ahmad SA, Marhaban MH, Wada C, Izhar LI
    Sensors (Basel), 2020 Jul 27;20(15).
    PMID: 32727150 DOI: 10.3390/s20154174
    Trans-radial prosthesis is a wearable device that intends to help amputees under the elbow to replace the function of the missing anatomical segment that resembles an actual human hand. However, there are some challenging aspects faced mainly on the robot hand structural design itself. Improvements are needed as this is closely related to structure efficiency. This paper proposes a robot hand structure with improved features (four-bar linkage mechanism) to overcome the deficiency of using the cable-driven actuated mechanism that leads to less structure durability and inaccurate motion range. Our proposed robot hand structure also took into account the existing design problems such as bulky structure, unindividual actuated finger, incomplete fingers and a lack of finger joints compared to the actual finger in its design. This paper presents the improvements achieved by applying the proposed design such as the use of a four-bar linkage mechanism instead of using the cable-driven mechanism, the size of an average human hand, five-fingers with completed joints where each finger is moved by motor individually, joint protection using a mechanical stopper, detachable finger structure from the palm frame, a structure that has sufficient durability for everyday use and an easy to fabricate structure using 3D printing technology. The four-bar linkage mechanism is the use of the solid linkage that connects the actuator with the structure to allow the structure to move. The durability was investigated using static analysis simulation. The structural details and simulation results were validated through motion capture analysis and load test. The motion analyses towards the 3D printed robot structure show 70-98% similar motion range capability to the designed structure in the CAD software, and it can withstand up to 1.6 kg load in the simulation and the real test. The improved robot hand structure with optimum durability for prosthetic uses was successfully developed.
    Matched MeSH terms: Robotics*
  5. Abdullah BJ, Yeong CH, Goh KL, Yoong BK, Ho GF, Yim CC, et al.
    Eur Radiol, 2015 Jan;25(1):246-57.
    PMID: 25189152 DOI: 10.1007/s00330-014-3391-7
    OBJECTIVE: This study aimed to assess the technical success, radiation dose, safety and performance level of liver thermal ablation using a computed tomography (CT)-guided robotic positioning system.

    METHODS: Radiofrequency and microwave ablation of liver tumours were performed on 20 patients (40 lesions) with the assistance of a CT-guided robotic positioning system. The accuracy of probe placement, number of readjustments and total radiation dose to each patient were recorded. The performance level was evaluated on a five-point scale (5-1: excellent-poor). The radiation doses were compared against 30 patients with 48 lesions (control) treated without robotic assistance.

    RESULTS: Thermal ablation was successfully completed in 20 patients with 40 lesions and confirmed on multiphasic contrast-enhanced CT. No procedure related complications were noted in this study. The average number of needle readjustment was 0.8 ± 0.8. The total CT dose (DLP) for the entire robotic assisted thermal ablation was 1382 ± 536 mGy.cm, while the CT fluoroscopic dose (DLP) per lesion was 352 ± 228 mGy.cm. There was no statistically significant (p > 0.05) dose reduction found between the robotic-assisted versus the conventional method.

    CONCLUSION: This study revealed that robotic-assisted planning and needle placement appears to be safe, with high accuracy and a comparable radiation dose to patients.

    KEY POINTS: • Clinical experience on liver thermal ablation using CT-guided robotic system is reported. • The technical success, radiation dose, safety and performance level were assessed. • Thermal ablations were successfully performed, with an average performance score of 4.4/5.0. • Robotic-assisted ablation can potentially increase capabilities of less skilled interventional radiologists. • Cost-effectiveness needs to be proven in further studies.

    Matched MeSH terms: Robotics/methods*
  6. Abdullah BJ, Yeong CH, Goh KL, Yoong BK, Ho GF, Yim CC, et al.
    Eur Radiol, 2014 Jan;24(1):79-85.
    PMID: 23928933 DOI: 10.1007/s00330-013-2979-7
    OBJECTIVE: Computed tomography (CT)-compatible robots, both commercial and research-based, have been developed with the intention of increasing the accuracy of needle placement and potentially improving the outcomes of therapies in addition to reducing clinical staff and patient exposure to radiation during CT fluoroscopy. In the case of highly inaccessible lesions that require multiple plane angulations, robotically assisted needles may improve biopsy access and targeted drug delivery therapy by avoidance of the straight line path of normal linear needles.

    METHODS: We report our preliminary experience of performing radiofrequency ablation of the liver using a robotic-assisted CT guidance system on 11 patients (17 lesions).

    RESULTS/CONCLUSION: Robotic-assisted planning and needle placement appears to have high accuracy, is technically easier than the non-robotic-assisted procedure, and involves a significantly lower radiation dose to both patient and support staff.

    KEY POINTS: • An early experience of robotic-assisted radiofrequency ablation is reported • Robotic-assisted RFA improves accuracy of hepatic lesion targeting • Robotic-assisted RFA makes the procedure technically easier with significant lower radiation dose.

    Matched MeSH terms: Robotics*
  7. Abdullah MZ, Awang MS, Tan YC, Abdullah JM
    J Neurol Surg A Cent Eur Neurosurg, 2014 Mar;75(2):155-7.
    PMID: 23636911 DOI: 10.1055/s-0032-1330954
    The study assesses the capability and accuracy of a robotic arm to perform burr holes.
    Matched MeSH terms: Robotics/methods*
  8. Adlin Dasima, A.K., Nadia Hanom, I., Siti Aznida, A.K., Rusnaini, M.K., Mohd Fahmi, Z., Mohd Nazir, M.S., et al.
    MyJurnal
    This is our first experience in providing general anaesthesia for robotic-assisted thyroidectomy (RAT). It is rather a
    new experience for our anaesthetic team and few issues should be addressed. The conduct of RAT must be fully
    understood and familiarized as it may present with few challenges for the anaesthesiologists. The key point of
    success during this learning curve period is the importance of teamwork between the anaesthesiologists and the
    operating surgeons. The specific anaesthetic challenges include limited access to the patient post-docking of the
    robot, the need of extra precautions of the anaesthetic circuit and IV line connections, a vigilant anaesthesiologists
    and options for postoperative pain relief.
    Matched MeSH terms: Robotics
  9. Ahmad FA, Ramli AR, Samsudin K, Hashim SJ
    ScientificWorldJournal, 2014;2014:153162.
    PMID: 24949491 DOI: 10.1155/2014/153162
    Deploying large numbers of mobile robots which can interact with each other produces swarm intelligent behavior. However, mobile robots are normally running with finite energy resource, supplied from finite battery. The limitation of energy resource required human intervention for recharging the batteries. The sharing information among the mobile robots would be one of the potentials to overcome the limitation on previously recharging system. A new approach is proposed based on integrated intelligent system inspired by foraging of honeybees applied to multimobile robot scenario. This integrated approach caters for both working and foraging stages for known/unknown power station locations. Swarm mobile robot inspired by honeybee is simulated to explore and identify the power station for battery recharging. The mobile robots will share the location information of the power station with each other. The result showed that mobile robots consume less energy and less time when they are cooperating with each other for foraging process. The optimizing of foraging behavior would result in the mobile robots spending more time to do real work.
    Matched MeSH terms: Robotics*
  10. Ahmad NS
    Sensors (Basel), 2020 Jun 30;20(13).
    PMID: 32630046 DOI: 10.3390/s20133673
    Motion control involving DC motors requires a closed-loop system with a suitable compensator if tracking performance with high precision is desired. In the case where structural model errors of the motors are more dominating than the effects from noise disturbances, accurate system modelling will be a considerable aid in synthesizing the compensator. The focus of this paper is on enhancing the tracking performance of a wheeled mobile robot (WMR), which is driven by two DC motors that are subject to model parametric uncertainties and uncertain deadzones. For the system at hand, the uncertain nonlinear perturbations are greatly induced by the time-varying power supply, followed by behaviour of motion and speed. In this work, the system is firstly modelled, where correlations between the model parameters and different input datasets as well as voltage supply are obtained via polynomial regressions. A robust H ∞ -fuzzy logic approach is then proposed to treat the issues due to the aforementioned perturbations. Via the proposed strategy, the H ∞ controller and the fuzzy logic (FL) compensator work in tandem to ensure the control law is robust against the model uncertainties. The proposed technique was validated via several real-time experiments, which showed that the speed and path tracking performance can be considerably enhanced when compared with the results via the H ∞ controller alone, and the H ∞ with the FL compensator, but without the presence of the robust control law.
    Matched MeSH terms: Robotics
  11. Ahmed M. M. ALmassri, Chikamune Wada, Wan Hasan, W.Z., Ahmad, S.A.
    MyJurnal
    This paper presents an auto grasping algorithm of a proposed robotic gripper. The purpose is to enhance the grasping mechanism of the gripper. Earlier studies have introduced various methods to enhance the grasping mechanism, but most of the works have not looked at the weight measurement method. Thus, with this algorithm, the weight of the object is calculated based on modified Wheatstone Bridge Circuit (WBC) which is controlled by programmable interface controller (PIC) method. Having this approach introduces and improves the grasping mechanism through an auto grasping algorithm. Experimental results show that an auto grasping algorithm based on pressure sensor measurements leads to a more precise grasping measurement and consequently enhance the sensitivity measurement as well as accurate movement calibration. Furthermore, several different grasping objects based on the proposed method are examined to demonstrate the performance and robustness of our approach.
    Matched MeSH terms: Robotics
  12. Al-Abdullah KI, Lim CP, Najdovski Z, Yassin W
    Int J Med Robot, 2019 Jun;15(3):e1989.
    PMID: 30721570 DOI: 10.1002/rcs.1989
    BACKGROUND: This paper presents a model-based bone milling state identification method that provides intraoperative bone quality information during robotic bone milling. The method helps surgeons identify bone layer transitions during bone milling.

    METHODS: On the basis of a series of bone milling experiments with commercial artificial bones, an artificial neural network force model is developed to estimate the milling force of different bone densities as a function of the milling feed rate and spindle speed. The model estimations are used to identify the bone density at the cutting zone by comparing the actual milling force with the estimated one.

    RESULTS: The verification experiments indicate the ability of the proposed method to distinguish between one cortical and two cancellous bone densities.

    CONCLUSIONS: The significance of the proposed method is that it can be used to discriminate a set of different bone density layers for a range of the milling feed rate and spindle speed.

    Matched MeSH terms: Robotics
  13. Al-Qaysi ZT, Zaidan BB, Zaidan AA, Suzani MS
    Comput Methods Programs Biomed, 2018 Oct;164:221-237.
    PMID: 29958722 DOI: 10.1016/j.cmpb.2018.06.012
    CONTEXT: Intelligent wheelchair technology has recently been utilised to address several mobility problems. Techniques based on brain-computer interface (BCI) are currently used to develop electric wheelchairs. Using human brain control in wheelchairs for people with disability has elicited widespread attention due to its flexibility.

    OBJECTIVE: This study aims to determine the background of recent studies on wheelchair control based on BCI for disability and map the literature survey into a coherent taxonomy. The study intends to identify the most important aspects in this emerging field as an impetus for using BCI for disability in electric-powered wheelchair (EPW) control, which remains a challenge. The study also attempts to provide recommendations for solving other existing limitations and challenges.

    METHODS: We systematically searched all articles about EPW control based on BCI for disability in three popular databases: ScienceDirect, IEEE and Web of Science. These databases contain numerous articles that considerably influenced this field and cover most of the relevant theoretical and technical issues.

    RESULTS: We selected 100 articles on the basis of our inclusion and exclusion criteria. A large set of articles (55) discussed on developing real-time wheelchair control systems based on BCI for disability signals. Another set of articles (25) focused on analysing BCI for disability signals for wheelchair control. The third set of articles (14) considered the simulation of wheelchair control based on BCI for disability signals. Four articles designed a framework for wheelchair control based on BCI for disability signals. Finally, one article reviewed concerns regarding wheelchair control based on BCI for disability signals.

    DISCUSSION: Since 2007, researchers have pursued the possibility of using BCI for disability in EPW control through different approaches. Regardless of type, articles have focused on addressing limitations that impede the full efficiency of BCI for disability and recommended solutions for these limitations.

    CONCLUSIONS: Studies on wheelchair control based on BCI for disability considerably influence society due to the large number of people with disability. Therefore, we aim to provide researchers and developers with a clear understanding of this platform and highlight the challenges and gaps in the current and future studies.

    Matched MeSH terms: Robotics
  14. Al-Quraishi MS, Ishak AJ, Ahmad SA, Hasan MK, Al-Qurishi M, Ghapanchizadeh H, et al.
    Med Biol Eng Comput, 2017 May;55(5):747-758.
    PMID: 27484411 DOI: 10.1007/s11517-016-1551-4
    Electromyography (EMG)-based control is the core of prostheses, orthoses, and other rehabilitation devices in recent research. Nonetheless, EMG is difficult to use as a control signal given the complex nature of the signal. To overcome this problem, the researchers employed a pattern recognition technique. EMG pattern recognition mainly involves four stages: signal detection, preprocessing feature extraction, dimensionality reduction, and classification. In particular, the success of any pattern recognition technique depends on the feature extraction stage. In this study, a modified time-domain features set and logarithmic transferred time-domain features (LTD) were evaluated and compared with other traditional time-domain features set (TTD). Three classifiers were employed to assess the two feature sets, namely linear discriminant analysis (LDA), k nearest neighborhood, and Naïve Bayes. Results indicated the superiority of the new time-domain feature set LTD, on conventional time-domain features TTD with the average classification accuracy of 97.23 %. In addition, the LDA classifier outperformed the other two classifiers considered in this study.
    Matched MeSH terms: Robotics/methods
  15. Ali MAH, Mailah M, Jabbar WA, Moiduddin K, Ameen W, Alkhalefah H
    Sensors (Basel), 2020 Jul 01;20(13).
    PMID: 32630340 DOI: 10.3390/s20133694
    A real-time roundabout detection and navigation system for smart vehicles and cities using laser simulator-fuzzy logic algorithms and sensor fusion in a road environment is presented in this paper. A wheeled mobile robot (WMR) is supposed to navigate autonomously on the road in real-time and reach a predefined goal while discovering and detecting the road roundabout. A complete modeling and path planning of the road's roundabout intersection was derived to enable the WMR to navigate autonomously in indoor and outdoor terrains. A new algorithm, called Laser Simulator, has been introduced to detect various entities in a road roundabout setting, which is later integrated with fuzzy logic algorithm for making the right decision about the existence of the roundabout. The sensor fusion process involving the use of a Wi-Fi camera, laser range finder, and odometry was implemented to generate the robot's path planning and localization within the road environment. The local maps were built using the extracted data from the camera and laser range finder to estimate the road parameters such as road width, side curbs, and roundabout center, all in two-dimensional space. The path generation algorithm was fully derived within the local maps and tested with a WMR platform in real-time.
    Matched MeSH terms: Robotics
  16. Alshammari RFN, Abd Rahman AH, Arshad H, Albahri OS
    Sensors (Basel), 2023 Dec 05;23(24).
    PMID: 38139465 DOI: 10.3390/s23249619
    Existing methods for scoring student presentations predominantly rely on computer-based implementations and do not incorporate a robotic multi-classification model. This limitation can result in potential misclassification issues as these approaches lack active feature learning capabilities due to fixed camera positions. Moreover, these scoring methods often solely focus on facial expressions and neglect other crucial factors, such as eye contact, hand gestures and body movements, thereby leading to potential biases or inaccuracies in scoring. To address these limitations, this study introduces Robotics-based Presentation Skill Scoring (RPSS), which employs a multi-model analysis. RPSS captures and analyses four key presentation parameters in real time, namely facial expressions, eye contact, hand gestures and body movements, and applies the fuzzy Delphi method for criteria selection and the analytic hierarchy process for weighting, thereby enabling decision makers or managers to assign varying weights to each criterion based on its relative importance. RPSS identifies five academic facial expressions and evaluates eye contact to achieve a comprehensive assessment and enhance its scoring accuracy. Specific sub-models are employed for each presentation parameter, namely EfficientNet for facial emotions, DeepEC for eye contact and an integrated Kalman and heuristic approach for hand and body movements. The scores are determined based on predefined rules. RPSS is implemented on a robot, and the results highlight its practical applicability. Each sub-model is rigorously evaluated offline and compared against benchmarks for selection. Real-world evaluations are also conducted by incorporating a novel active learning approach to improve performance by leveraging the robot's mobility. In a comparative evaluation with human tutors, RPSS achieves a remarkable average agreement of 99%, showcasing its effectiveness in assessing students' presentation skills.
    Matched MeSH terms: Robotics*
  17. Amini H, Farzaneh B, Azimifar F, Sarhan AAD
    ISA Trans, 2016 Sep;64:293-302.
    PMID: 27329852 DOI: 10.1016/j.isatra.2016.05.006
    This paper establishes a novel control strategy for a nonlinear bilateral macro-micro teleoperation system with time delay. Besides position and velocity signals, force signals are additionally utilized in the control scheme. This modification significantly improves the poor transparency during contact with the environment. To eliminate external force measurement, a force estimation algorithm is proposed for the master and slave robots. The closed loop stability of the nonlinear micro-micro teleoperation system with the proposed control scheme is investigated employing the Lyapunov theory. Consequently, the experimental results verify the efficiency of the new control scheme in free motion and during collision between the slave robot and the environment of slave robot with environment, and the efficiency of the force estimation algorithm.
    Matched MeSH terms: Robotics
  18. Amir Abdullah, M.D., Leman, A.M., Norhidayah, A., Syafiq Syazwan, M.M.
    MyJurnal
    A poor Indoor Air Quality (IAQ) is a crucial problem which produces by the improper maintenance of Mechanical Ventilation and Air Conditioning (MVAC) ducting. A budget constraint intimidates for the practise of monitoring of the MVAC ducting. Thus IAQ measurements were conducted at the room where the air supplied by centralized air conditioning. It has been performed at four different offices that supply by two different Air Handling Unit (AHU). Walkthrough survey was conducted and the area samplings were selected for data collection. This paper examines the result of comparison of air ducting and air quality at academic office building, Universiti Tun Hussein Onn Malaysia (UTHM). The parameters involved were Temperature (°C), Relative Humidity (RH), Carbon Dioxide (CO2) and Carbon Monoxide (CO). Pictures were also captured to demonstrate the real conditions inside the ducting by using Mechanical Robot. Thus, duct cleaning was recommended to be an exceptional platform for the IAQ improvement.
    Matched MeSH terms: Robotics
  19. Aole S, Elamvazuthi I, Waghmare L, Patre B, Meriaudeau F
    Sensors (Basel), 2020 Jun 30;20(13).
    PMID: 32630115 DOI: 10.3390/s20133681
    Neurological disorders such as cerebral paralysis, spinal cord injuries, and strokes, result in the impairment of motor control and induce functional difficulties to human beings like walking, standing, etc. Physical injuries due to accidents and muscular weaknesses caused by aging affect people and can cause them to lose their ability to perform daily routine functions. In order to help people recover or improve their dysfunctional activities and quality of life after accidents or strokes, assistive devices like exoskeletons and orthoses are developed. Control strategies for control of exoskeletons are developed with the desired intention of improving the quality of treatment. Amongst recent control strategies used for rehabilitation robots, active disturbance rejection control (ADRC) strategy is a systematic way out from a robust control paradox with possibilities and promises. In this modern era, we always try to find the solution in order to have minimum resources and maximum output, and in robotics-control, to approach the same condition observer-based control strategies is an added advantage where it uses a state estimation method which reduces the requirement of sensors that is used for measuring every state. This paper introduces improved active disturbance rejection control (I-ADRC) controllers as a combination of linear extended state observer (LESO), tracking differentiator (TD), and nonlinear state error feedback (NLSEF). The proposed controllers were evaluated through simulation by investigating the sagittal plane gait trajectory tracking performance of two degrees of freedom, Lower Limb Robotic Rehabilitation Exoskeleton (LLRRE). This multiple input multiple output (MIMO) LLRRE has two joints, one at the hip and other at the knee. In the simulation study, the proposed controllers show reduced trajectory tracking error, elimination of random, constant, and harmonic disturbances, robustness against parameter variations, and under the influence of noise, with improvement in performance indices, indicates its enhanced tracking performance. These promising simulation results would be validated experimentally in the next phase of research.
    Matched MeSH terms: Robotics*
  20. Aslan MF, Hasikin K, Yusefi A, Durdu A, Sabanci K, Azizan MM
    Front Public Health, 2022;10:855994.
    PMID: 35734764 DOI: 10.3389/fpubh.2022.855994
    Artificial intelligence researchers conducted different studies to reduce the spread of COVID-19. Unlike other studies, this paper isn't for early infection diagnosis, but for preventing the transmission of COVID-19 in social environments. Among the studies on this is regarding social distancing, as this method is proven to prevent COVID-19 to be transmitted from one to another. In the study, Robot Operating System (ROS) simulates a shopping mall using Gazebo, and customers are monitored by Turtlebot and Unmanned Aerial Vehicle (UAV, DJI Tello). Through frames analysis captured by Turtlebot, a particular person is identified and followed at the shopping mall. Turtlebot is a wheeled robot that follows people without contact and is used as a shopping cart. Therefore, a customer doesn't touch the shopping cart that someone else comes into contact with, and also makes his/her shopping easier. The UAV detects people from above and determines the distance between people. In this way, a warning system can be created by detecting places where social distance is neglected. Histogram of Oriented-Gradients (HOG)-Support Vector Machine (SVM) is applied by Turtlebot to detect humans, and Kalman-Filter is used for human tracking. SegNet is performed for semantically detecting people and measuring distance via UAV. This paper proposes a new robotic study to prevent the infection and proved that this system is feasible.
    Matched MeSH terms: Robotics*
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