IAES International Journal of Robotics and Automation (IJRA)
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    460 research outputs found

    Position control of AX-12 servo motor using proportional-integral-derivative controller with particle swarm optimization for robotic manipulator application

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    This study proposes a control method for servo motor position using a proportional-integral-derivative (PID) controller with particle swarm optimization (PSO). We use an AX-12 servo motor that is commonly used for robotic manipulator applications. The angular position of the servo motor will be controlled using the PID control method with PSO as a controller gain optimizer. Firstly, the transfer function model of the servo motor is generated using open-loop model identification. Then, the integral error of the closed-loop system is used as PSO input in producing PID controller gain. As an objective function of the PSO algorithm, the integral time absolute error (ITAE) index performance is used. The proposed controller was tested and compared with PID with the Ziegler-Nichols (ZN) method. We also conduct the hardware experiment using Arduino Uno as a microcontroller using one AX-12 servo motor on the base joint of the manipulator robot. Based on the simulation result, the PID-PSO controller can achieve the best control response performance if compared to PID-ZN with a rise time is less than 0.5 s, a settling time of fewer than 8 s, and an overshoot under 1.2%. The effectiveness of the proposed PID-PSO controller is also validated by hardware experimental results

    In-car speech enhancement based on source separation technique

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    This work addresses the solution of localizing and enhancing hands-free speech inside the car environment. Cars have different types of sounds from outside, co-passengers dialogue and noise. To provide better-quality speech, a microphone array-based beamforming technique is used. This research work proposes the method for selected source localization, source separation, and enhancement. An estimation of the direction of arrival (DOA) to localize the signal direction and preferred direction is selected for speech enhancement. The spiral and sine-cosine algorithm (SSCA) algorithm is combined with an adaptive least mean square to adapt the system for different environments. The algorithm is implemented in hardware and tested in a real-time car environment. The results showed significant improvement in signal-to-noise ratio (SNR) of 5.2 dB and perceptual evaluation of speech quality (PESQ) of 2.3. Finally, the model is fine-tuned for the car to get better quality. The proposed technique is efficient, and results are compared with existing methods

    A model-free continuous integral sliding mode controller for robust control of robotic manipulators

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    This paper proposes a model-free continuous integral sliding mode controller for robust control of robotic manipulators. The highly nonlinear dynamics of robots and load disturbances cause control challenges. To achieve tracking control under load disturbances and nonlinear parameter variations, the controller is constructed with three continuous terms including an integral term that acts as an adaptive controller. The proposed controller is able to accomplish a non-overshoot transient response, a short settling time, and strong disturbance rejection performance for robotic manipulators. The developed model-free control method is implemented on the PUMA 560 robotic manipulator, and its performance is compared with the proportional-derivative (PD) plus gravity controller. Numerical results under measurement noise and load disturbances are provided in order to show the efficacy, validity, and feasibility of the method

    Smart factory for future industry development

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    The paradigm of the smart factory is thought of as an innovative outline for the fourth industrial revolt. The GLOVA G7-DR20U is set as a programmable logic controller (PLC) for monitoring the performance of the smart factory while using the NodeMCU-V3 esp8266 as the internet of things (IoT) board for interaction between managers and the factory using the personal digital assistant (PDA) programming that has been written in the RabitMQ platform. The program logged inner PLC by applying ladder language for monitoring the performance of PLC. With the completion of intelligent PLC, it is likely to extend the existing making capability in the factory with simplicity. This work joins a PLC used as a parent control unit, apps, user programs, and human-machine interface, with the Internet. The proposed model of the smart factory holds two motors one for the parallel drive and the other for the upright drive. While running the system, we observe that the proposal is working correctly, and the reply to the interaction method via IoT is excellent

    Semi-automated mid-turbinate swab sampling using a six degrees of freedom collaborative robot and cameras

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    Mid-turbinate swab sampling is an effective way to detect the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus. Several articles discussed the importance and benefits of using robotic technology to alleviate healthcare workers’ daily burdens against coronavirus disease 2019 (COVID-19). Therefore, a semi-automated approach for collecting swab samples from the mid-turbinate area-approximately 4 cm inside the nose is proposed. The system utilizes a six-degrees-of-freedom (6-DOF) Doosan Robot M1509 and two smart visual sensors: one on the end effector and the other fixed to the side for estimating the angle of the nasal path. This work suggests a method of robot and human collaboration in the sampling process that could minimize infections from samplings and guarantee uniformly administered sampling processes. The effectiveness of this proposed work was tested on a live patient and a phantom head; meanwhile, the insertion process was only administered on the phantom head. Although the overall time of the experiment was greater than a manual swab, the feasibility of implementing robotic applications for COVID-19 swab sampling has been practically showcased in this paper

    Microexpression recognition robot

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    Following the development of big data, the use of microexpression technology has become increasingly popular. The application of microexpressions has expanded beyond medical treatment to include scientific case investigations. Because microexpressions are characterized by short duration and low intensity, training humans to recognize their yields poor performance results. Automatically recognizing microexpressions by using machine learning techniques can provide more effective results and save time and resources. In the real world, to avoid judicial punishment, people lie and conceal the truth for a variety of reasons. In this study, our primary objective was to develop a system for real-time microexpression recognition. We used FaceReader as the retrieval system and integrated the data with an application programming interface to provide recognition results as objective references in real-time. Using an experimental analysis, we also attempted to determine the optimal system configuration conditions. In conclusion, the use of artificial intelligence is expected to enhance the efficiency of investigations

    Fault tolerance of a quadrotor via feedback linearization approach

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    A control algorithm is proposed to efficiently control the state, position, and height of a nonlinear dynamic model of a quadcopter. Based on feedback linearization, a state space model is presented for the system with the controller with a two-loop control structure designed and implemented in it. The inner and faster controller is responsible for adjusting the quadcopter height and angles, and the outer and slower controller is responsible for changing the desired figures of roll and pitch angles to control the system position. Whenever a rotor of the quadcopter rotor fails, the status and position of the system are converged and the system is stabilized. Simulation results based on different scenarios indicate the proper performance of the control system whenever there are external disturbances. Note that the gyroscopic effects because of the propeller rotation were not considered

    Object distance estimation using a monovision camera

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    In computer vision, most monovision cameras used for estimating the position of an object only estimate the 2D information of the object without the depth information. Estimating the depth information, which is the distance between the target object and the camera is quite challenging but, in this paper, a less computationally intensive method was used to estimate the object’s distance to complete the 3D information needed to determine the object’s location in cartesian space. In this method, the object was positioned in front of the camera at a sequential distance and was measured directly. The distances measured in the experiment with a set of training data obtained from the image were fitted into a curve using the least-square framework to derive a non-linear function that was used for estimating the object’s distance also known as the z-coordinate. The result from the experiment showed that there was an average error of 1.33 mm between the actual distance and the estimated distance of the object. Hence, this method can be applied in many robotic and autonomous systems applications

    Fuzzy-proportional-integral-derivative hybrid controller design for ultra-high temperature milk processing

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    In the ultra-high temperature (UHT) process, fluid temperature is raised above 135 °C for a short period of time (typically 4 seconds) and then quickly cooled ensuring no microbes remain in the final product. To have better quality processed milk, a stringent temperature control system is necessary. To solve this problem a detailed control-oriented mathematical model of the heating system for UHT application is developed and a detailed block diagram is established by identifying various systems and signals. To draw the merits of a feedforward controller (transfer function or fuzzy logic based) and proportional-integral-derivative (PID) feedback compensator, a fuzzy PID hybrid controller is designed and simulated in a MATLAB environment. Findings of the simulation results indicate that the fuzzy-PID hybrid compensator concatenates the benefits of both controllers. PID controller processes the error signal and tracks the setpoint whereas the feedforward controller (transfer function or fuzzy) effectively rejects the disturbance signal’s effect on the controlled variable. The fuzzy-PID hybrid controller performs better than the individual PID or fuzzy controller

    Mechanism design for walking typed solar panel-cleaning robot using triple driving lines

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    In this study, we propose a walking-type solar power cleaning robot mechanism driven by a driving unit composed of three driving lines. The triple driving lines are driven using a link mechanism, and vacuum pads are attached to each driving line to move the robot body through a sequence operation between the three lines. Through this mechanism, the robot body can be moved horizontally with the panel without folding the pad, and the amount of vertical movement is minimized during movement. By analyzing the pressure patterns of the pads on the driving line, smooth and fast movement was possible

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    IAES International Journal of Robotics and Automation (IJRA)
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