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The precision of robotic manipulators in the industrial or medical field is very important, especially when it comes to repetitive or exhaustive tasks. Geometric deformations are the most common in this field. For this reason, new robotic vision techniques have been proposed, including 3D methods that made it possible to determine the geometric distances between the parts of a robotic manipulator. The aim of this work is to measure the angular position of a robotic arm with six degrees of freedom. For this purpose, a stereo camera and a convolutional neural network algorithm are used to reduce the degradation of precision caused by geometric errors. This method is not intended to replace encoders, but to enhance accuracy by compensating for degradation through an intelligent visual measurement system. The camera is tested and the accuracy is about one millimeter. The implementation of this method leads to better results than traditional and simple neural network methods. [ABSTRACT FROM AUTHOR]

Mobile robots are robots that can move on their own. Robots move in their environment, not fixed to a real location. With the flexibility of the navigation wheel combined with the dynamic system, the wheeled mobile robot is suitable for flexible movement on flat terrain, using tank-like tracks will be suitable for moving on difficult, complex, bumpy terrain. The article introduces a process of developing, designing a mobile robot combining a 4-degree-of-freedom arm with a mobile chassis. Kinematics, dynamics, strength of structure testing and simulation are all calculated in detail. Finally, a prototype was built and tested to prove the correctness of the process. The project has calculated the kinematics and dynamics of the model, thereby building trajectories, designing controllers for the vehicle and manipulator, thereby simulating problems on Matlab-Simulink. Designing 3D CAD models, building hardware, and testing CAE durability on Abaqus software. The results are visually tested by software, with high feasibility, is the premise for manufacturing. [ABSTRACT FROM AUTHOR]

ObjectiveTo investigate the influence of acupuncture lifting-thrusting frequency and amplitude on the analgesic effects, and its correlation with mast cell degranulation.MethodsAcute adjuvant arthritis (AA) rat models were employed. Robot-arm aided lifting-thrusting acupuncture therapy was conducted with various frequencies (ranging from 0.5 to 4 Hz) and amplitudes (ranging from 0.5 to 2.0 mm). The rats’ pain thresholds were measured multiple times before and after the therapy, and the analgesic effects were evaluated using the pain threshold recovery rate (PTRR), a normalized index. The mast cell degranulation rate (MCdR) at the acupoint was calculated, and a correlation analysis between PTRR and MCdR was performed.ResultsAcupuncture therapy partially restored the pain threshold affected by arthritis. The analgesic effects were influenced by stimulus frequency and amplitude, with best outcomes occurring at an intermediate optimal frequency of 1.0 Hz and amplitude of 1.0–1.5 mm. Similarly, the MCdR peaked at the optimal frequency and amplitude.ConclusionOur animal experiment suggests that optimal analgesic effects can be achieved with stimulation at an optimal intensity. This intensity-effect correlation appears to originate from mast cell activation rates under different mechanical stimulus.

In this paper, we propose a solution of designing and building a three-order 4D magician robot arm to palletize goods. Inverse kinematic of system is calculated. Thence, we design a suitable robot arm which can utilizing camera to palletizing goods. PID controller is used to move operating point. Simulation and experimental results are shown to prove the well operation of this robot arm.

Aiming at the difficulty of dynamic modeling of a hybrid robotic arm, a dynamic model system of industrial robotic arm based on Simscape Multibody was established with the MG400 robotic arm as the research object, which combines the motion control and data acquisition modules. The model is dynamically visualized and provides a convenient platform for studying the control algorithm of the robot arm. In response to the issues of sluggish speed and substantial position error in robot trajectory tracking control of a traditional controller, a variable gain iterative learning control methodology was designed. The robot arm control system model was employed to corroborate the trajectory tracking control under the stipulated target trajectory. The empirical outcomes indicate that in comparison to the traditional controller and the fixed-gain iterative learning controller, the variable-gain iterative learning controller can regulate the robot end trajectory more precisely, with swift tracking speed and accurate tracking posture, demonstrating commendable feasibility and portability. It offers an open-source research and development platform for the dynamic modeling of robot arm and a potent solution for the control strategy of robot arm. [ABSTRACT FROM AUTHOR]

Within this interdisciplinary study, we demonstrate the applicability of a 6D printer for soft tissue engineering models. For this purpose, a special plant was constructed, combining the technical requirements for 6D printing with the biological necessities, especially for soft tissue. Therefore, a commercial 6D robot arm was combined with a sterilizable housing (including a high‐efficiency particulate air (HEPA) filter and ultraviolet radiation (UVC) lamps) and a custom‐made printhead and printbed. Both components allow cooling and heating, which is desirable for working with viable cells. In addition, a spraying unit was installed that allows the distribution of fine droplets of a liquid. Advanced geometries on uneven or angled surfaces can be created with the use of all six axes. Based on often used bioinks in the field of soft tissue engineering (gellan gum, collagen, and gelatin methacryloyl) with very different material properties, we could demonstrate the flexibility of the printing system. Furthermore, cell‐containing constructs using primary human adipose‐derived stem cells (ASCs) could be produced in an automated manner. In addition to cell survival, the ability to differentiate along the adipogenic lineage could also be demonstrated as a representative of soft tissue engineering. [ABSTRACT FROM AUTHOR]

As a result of advances in both technology and science, it is now possible to carry out essential processes such as lifting objects and moving them by remote control of an arm. In this sense, it is much easier for a person to engage in potentially dangerous activities without running the risk of getting hurt. This article presents the development and design of a robot arm that is controlled by a smartphone device using gyroscope sensors integrated inside. Smartphones with built-in gyroscope sensors are used to operate robot arms in a flexible and affordable manner. The robot arm's movement is effectively controlled by the gyroscope sensors, which include proximity, orientation, and accelerometer sensors, to get it to the required position. The developed prototype found to capable of handling a variety of objects with a smooth movement and transporting them based on the movement of a mobile phone. The control of the arm imitates the movements of a human being, which results in the reduction of the amount of time and effort required by a person to carry out a certain process. [ABSTRACT FROM AUTHOR]

In order to enhance the synchronization of welding robot arms and improve welding quality, this study proposes a fuzzy PID-based improved deviation coupling multi-axis synchronous control method. Firstly, in response to the intricacies inherent in the compensation mechanism of the deviation coupling control structure and the substantial volume of system computation, the integration of average speed and sub-average speed is proposed to optimize the speed compensator. This integration aims to mitigate speed synchronization errors, minimize synchronization adjustment time, and elevate overall system synchronization performance. Moreover, the fuzzy PID algorithm is employed to design the controller to realize the single-motor adaptive control, leading to improvement in both system stability and dynamic response performance. Finally, a simulation model for six-axis synchronization control and an experimental platform were developed. Both simulation and experimental results demonstrate that the improved deviation coupling control method exhibits superior synchronization performance. The proposed multi-axis synchronous control method effectively heightens the synchronous performance of the six-degrees-of-freedom robotic arm. [ABSTRACT FROM AUTHOR]

This paper develops a neural network based adaptive backstepping sliding mode control for trajectory tracking problems of uncertain nonlinear Euler-Lagrange systems. Firstly, the conventional sliding mode control is conducted based on the backstepping technique. Then, the uncertain components are approximated by neural networks to overcome the drawbacks in system dynamics, system parameters, and external disturbances. One advantage of the proposed controller is that the upper bound of the uncertainties and disturbances is not required as usual, it will be estimated directly by the neural network instead. Moreover, the chattering phenomenon, which is typical of the sliding mode control, is countably reduced. The stability of the closed loop and the convergence of the approximation are proven mathematically via Lyapunov stable theory. Finally, the simulation and the comparison with the recent existing works are employed to demonstrate the effectiveness of the introduced control scheme. [ABSTRACT FROM AUTHOR]

The field of robotics and autonomous systems has witnessed significant advancements in recent years, with an increasing focus on enhancing the capabilities of robotic agents through RL. This project centres around applying Reinforcement Learning (RL) techniques to do object manipulation tasks with a specific focus on making a robot arm reach a target object. Using a combination of Gazebo and Robot Operating System (ROS) environments, the robot arm is trained using custom OpenAI Gym environments to simulate the task. The primary objective involves positioning the end-effector of the robot arm close to a designated object and overcoming challenges such as self-collisions during movements. Various iterations of RL training, including different reward logics, curriculum learning approaches, and fine-tuning parameters, are explored to refine the decision-making capabilities of the agent. The training process of Curriculum Learning involves a phased approach, starting with basic movements and progressing to more complex tasks, demonstrating improved performance. However, challenges such as prolonged training times and uncertainties in arm behaviour persist. The project highlights the complexities inherent in designing effective RL strategies for robotic systems and stresses the need for further research to enhance computational efficiency and reliability in real-world applications.

Aiming at the problem that human beings are prone to fatigue when they repeatedly perform a single action in the performance test of the driver attention monitoring system, a humanoid robot arm is designed to simulate the driver's behaviors such as answering and making handsets and smoking. Firstly, based on the exoskeleton design method, the structure of the robot arm and the bionic hand is designed. Secondly, the improved D-H method is used to establish the kinematics model of the manipulator; the forward and inverse kinematics are solved, and the workspace is analyzed; the dynamics simulation of the robot arm is carried out in Adams software to obtain its motion characteristics and load characteristics. The simulation results show that the structural design of the manipulator is reasonable, and the selection of joint flexible actuators meets the requirements.

Copyright of Przegląd Elektrotechniczny is the property of Przeglad Elektrotechniczny and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Shanghai University of Engineering Science / Shanghai Gongcheng Jishu Daxue Xuebao is the property of Journal of Shanghai University of Engineering Science Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Abstract Within this interdisciplinary study, we demonstrate the applicability of a 6D printer for soft tissue engineering models. For this purpose, a special plant was constructed, combining the technical requirements for 6D printing with the biological necessities, especially for soft tissue. Therefore, a commercial 6D robot arm was combined with a sterilizable housing (including a high‐efficiency particulate air (HEPA) filter and ultraviolet radiation (UVC) lamps) and a custom‐made printhead and printbed. Both components allow cooling and heating, which is desirable for working with viable cells. In addition, a spraying unit was installed that allows the distribution of fine droplets of a liquid. Advanced geometries on uneven or angled surfaces can be created with the use of all six axes. Based on often used bioinks in the field of soft tissue engineering (gellan gum, collagen, and gelatin methacryloyl) with very different material properties, we could demonstrate the flexibility of the printing system. Furthermore, cell‐containing constructs using primary human adipose‐derived stem cells (ASCs) could be produced in an automated manner. In addition to cell survival, the ability to differentiate along the adipogenic lineage could also be demonstrated as a representative of soft tissue engineering.

The paper presents the development of a new platform that represents a robotic arm system, useful and appropriate for the Additive Manufacturing applications. The main objective of this work was to explore the feasibility of integrating the off-the-shelf (COTS) Additive Manufacturing technologies and the six-degree-of-freedom industrial robotic arm, achieving a 3D Additive Manufacturing system which is able to perform six-degree fused deposition printing. The authors investigated the materials suitable to be used and performed more experiments with the aim to find the right configuration of the printing system. Finally, the technical issues reported during the experimental programme have been solved, the system being prepared to carry out workpieces with more complex shapes and more types of polymers.

As the intelligent and information technology advancing rapidly, enterprises selling refined oil product become active in exploring the intelligent refueling robot technology, in attempt to solve the problems of recruitment difficulty, high labor costs, high working intensity and inadequate customer experience. The research systematically reviewed the development of refueling robots at home and abroad,discussed in detail the key technologies such as the refueling robot arm technology and its control system, end actuator, visual identification system, explosion-proof and intelligent interaction. The research made a statistical analysis by observing 2 000 times of refueling actions conducted by 40 refueling staff of varying proficiency and from different types of petrol stations. Then the research compared systematically the factors of efficiency and economy between the two service modes of manual filling and robot filling by taking into consideration the difference of petrol stations in different regions. The analysis results provide references for determining the research and development objectives and measuring commercialization conditions of the refueling robot. On this basis, the research proposed the objective of the application of refueling robots and development goals and the directions for improvements.

The precision of robotic manipulators in the industrial or medical field is very important, especially when it comes to repetitive or exhaustive tasks. Geometric deformations are the most common in this field. For this reason, new robotic vision techniques have been proposed, including 3D methods that made it possible to determine the geometric distances between the parts of a robotic manipulator. The aim of this work is to measure the angular position of a robotic arm with six degrees of freedom. For this purpose, a stereo camera and a convolutional neural network algorithm are used to reduce the degradation of precision caused by geometric errors. This method is not intended to replace encoders, but to enhance accuracy by compensating for degradation through an intelligent visual measurement system. The camera is tested and the accuracy is about one millimeter. The implementation of this method leads to better results than traditional and simple neural network methods.

To improve the efficiency of robots, a novel sustainable design of a robotic arm is proposed that can address the thermal, vibration, energy usage and dynamic stiffness issues. The proposed design utilises easy-to-produce carbon fibre tubes including some that are commercially available, for the robot link instead of traditional materials, which can be heavy and carbon intensive. The design involves arranging several carbon fibre reinforced polymer (CFRP) tubes in a specific array inside an epoxy resin substrate. Based on this design, a Finite Element Analysis (FEA) was implemented demonstrating the relatively low mass and high stiffness characteristics. Design optimisation was then performed using custom generated MATLAB® code to reduce the computation time. The proposed design for a one-meter-long robot link with a diameter of 108 mm offers a stiffness of 0.75 N/μm. A structural steel link, with the same stiffness, is 33 % heavier than the concept design. The design maintains thermal stability with about a third of the thermal deformation seen in structural steel. [ABSTRACT FROM AUTHOR]

This study focuses on the development of a visual system designed to facilitate object detection for the Spinbotics robotic arm in spatial environments. The primary objective is to enable accurate detection and classification of diverse objects, enhancing the arm's capability to grasp and manipulate items effectively. The system employs the YOLOv7 deep neural network, fine-tuned using transfer learning on a local computing infrastructure. Compared to traditional methods like R-CNN and SSD, YOLOv7 offers superior real-time processing capabilities and efficiency, making it well-suited for dynamic environments. Through extensive training and testing, the system demonstrates robust performance in detecting objects across varied scenes and identifying optimal grasp points. This research underscores the effectiveness of integrating advanced computer vision techniques to enhance the operational efficiency and versatility of robotic manipulators in real-world applications. [ABSTRACT FROM AUTHOR]

A gecko foot-inspired, mushroom-shaped artificial dry adhesive exploiting intermolecular forces between microstructure and surface has drawn research attention for its strong adhesive force. However, the high pull-off strength corresponding to the adhesive force matters when detaching fragile substrates. In this study, we report a vacuum-powered soft actuator having oblique air chambers and a dry adhesive. The soft actuator performs coupled contraction and twisting by applying negative pneumatic pressure inward and exhibits not only high pull-off strength but also easy detachment. This effective detachment can be achieved thanks to the twisting motion of the soft actuator. The detachment performances of the actuator models are assessed using a 6-degrees-of-freedom robot arm. Results show that the soft actuators exhibit remarkable pull-off strength decrement from ~20 N cm−2 to ~2 N cm−2 due to the twisting. Finally, to verify a feasible application of this study, we utilize the inherent compliance of the actuators and introduce a glass transfer system for which a glass substrate on a slope is gripped by the flexibility of the soft actuators and delivered to the destination without any fracture. Vacuum-powered soft actuator with oblique air chambers for easy detachment of artificial dry adhesive by coupled contraction and twisting In this work, we report a vacuum-powered soft actuator with artificial dry adhesive. We used a vacuum for the easy detachment of the dry adhesive and verified a feasibility for the real-industrial fields. The highlights and novelty of this work are as follows: • Vacuum-powered soft actuator with Gecko inspired dry adhesive • High adhesion with an easy detachment by twisting motion • Mechanical analysis of the easy detachment • Novel glass transfer system with the 6-DOF robot arm based on the soft actuator [ABSTRACT FROM AUTHOR]

Small–size (desktop) robot arms are being increasingly used in research and education, where low–cost implementation prevails over the need for high dynamic performance. This paper presents a design of a control unit for a 6DoF desktop robot arm with cylindrical joints actuated with stepper motors. Feedforward control, often chosen as a control strategy for stepper motors due to the simplicity of control algorithms, as well as the cost–effectiveness of the solution, is selected as the control method. The applicative software with GUI developed in Matlab is presented. A trajectory planner based on the solution of the inverse kinematics problem and the user–selected joint velocity profile is implemented. In order to avoid step skipping occurrence, the torque in joints necessary to produce the programmed joints motion have to be achievable by the installed stepper motors. As a part of applicative software, the check on the feasibility of the programmed robot trajectories by numerical simulation of solution of inverse dynamics problem in Simscape Multibody is performed. The microcontroller is used as an interface device that controls the stepper motor drivers. The applicative software communicates with the microcontroller using the TCP protocol. [ABSTRACT FROM AUTHOR]

In order to enhance the synchronization of welding robot arms and improve welding quality, this study proposes a fuzzy PID-based improved deviation coupling multi-axis synchronous control method. Firstly, in response to the intricacies inherent in the compensation mechanism of the deviation coupling control structure and the substantial volume of system computation, the integration of average speed and sub-average speed is proposed to optimize the speed compensator. This integration aims to mitigate speed synchronization errors, minimize synchronization adjustment time, and elevate overall system synchronization performance. Moreover, the fuzzy PID algorithm is employed to design the controller to realize the single-motor adaptive control, leading to improvement in both system stability and dynamic response performance. Finally, a simulation model for six-axis synchronization control and an experimental platform were developed. Both simulation and experimental results demonstrate that the improved deviation coupling control method exhibits superior synchronization performance. The proposed multi-axis synchronous control method effectively heightens the synchronous performance of the six-degrees-of-freedom robotic arm.

ABSTRACTA gecko foot-inspired, mushroom-shaped artificial dry adhesive exploiting intermolecular forces between microstructure and surface has drawn research attention for its strong adhesive force. However, the high pull-off strength corresponding to the adhesive force matters when detaching fragile substrates. In this study, we report a vacuum-powered soft actuator having oblique air chambers and a dry adhesive. The soft actuator performs coupled contraction and twisting by applying negative pneumatic pressure inward and exhibits not only high pull-off strength but also easy detachment. This effective detachment can be achieved thanks to the twisting motion of the soft actuator. The detachment performances of the actuator models are assessed using a 6-degrees-of-freedom robot arm. Results show that the soft actuators exhibit remarkable pull-off strength decrement from ~20 N cm−2 to ~2 N cm−2 due to the twisting. Finally, to verify a feasible application of this study, we utilize the inherent compliance of the actuators and introduce a glass transfer system for which a glass substrate on a slope is gripped by the flexibility of the soft actuators and delivered to the destination without any fracture.

Copyright of Control Theory & Applications / Kongzhi Lilun Yu Yinyong is the property of Editorial Department of Control Theory & Applications and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In this paper, a support vector machine (SVM) model is trained to classify objects in the automatic sorting system using a robot arm. The robot arm is used to grab objects and move them to the right position according to their shape predicted by the SVM model. The position of objects in the image is identified by using the contouring technique. The centroid of objects is calculated from the image moment of the object's contour. The calibration is conducted to get the parameters of the camera and combine with the pinhole camera model to compute the 3D position of the objects. The feature vector for SVM training is the zone feature and the SVM kernel is the Gaussian kernel. In the experiment, the SVM model is used to classify four objects with different shapes. The results show that the accuracy of the SVM classifier is 99.72%, 99.4%, 99.4% and 99.88% for four objects, respectively. [ABSTRACT FROM AUTHOR]

Copyright of Machine Tool & Hydraulics is the property of Guangzhou Mechanical Engineering Research Institute (GMERI) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Harbin Institute of Technology. Social Sciences Edition / Haerbin Gongye Daxue Xuebao. Shehui Kexue Ban is the property of Harbin Institute of Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This manuscript presents an efficient algorithm for solving the inverse kinematics problem of a 6R robot manipulator to be deployed on embedded control hardware. The proposed method utilizes the geometric relationship between the end-effector and the base of the manipulator, resulting in a computationally efficient solution. The approach aims to minimize computational complexity and memory consumption while maintaining the accuracy and real-time performance demonstrated by simulations and verified by experimental results on an embedded system. Furthermore, the manipulator is analyzed in terms of singularities, limits, the workspace, and general solvability. Due to the simplicity of the algorithm, a platform-independent implementation is possible. As a result, the average calculation time is reduced by a factor of five to eight and the average error is decreased by a factor of fifty compared to a powerful analytical solver. [ABSTRACT FROM AUTHOR]

In this paper, the Deep Deterministic Policy Gradient (DDPG) reinforcement learning algorithm is employed to enable a double-jointed robot arm to reach continuously changing target locations. The experimentation of the algorithm is carried out by training an agent to control the movement of this double-jointed robot arm. The architectures of the actor and cretic networks are meticulously designed and the DDPG hyperparameters are carefully tuned. An enhanced version of the DDPG is also presented to handle multiple robot arms simultaneously. The trained agents are successfully tested in the Unity Machine Learning Agents environment for controlling both a single robot arm as well as multiple simultaneous robot arms. The testing shows the robust performance of the DDPG algorithm for empowering robot arm manoeuvring in complex environments. [ABSTRACT FROM AUTHOR]

To achieve accurate position tracking, there is a need to develop high-fidelity robot arm models that are compliant and affordable. However, physics-based models are constrained by their stiffness and complexity. Therefore, reduced-order modelling developed from data through sub-space system identification is proposed as a solution to this problem. A high-fidelity simulation model of a two-link robot arm developed in MATLAB and Simulink was used to generate synthetic data, and the data acquired was used for the estimation and validation of first- and second-order linear state-space models. Due to its effective tracking characteristics, the model predictive control technique was used for trajectory tracking. The results of the simulations demonstrate that the first-order and second-order models can track the intended set points accurately but at the cost of larger joint torques required to counteract gravity. The results show that low-order and data-compliant models can follow trajectories with high precision. MATLAB 2020a was used for all simulations. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to quickly and stably achieve grasping objects with a 3D robot arm controlled by electrooculography (EOG) signals. A EOG signal is a biological signal generated when the eyeballs move, leading to gaze estimation. In conventional research, gaze estimation has been used to control a 3D robot arm for welfare purposes. However, it is known that the EOG signal loses some of the eye movement information when it travels through the skin, resulting in errors in EOG gaze estimation. Thus, EOG gaze estimation is difficult to point out the object accurately, and the object may not be appropriately grasped. Therefore, developing a methodology to compensate, for the lost information and increase spatial accuracy is important. This paper aims to realize highly accurate object grasping with a robot arm by combining EMG gaze estimation and the object recognition of camera image processing. The system consists of a robot arm, top and side cameras, a display showing the camera images, and an EOG measurement analyzer. The user manipulates the robot arm through the camera images, which can be switched, and the EOG gaze estimation can specify the object. In the beginning, the user gazes at the screen's center position and then moves their eyes to gaze at the object to be grasped. After that, the proposed system recognizes the object in the camera image via image processing and grasps it using the object centroid. The object selection is based on the object centroid closest to the estimated gaze position within a certain distance (threshold), thus enabling highly accurate object grasping. The observed size of the object on the screen can differ depending on the camera installation and the screen display state. Therefore, it is crucial to set the distance threshold from the object centroid for object selection. The first experiment is conducted to clarify the distance error of the EOG gaze estimation in the proposed system configuration. As a result, it is confirmed that the range of the distance error is 1.8–3.0 cm. The second experiment is conducted to evaluate the performance of the object grasping by setting two thresholds from the first experimental results: the medium distance error value of 2 cm and the maximum distance error value of 3 cm. As a result, it is found that the grasping speed of the 3 cm threshold is 27% faster than that of the 2 cm threshold due to more stable object selection. [ABSTRACT FROM AUTHOR]

This document presents the development of a prototype of a Cartesian robot with a 5 degrees-of-freedom articulated robot arm for possible applications in a wet spinning process at the laboratory-level. The mechatronic system was developed using various modular electronics elements compatible with an ArduinoTM Mega 2560 microcontroller. The control algorithm recognizes the position of the servomotors and the speed of the motors so that the prototype performs a complete cycle of displacement in 67 s, which includes the transport of a polymeric filament immersed in a coagulation bath for 10 s. A structural analysis indicates that there will be no tension failures because the maximum and axial stress of the Cartesian robot was 2.89 MPa while the von Mises tension of the robotic arm was 468 MPa, both tensions below their upper limits. The pulse signals, in the order of 4000 +25 ms, of the servomotors were consistent in 96-98% repeatability and 3-19% reproducibility. Forty percent of the extrusion tests performed were satisfactory, since the transport of a polymeric filament within a coagulant solution was achieved. [ABSTRACT FROM AUTHOR]