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Journal articles on the topic 'Microsoft Robotics Studio'
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Jackson, J. "Microsoft robotics studio: A technical introduction." IEEE Robotics & Automation Magazine 14, no. 4 (2007): 82–87. http://dx.doi.org/10.1109/m-ra.2007.905745.
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Gustiana, Milda, Youllia Indrawaty, and Arry Febriandi. "Perancangan Mobile Manipulator Robot Secara Simulasi Menggunakan Microsoft Robotics Developer Studio." MIND Journal 3, no. 1 (2019): 15–23. http://dx.doi.org/10.26760/mindjournal.v3i1.15-23.
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Mobile Manipulator Robot merupakan suatu jenis robot yang terdiri atas bagianmobilitas (mobile) dan bagian manipulator. Pemanfaatan robot jenis ini antara laindalam hal keamanan misalnya untuk mengambil dan mengangkut bendaberbahaya. Simulasi dilakukan untuk mengurangi kesalahan saat prosesperancangan yang dapat terjadi sepert dalam hal perancangan fisik maupun padapemrograman. Pada penelitian ini dilakukan perancangan mobile manipulatorrobot dengan methodology for robotic simulation dan disimulasikan menggunakanMicrosoft Robotics Developer Studio. Bagian manipulator dari robot yang dirancangmemiliki 6 DOF. Simulasi yang dihasilkan menunjukkan kesesuaian denganrancangan yang dibuat
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Matta-Gómez, Antonio, Jaime Del Cerro, and Antonio Barrientos. "Multi-robot data mapping simulation by using microsoft robotics developer studio." Simulation Modelling Practice and Theory 49 (December 2014): 305–19. http://dx.doi.org/10.1016/j.simpat.2014.10.003.
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Tsai, W. T., Xin Sun, Qian Huang, and Helen Karatza. "An ontology-based collaborative service-oriented simulation framework with Microsoft Robotics Studio®." Simulation Modelling Practice and Theory 16, no. 9 (2008): 1392–414. http://dx.doi.org/10.1016/j.simpat.2008.07.007.
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MENEGATTI, EMANUELE, GIOVANNI SILVESTRI, ENRICO PAGELLO, et al. "3D MODELS OF HUMANOID SOCCER ROBOT IN USARSim AND ROBOTICS STUDIO SIMULATORS." International Journal of Humanoid Robotics 05, no. 03 (2008): 523–46. http://dx.doi.org/10.1142/s0219843608001492.
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This paper describes our experience in the simulation of humanoid soccer robots using two general purposes 3D simulators, namely USARSim and Microsoft Robotics Studio. We address the problem of the simulation of a soccer match among two teams of small humanoid robots in the RoboCup Soccer Kid-Size Humanoid competitions. The paper reports the implementation of the virtual models of the Robovie-M humanoid robot platform in the two simulators. Robovie-M was the robot used by our team "Artisti" in the RoboCup 2006 competitions. This paper focuses on the procedures needed to implement the virtual models of the robot and in the details of the models. We describe experiments assessing the feasibility and the fidelity of the two simulators.
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Zhang, Wei Bing, Chu Guang Liang, and Yun Hang Zhu. "The Real-Time Simulation System of Bionic Robot Fish Water-Polo-Game Based on MSRS." Applied Mechanics and Materials 644-650 (September 2014): 294–97. http://dx.doi.org/10.4028/www.scientific.net/amm.644-650.294.
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The system simulates completely the water polo-game of entity bionic robot-fish, designed and developed based on Microsoft Robotics Studio SDK(MSRS) 1.5, which includes seven modules, such as client strategy, server core control, common interface, environment setting, simulation data display, assistant function, fish robot kinematics modeling and so on. The simulation system simulates the motion of bionic robot fish and the entire process of water-polo-game in real time, and provides simulation testing platform for bionic-robot-fish model optimization, machine fish movement algorithm, and robot fish water-polo-game.
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Latumakulita, Luther, and Chriestie E. J. C. Montolalu. "SISTEM PAKAR PENDIAGNOSA PENYAKIT GINJAL." JURNAL ILMIAH SAINS 11, no. 1 (2011): 131. http://dx.doi.org/10.35799/jis.11.1.2011.55.
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Sistem pakar merupakan salah satu cabang kecerdasan buatan yang mempelajari bagaimana meniru cara berpikir seorang pakar dalam menyelesaikan suatu permasalahan. Kecerdasan buatan adalah salah satu bidang ilmu komputer yang mendayagunakan komputer sehingga dapat berperilaku cerdas seperti manusia. Ilmu komputer mengembangkan perangkat lunak dan perangkat keras untuk menirukan tindakan manusia. Aktifitas manusia yang ditirukan seperti penalaran, penglihatan, pembelajaran, pemecahan masalah, pemahaman bahasa alami, dan sebagainya. Sesuai definisi, teknologi kecerdasan buatan dipelajari dalam bidang-bidang seperti Robotika (Robotics), Penglihatan Komputer (Computer Vision), Pengolahan Bahasa Alami (Natural Language Processing), Pengenalan Pola (Pattern Recognition), Sistem Syaraf Buatan (Artificial Neural System), Pengenalan Suara (Speech Recognition), dan Sistem pakar (Expert System). Sistem pakar terdiri 2 bagian pokok, yaitu lingkungan pengembangan (development environment) digunakan sebagai pembangun sistem pakar baik dari segi pembangun komponen maupun basis pengetahuan dan lingkungan konsultasi (consultation environment)digunakan oleh seseorang yang bukan ahli untuk berkonsultasi. Lingkungan pengembangan digunakan oleh ES builder untuk membangun komponen dan memasukan penetahuan kedalam basis pengetahuan. Aplikasi Sistem Pakar ini adalah merupakan paket perangkat lunak yang membahas bagaimana cara untuk mendeteksi penyakit ginjal pada manusia. Sistem pakar pendeteksi penyakit ginjal pada manusia ini terdiri atas 2 bagian yaitu : Lingkungan Konsultasi (Development environment) dan Lingkungan Pengembangan (Consultation environment). Bahasa pemrograman yang digunakan untuk membuat aplikasi system pakar ini Microsoft Visual Studio 6.0 dengan databasenya menggunakan Microsoft Access 2003. sesuai dengan bahasa pemrograman yang digunakan maka interface yang akan ditampilkan dalam memberikan informasi bagi user akan berbentuk visual. EXPERT SYSTEM FOR KIDNEY DISEASE DIAGNOSISABSTRACTExpert System (ES) is an artifial intelligence which aplicate a profesional’s way of think in solving a problem. Artificial intelligence is a computer field which move computer to operate as smart as human brain. This computer science develop software and hardware to act like a human. Human activities which modify such as reasoning, vision, learning, problem solving, natural language, etc. Base on that definition, artificial intelligence technologi were improved in many fields such as Robotics, Computer Vision, Natural Language Processing, Pattern Recognition, Artificial Neural System, Speech Recognition, and Expert System. Expert System consist of two main fields: development environment used as expert system builder in component builder and also knowledge base, and consultation builder used by a person who has not ability in in consultation. Development environment used by ES builder to build component and input knowledge in to the knowledge base. This Expert System Aplication is a software sistem, which improve the aplication to detect kidney disease for human. Expert System detection of kidney disease for human consists of two parts: Development environment and Consultation environment.Programming language, which used to build this Expert System aplication, is Microsoft Visual Studio 6.0 with database Microsoft Access 2003. Base on the language programming used, then the interface, to give the information for user, will be shown in visual.
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NIKITIN, YURY, ALEXANDR TURYGIN, and VLADIMIR STOLLMANN. "MULTILEVEL CONTROL OF A TRANSPORT ROBOT." MM Science Journal 2022, no. 2 (2022): 5662–69. http://dx.doi.org/10.17973/mmsj.2022_06_2022089.
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The control systems of modern robots are multilevel. The upper level control of the transport robot by voice commands and simulation of its motion in the software product Microsoft Robotics Developer Studio are considered. Visual Programming Language for creating and debugging applications was used to simulate the motion of the transport robot. An Android tablet or mobile phone with an application is used to recognize voice commands and the robot can be controlled using the Bluetooth interface. A program has been developed that will allow a human to control the robot using speech. An example of simulation of the robot and its motion path using voice control is given. The developed control system allows the transport robot to follow from one target point to another using voice control. At a low level, optimal asynchronous motor based actuator control using a model oriented approach in SimInTech is considered.
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Wang, Baofang, Chen Qian, and Qingwei Chen. "A Dynamics Controller Design Method for Car-like Mobile Robot Formation Control." MATEC Web of Conferences 160 (2018): 06003. http://dx.doi.org/10.1051/matecconf/201816006003.
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A dynamics controller design method based on characteristic model is proposed for the formation control problem of car-like mobile robots. Only kinematics controller is not enough for some cases such as the environment is rugged, and the dynamics parameters of the robot are time-varying. Simulation results show that the proposed method can improve the responding speed of the mobile robots and maintain high formation accuracy. First, we obtain the kinematic error state equations according to the leader-follower method. A kinematics controller is designed and the stability is proved by Lyapunov theory. Then the characteristic model of the dynamics inner loop is established. A sliding mode controller is designed based on the second order discrete model, and the stability of the closed-loop system is analyzed. Finally, simulations are designed in MATLAB and Microsoft Robotics Developer Studio 4 (MRDS) to verify the effectiveness of the proposed method.
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Torres-Torriti, M., T. Arredondo, and P. Castillo-Pizarro. "Survey and comparative study of free simulation software for mobile robots." Robotica 34, no. 4 (2014): 791–822. http://dx.doi.org/10.1017/s0263574714001866.
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SUMMARYIn robotics, simulation has become an essential tool for research, education, and design purposes. Various software tools for mobile robot simulation have been developed and have reached different levels of maturity in recent years. This paper presents a general survey of mobile robot simulation tools and discusses qualitative and quantitative aspects of selection of four major simulators publicly available at no cost: Carmen, Player-Stage-Gazebo, Open Dynamics Engine, and Microsoft Robotics Developer Studio. The comparison of the simulators is aimed at establishing the range of applications for which these are best suited as well as their accuracy for certain simulation tasks. The simulators chosen for detailed comparison were selected considering their level of maturity, modularity, and popularity among engineers and researchers. The qualitative comparison included a discussion of relevant features. The quantitative analysis entailed the development of a detailed dynamical model of a mobile robot on a road with varying slope. This model was used as benchmark to compare the accuracy of each simulator. The validity of the simulated results was also contrasted against measurements obtained from experiments with a real robot. This research and analysis should be very valuable to educators, engineers, and researchers who are always seeking adequate tools for simulating autonomous mobile robots.
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Nikitin, Yu R., and M. Yu Teplyakova. "Transport Robot Control by Voice Commands." Intellekt. Sist. Proizv. 15, no. 3 (2017): 112. http://dx.doi.org/10.22213/2410-9304-2017-3-112-117.
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В системах управления современных роботов используется нечеткая логика, поэтому целесообразно подавать команды управления роботом на основе нечеткой логики, которая позволит роботам эффективно выполнять поставленные задачи. В статье рассматривается управление транспортным роботом голосовыми командами и моделирование его движения в программном продукте Microsoft Robotics Developer Studio. Для моделирование движения транспортного робота использовался язык Visual Programming Language (VPL) - среда визуального программирования для создания и отладки приложений. Для распознавания голосовых команд используется планшетный компьютер или мобильный телефон с операционной системы Android с приложением, при помощи которого можно управлять роботом с использованием интерфейса Bluetooth. Разработана программа, которая позволит человеку управлять роботом с помощью речи. Получена визуальная программа управления движением транспортного робота. Приведен пример моделирования робота и его траектория движения с использованием голосового управления. Разработанная система управления позволяет следовать транспортному роботу от одной целевой точки к другой с использованием голосового управления. Задача управления роботом с использованием голосового управления существенно упрощается, поскольку она практически не требует специальных навыков от оператора. В конечном счете, голосовое управление облегчит использование роботов в промышленности, быту и других областях. Управлять можно будет не только роботами, но и другими устройствами, имеющими микропроцессорное управление.
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Guzel, Mehmet Serdar, and Robert Bicker. "A Behaviour-Based Architecture for Mapless Navigation Using Vision." International Journal of Advanced Robotic Systems 9, no. 1 (2012): 18. http://dx.doi.org/10.5772/46200.
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Autonomous robots operating in an unknown and uncertain environment must be able to cope with dynamic changes to that environment. For a mobile robot in a cluttered environment to navigate successfully to a goal while avoiding obstacles is a challenging problem. This paper presents a new behaviour-based architecture design for mapless navigation. The architecture is composed of several modules and each module generates behaviours. A novel method, inspired from a visual homing strategy, is adapted to a monocular vision-based system to overcome goal-based navigation problems. A neural network-based obstacle avoidance strategy is designed using a 2-D scanning laser. To evaluate the performance of the proposed architecture, the system has been tested using Microsoft Robotics Studio (MRS), which is a very powerful 3D simulation environment. In addition, real experiments to guide a Pioneer 3-DX mobile robot, equipped with a pan-tilt-zoom camera in a cluttered environment are presented. The analysis of the results allows us to validate the proposed behaviour-based navigation strategy.
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Kim, Jinwook, Yoon-Gu Kim, and Jinung An. "A Fuzzy Obstacle Avoidance Controller Using a Lookup-Table Sharing Method and Its Applications for Mobile Robots." International Journal of Advanced Robotic Systems 8, no. 5 (2011): 62. http://dx.doi.org/10.5772/45700.
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A Lookup-Table (LUT) based design enhances the processing speed of a fuzzy obstacle avoidance controller by reducing the operation time. Also, a LUT sharing method provides efficient ways of reducing the LUT memory size. In order to share the LUT which is used for a fuzzy obstacle avoidance controller, an idea of using a basis function is developed. As applications of the shared LUT-based fuzzy controller, a laser-sensor-based fuzzy controller and an ultrasonic-sensor-based fuzzy controller are introduced in this paper. This paper suggests a LUT sharing method that reduces the LUT buffer size without a significant degradation of the performance. The LUT sharing method makes the buffer size independent of the fuzzy system's complexity. A simulation using MSRDS (Microsoft Robotics Developer Studio) is used to evaluate the proposed method. To investigate the performance of the controller, experiments are carried out using a Pioneer P3-DX with LabVIEW as an integration tool. Although the simulation and experiments show little difference between the fully valued LUT-based method and the LUT sharing method in terms of the operation time, the LUT sharing method reduces almost 95% of the full-valued LUT-based buffer size.
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Hill, Gary, and Scott Turner. "Problems First, Second and Third." International Journal of Quality Assurance in Engineering and Technology Education 3, no. 3 (2014): 88–109. http://dx.doi.org/10.4018/ijqaete.2014070104.
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This paper considers the need to focus initial programming education on problem-solving, prior to the teaching of programming syntax and software design methodology. The main vehicle for this approach is simple Lego based robots programmed in Java, followed by the programming of a graphical representation/simulation to develop programming skills. Problem solving is not trivial (Beaumont & Fox, 2003) and is an important skill, central to computing and engineering. The paper extends the authors earlier research on problems first and problem solving (Hill & Turner, 2011) to further emphasise the importance of problem-solving, problem based learning and the benefits of both physical and visual solutions. An approach will be considered, illustrated with a series of problem-solving tasks that increase in complexity at each stage and give the students practice in attempting problem-solving approaches, as well as assisting them to learn from their mistakes. Some of the problems include ambiguities or are purposely ill-defined, to enable the student to resolve these as part of the process. The benefits to students will be discussed including students' statements that this approach, using robots, provides a method to visually and physically see the outcome of a problem. In addition, students report that the method improves their satisfaction with the course. The importance of linking the problem-solving robot activity and the programming assignment, whilst maintaining the visual nature of the problem, will be discussed, together with the comparison of this work with similar work reported by other authors relating to teaching programming using robots (Williams, 2003). In addition, limitations will be discussed relating to the access to the physical robots and the alternative attempts to simulate the robots using three options of, Microsoft Robotics Studio (MSRS), Lego Mindstorms and Greenfoot simulators.
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Hill, Gary, and Scott Turner. "Problems First, Second, and Third." International Journal of Quality Assurance in Engineering and Technology Education 3, no. 4 (2014): 66–90. http://dx.doi.org/10.4018/ijqaete.2014100103.
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This paper considers the need to focus initial programming education on problem-solving, prior to the teaching of programming syntax and software design methodology. The main vehicle for this approach is simple Lego based robots programmed in Java, followed by the programming of a graphical representation/simulation to develop programming skills. Problem solving is not trivial (Beaumont & Fox, 2003) and is an important skill, central to computing and engineering. The paper extends the authors earlier research on problems first and problem solving () to further emphasise the importance of problem-solving, problem based learning and the benefits of both physical and visual solutions. An approach will be considered, illustrated with a series of problem-solving tasks that increase in complexity at each stage and give the students practice in attempting problem-solving approaches, as well as assisting them to learn from their mistakes. Some of the problems include ambiguities or are purposely ill-defined, to enable the student to resolve these as part of the process. The benefits to students will be discussed including students' statements that this approach, using robots, provides a method to visually and physically see the outcome of a problem. In addition, students report that the method improves their satisfaction with the course. The importance of linking the problem-solving robot activity and the programming assignment, whilst maintaining the visual nature of the problem, will be discussed, together with the comparison of this work with similar work reported by other authors relating to teaching programming using robots (). In addition, limitations will be discussed relating to the access to the physical robots and the alternative attempts to simulate the robots using three options of, Microsoft Robotics Studio (MSRS), Lego Mindstorms and Greenfoot simulators.
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D'Souza, Floyd, João Costa, and J. Norberto Pires. "Development of a solution for adding a collaborative robot to an industrial AGV." Industrial Robot: the international journal of robotics research and application 47, no. 5 (2020): 723–35. http://dx.doi.org/10.1108/ir-01-2020-0004.
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Purpose The Industry 4.0 initiative – with its ultimate objective of revolutionizing the supply-chain – putted more emphasis on smart and autonomous systems, creating new opportunities to add flexibility and agility to automatic manufacturing systems. These systems are designed to free people from monotonous and repetitive tasks, enabling them to concentrate in knowledge-based jobs. One of these repetitive functions is the order-picking task which consists of collecting parts from storage (warehouse) and distributing them among the ordering stations. An order-picking system can also pick finished parts from working stations to take them to the warehouse. The purpose of this paper is to present a simplified model of a robotic order-picking system, i.e. a mobile manipulator composed by an automated guided vehicle (AGV), a collaborative robot (cobot) and a robotic hand. Design/methodology/approach Details about its implementation are also presented. The AGV is needed to safely navigate inside the factory infrastructure, namely, between the warehouse and the working stations located in the shop-floor or elsewhere. For that purpose, an ActiveONE AGV, from Active Space Automation, was selected. The collaborative robot manipulator is used to move parts from/into the mobile platform (feeding the working stations and removing parts for the warehouse). A cobot from Kassow Robots was selected (model KR 810), kindly supplied by partner companies Roboplan (Portugal) and Kassow Robotics (Denmark). An Arduino MKR1000 board was also used to interconnect the user interface, the AGV and the collaborative robot. The graphical user interface was developed in C# using the Microsoft Visual Studio 2019 IDE, taking advantage of this experience in this type of language and programming environment. Findings The resulting prototype was fully demonstrated in the partner company warehouse (Active Space Automation) and constitutes a possible order-picking solution, which is ready to be integrated into advanced solutions for the factories of the future. Originality/value A solution to fully automate the order-picking task at an industrial shop-floor was presented and fully demonstrated. The objective was to design a system that could be easy to use, to adapt to different applications and that could be a basic infrastructure for advanced order-picking systems. The system proved to work very well, executing all the features required for an order-picking system working in an Industry 4.0 scenario where humans and machines must act as co-workers. Although all the system design objectives were accomplished, there are still opportunities to improve and add features to the presented solution. In terms of improvements, a different robotic hand will be used in the final setup, depending on the type of objects that are being required to move. The amount of equipment that is located on-board of the AGV can be significantly reduced, freeing space and lowering the weight that the AGV carries. For example, the controlling computer can be substituted by a single-board-computer without any advantage. Also, the cobot should be equipped with a wrist camera to identify objects and landmark. This would allow the cobot to fully identify the position and orientation of the objects to pick and drop. The wrist camera should also use bin-picking software to fully identify the shape of the objects to pick and also their relative position (if they are randomly located in a box, for example). These features are easy to add to the developed mobile manipulator, as there are a few vision systems in the market (some that integrate with the selected cobot) that can be easily integrated in the solution. Finally, this paper reports a development effort that neglected, for practical reasons, all issues related with certification, safety, training, etc. A future follow-up paper, reporting a practical use-case implementation, will properly address those practical and operational issues.
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"Braintech joins Microsoft's Robotics Studio Partner Program." Industrial Robot: An International Journal 34, no. 4 (2007). http://dx.doi.org/10.1108/ir.2007.04934dab.001.
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Chakraborty, Sudip, and P. S. Aithal. "Demonstration of Drawing by Robotic Arm using RoboDK and C#." International Journal of Applied Engineering and Management Letters, June 30, 2021, 153–58. http://dx.doi.org/10.47992/ijaeml.2581.7000.0099.
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Purpose: Robots are transforming the world, and soon they will take part or assist in our all-daily life activities. There are several fields where robots are already doing well, like Surgery, painting, industrial automation, autonomous navigation, engraving, 3D printing, and many more. The robot is nothing but consists of some mechanical movement driven by functions and algorithms. To get the perfect result, the algorithm working behind the scene also needs to be perfect. In all the above fields, need to reach the end effector at the exact position. That is why we need serious research on it. Otherwise, it will remain a plaything, cannot be engaged in an important role. Before implementing it into an actual application, we need to test in a simulated environment, especially when writing new methods. The simulation environment is the safest place where anything that goes wrong cannot damage a physical entity. So, the robot researcher prefers the simulator. The RoboDK is one of the famous robot simulators. Its interface is excellent and easy to test any commercial robot inside the IDE. In our research will see how to keep marking the end-effector position using the graphical method. When our end-effector moves, it holds a footprint to inspect later. This one is a minimalistic approach. Through the simplified drawing method, we can observe arm movement. This demonstration will use an optimized version of C# API, which RoboDK provides. Design/Methodology/Approach: In RoboDK IDE, we can create a new station or import existing built-in available stations. Our application drives the simulator robot. It is developed in C# language using Microsoft visual studio 2019 community edition. Both applications communicate through socket communication. Pressing the mouse's left click, when we move the mouse, it calculates the mouse pointer position and maps the value based on the robot drawing area. Then the values are sent to the simulated robot. Fetching the value, RoboDK moves into the desired position. Findings/result: Using our research works, the researcher can get some references to enhance their research work. We keep our code as simple as possible to be understood quickly and easily integrate into their research work. Originality/Value: We search the research work on RoboDK and C# language. Most of the documents are available in the python language, even in little bit documents present in the RoboDK example collection. So, we decided to migrate from python to our native language, C#. That is why this research work. After lots of hard work, we achieved it. If anyone wants to research RoboDK using C# API, it can reference their research work. Paper Type: Simulation-based Research.
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Chakraborty, Sudip, and P. S. Aithal. "Open Loop Automated Baby Cradle Using Dobot Magician and C#." International Journal of Applied Engineering and Management Letters, June 30, 2022, 344–49. http://dx.doi.org/10.47992/ijaeml.2581.7000.0141.
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Purpose: We are all busy, especially those responsible for family expenditure. We have lots of pressure in our workspace. Some employees are still doing work from home. Family being converted into an office as well. The problem arises when our small kids cry during a scheduled meeting. Sometimes need someone who can swing the baby’s cradle. Here we demonstrated an automated baby cradle which is useful when our baby cries. We can put our kids into the robotic cradle and engage in other work. When the baby cries, we trigger the run button from our working PC/Laptop, and the cradle starts to swing automatically. Here we used Dobot Magician for this purpose, a famous robot in the education and research sector due to its cost-effectiveness. To drive the robot, we developed an application in C#. It is a small program that is used to swing the cradle. Here we move the robot by the program. So we can change the program quickly, so our sweetheart feels more comfortable inside the cradle. The entire project source code is available on Github. Anyone downloading the project can integrate, test, and continue further improvement. Design/Methodology/Approach: In our research, we used the Dobot magician robot to swing the cradle. One support-like stick is connected between the robot and the cradle to push the cradle. The robot is driven by the program written inside the programming area. The original API is a little bit programming specific. So we provided intermediate programming space to write code as our understandable language. The complete application is developed using the C# language under Microsoft visual studio 2022. We used the vendor-provided dynamic link library to send the command to the robot to reduce development time. Findings/Result: We can integrate the Dobot magician robot into our custom project after developing the complete system. The movement pattern can be changed by changing the program, which may be used for different task execution utilizing the robot. The IDE can also be used for other robots, like UARM metal, a 3D printer, etc. Under the code, any robot can be operated using this interface. It has a programming interface, as well as a command-line interface. We can test, debug and experiment as well. Originality/Value: We created our application in C#, a modern, easy and flexible language. The IDE has lots of scope for experiments. The program has very easy to understand. We use the robot to swing the cradle for flexibility in nature. We can change the swings pattern by changing the parameter value, which is impossible in fixed monotonous movement. This can give us a unique feature than most other available procedures to swing the cradle. Paper Type: Experimental-based Research.