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Journal articles on the topic 'Robotic Lab'
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Jiménez, Robinson, Oscar Avies Sanchez, and Mauricio Mauledeox. "Remote Lab for Robotics Applications." International Journal of Online Engineering (iJOE) 14, no. 01 (2018): 186. http://dx.doi.org/10.3991/ijoe.v14i01.7674.
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<span lang="EN-US">This article describes the development of a remote lab environment used to test and training sessions for robotics tasks. This environment is made up of the components and devices based on two robotic arms, a network link, Arduino card and Arduino shield for Ethernet, as well as an IP camera. The remote laboratory is implemented to perform remote control of the robotic arms with visual feedback by camera, of the robots actions, where, with a group of test users, it was possible to obtain performance ranges in tasks of telecontrol of up to 92%.</span>
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Wilkins, Alex. "Robotic lab techs." New Scientist 261, no. 3472 (2024): 22. http://dx.doi.org/10.1016/s0262-4079(24)00031-9.
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Vagaš, Marek, Marek Sukop, and Jozef Varga. "Design and Implementation of Remote Lab with Industrial Robot Accessible through the Web." Applied Mechanics and Materials 859 (December 2016): 67–73. http://dx.doi.org/10.4028/www.scientific.net/amm.859.67.
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This paper describes design and implementation of remote lab with industrial robot accessible through the web based on Moodle portal, Easy Java Simulations (EJS) and Arduino Sw & Hw. The main purpose of this lab is to improve study, training and programming knowledge in industrial and service robotics for students, teachers of secondary vocational schools and company workers that deal with problems that arise on real robotic workplaces. This lab allows the user to work from their homes and operates with industrial robot at real workplace. Such remote lab can also enable users to use expensive lab equipment, which is not usually available to all persons. Practical example of application of the lab with industrial robot on Department of Robotics, Technical University of Kosice, Slovakia is presented.
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R. C. Harrell, P. D. Adsit, T. A. Pool, and R. Hoffman. "THE FLORIDA ROBOTIC GROVE-LAB." Transactions of the ASAE 33, no. 2 (1990): 0391–99. http://dx.doi.org/10.13031/2013.31342.
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Krčadinac, Olja, Željko Stanković, Sanja Mrazovac, and Lazar Stošić. "Mobile robotic laboratory - UNT Lab." Journal of UUNT: Informatics and Computer Sciences 1, no. 1 (2024): 1–10. https://doi.org/10.62907/juuntics240101001k.
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The project envisages the creation of an experimental concept of a self-propelled laboratory - UNTLab. In crisis situations, it is necessary to examine the quality (contamination) and composition of the air (soil) in a room or on an open field. The UNTLab self-propelled platform, which was implemented at UNION Nikola Tesla University, Faculty of Information Technologies, will be used without risking human resources. In the current (first) phase of realization, UNTLab is equipped with ten sensors that provide information on temperature, pressure and air humidity, substrate temperature, gas concentration (carbon oxides, propane C3H8, butane C4H10, ammonia...), intensity of EM and UV radiation as and light intensity. In addition to the sensor group, a high-resolution Wi-Fi camera is also installed. All collected data from the sensor group is recorded on a micro SD card. The platform has an additional possibility related to mobility, it is equipped with mecanum wheels, which enables great maneuverability, which also includes holonomic movement. Control of the UNTLab platform is performed via mobile devices, Android application, bluetooth communication or wi-fi network.
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Png, Sarah Shi Hui, Hui Ping Chan, and Joseph S. Ng. "Has robotic surgery finally found robotic surgeons? The confluence of technology and the perfect user." Gynecologic Robotic Surgery 5, no. 2 (2024): 29–34. http://dx.doi.org/10.36637/grs.2024.00059.
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Objective: Our study aims to identify traits of a surgeon that might determine facility with robotic surgery.Methods: Several robotics lab sessions were organised for 129 medical students, where they were introduced to robotics surgery. Their demographic and self-reported data regarding their experience was collected.Results: Our data suggests that traits commonly believed to facilitate robotic surgery skill acquisition, such as technological proficiency and playing musical instruments do not confer an advantage in robotic surgery.Conclusion: One compelling explanation is the ubiquitous familiarity with technology that characterises this generation of surgeons. This ability to easily interface with digital technology to perform tasks is a more significant contributor to facility in robotic surgery than any trait of dexterity. These findings are interesting and inform the need for further investigation into the relationship between technology, the acquisition of dexterity, and ultimately the evolution of how surgeons are trained.
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Kriegel, Johannes. "Prozessinovation: Krankenhaus als Robotic Living Lab." Klinik Einkauf 04, no. 02 (2022): 18–21. http://dx.doi.org/10.1055/s-0042-1748300.
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Die Patientenversorgung im Krankenhaus steht hinsichtlich Patientenverhalten, Mitarbeitermotivation und Ressourcenverfügbarkeit verstärkt unter Druck. Bisherige Lösungsansätze erreichen Effizienz- und Effektivitätsgrenzen. Eine zukünftige Erschließung zusätzlicher Leistungspotenziale verspricht die innovative Kollaboration von Entwicklern und Anwendern über Innovationen durch Hospital Robotic Living Labs.
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Piozzi, Guglielmo Niccolò, Sentilnathan Subramaniam, Diana Ronconi Di Giuseppe, Rauand Duhoky, and Jim S. Khan. "Robotic colorectal surgery training: Portsmouth perspective." Annals of Coloproctology 40, no. 4 (2024): 350–62. http://dx.doi.org/10.3393/ac.2024.00444.0063.
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This study aims to discuss the principles and pillars of robotic colorectal surgery training and share the training pathway at Portsmouth Hospitals University NHS Trust. A narrative review is presented to discuss all the relevant and critical steps in robotic surgical training. Robotic training requires a stepwise approach, including theoretical knowledge, case observation, simulation, dry lab, wet lab, tutored programs, proctoring (in person or telementoring), procedure-specific training, and follow-up. Portsmouth Colorectal has an established robotic training model with a safe stepwise approach that has been demonstrated through perioperative and oncological results. Robotic surgery training should enable a trainee to use the robotic platform safely and effectively, minimize errors, and enhance performance with improved outcomes. Portsmouth Colorectal has provided such a stepwise training program since 2015 and continues to promote and augment safe robotic training in its field. Safe and efficient training programs are essential to upholding the optimal standard of care.
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Jiehan, Teoh, Tee Chee Yee, Hamna Zadhy, Aminatta Mohamed Diallo, Merwin Vickraman, and Nishata Royan Rajendran Royan. "Integrating IR4.0 Technology in Engineering Education: Robotic Arm Remote Lab." Journal of Engineering Education Transformations 36, no. 1 (2022): 83–94. http://dx.doi.org/10.16920/jeet/2022/v36i1/22140.
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The education sector, in general, is constantly trying to integrate the current fourth industrial revolution known as Industry Revolution 4.0 (IR4.0) into its curriculum. In efforts to do that, this capstone project was assigned to a group of students doing their Bachelor's in Engineering to effectively create and design a virtual or remote lab that would further help students everywhere to be more engaged and involved in the learning process. In this regard, this paper introduces the initiative being carried out by the UOW Malaysia KDU University College (UOWMKDU) to implement IR 4.0 in various modules being taught, in terms of projects or assignments. Therefore, a remote lab was created based on the learning outcomes of a subject available in the module. The lab includes a robotic arm manipulated through an established interface developer Blynk, being simultaneously observed through a website built by a student in the School of Engineering, UOWMKDU. The movement of therobotic arm is viewed through the website by incorporating an inexpensive camera chip into the design. Also, this paper discusses the advantages of using those components, in-depth information regarding the components and their usage, and a detailed methodology that could be used as a guideline for future students interested in creating their robotic arm. It highlights the objectives of the lab, procedures, and challenges that were faced during the period of assembling the prototype and how those challenges were overcome to produce a wellfunctioning robotic arm. Keywords : education sector; IR4.0; remote lab; robotic arm; virtual lab
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Klimina, N. V. "Virtual robotics based on VEXcode VR and Open Roberta Lab robot simulators." Informatics in school, no. 3 (August 23, 2022): 13–26. http://dx.doi.org/10.32517/2221-1993-2022-21-3-13-26.
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The article substantiates the choice of VEXcode VR and Open Roberta Lab robot simulators for teaching robotics at school. A description of some problems solved by virtual robots in these environments is given, and possible algorithms for solving problems are presented. Methods of teaching presented in the form of mini tasks will be useful for teachers teaching robotics at school to conduct classes using several virtual robots in VEXcode VR and Open Roberta Lab robot simulators from 2nd to 7th grade. Acquaintance with the elementary concepts of the theory of automatic control on the basis of the methodology presented in the article will contribute to the formation of students' skills in the practical application of programming, the ability to apply information technologies to solve problems of control of robotic systems.
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Manawadu, Udaka A., Hiroaki Ogawa, Keito Shishiki, et al. "Towards Developing a Teleoperation System for a Disaster Response Robot." SHS Web of Conferences 102 (2021): 04005. http://dx.doi.org/10.1051/shsconf/202110204005.
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Standard Disaster Robotics Challenge of World Robot Summit (WRS) aims to test the ability of robots that can be used as disaster response robots. Robot Engineering Lab of the University of Aizu is developing a robotic system to address challenges in the WRS. The competition has five stages, and the teleoperation robotic system had to be developed to satisfy the requirements of each challenge. REL uses a disaster-response robot called Giraffe, which has the capability of traveling in hard terrain. Open Robot Technology Middleware uses to integrate all of the subsystems inside the robot. Each subsystem has different tasks that process video data, RGB depth data, Point Cloud Data, sensor data and, feedback data. The Robotic system includes 6 cameras and NDI Software Developer Kit used to transmit and view video streams remotely. The video stream from each camera can be viewed separately, and it gives wider control over the robot for the operator. The teleoperation robotic system was tested during a robot demonstration held in Fukushima Robot Test Field, and results were analyzed according to the WRS 2018 competition guidelines. The results were at an acceptable level.
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Kilic, Gokhan Sami, Teresa M. Walsh, Mostafa Borahay, Burak Zeybek, Michael Wen, and Daniel Breitkopf. "Effect of Residents’ Previous Laparoscopic Surgery Experience on Initial Robotic Suturing Experience." ISRN Obstetrics and Gynecology 2012 (September 2, 2012): 1–4. http://dx.doi.org/10.5402/2012/569456.
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Objective. To assess the impact of gynecology residents’ previous laparoscopic experience on the learning curve of robotic suturing techniques and the value of initial structured teaching in dry lab prior to surgery. Methods. Thirteen gynecology residents with no previous robotic surgery experience were divided into Group 1, consisting of residents with 2 or fewer laparoscopic experiences, and Group 2, consisting of residents with 3 or more laparoscopic experiences. Group 1 had a dry-laboratory training in suturing prior to their initial experience in the operating room. Results. For all residents, it took on average 382±159 seconds for laparoscopic suturing and 326±196 seconds for robotic suturing (P=0.12). Residents in Group 1 had a lower mean suture time than residents in Group 2 for laparoscopic suturing (P=0.009). The residents in Group 2, however, had a lower mean suture time on the robot compared to Group 1 (P=0.5). Conclusion. Residents with previous laparoscopic suturing experience may gain more from a robotic surgery experience than those with limited laparoscopic surgery experience. In addition, dry lab training is more efficient than hands-on training in the initial phase of teaching for both laparoscopic and robotic suturing skills.
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R., Saranraj, P. Richard S., and Vigneshwaran P. "Cyborg using Labview for Temperature Sensor Handling." International Journal of Engineering and Advanced Technology (IJEAT) 9, no. 5 (2020): 92–95. https://doi.org/10.35940/ijeat.D8201.069520.
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This paper discusses about the development of the robotic manipulator which is fully controlled using the Lab VIEW software and potentiometer. The Arduino Uno R3 microcontroller is used to execute the program and LIFA (LabVIEW Interface Arduino) software is used to control the robotic manipulator. This robotic manipulator is specially design for temperature sensor MI cable pick and place purpose. The manipulator can also be used for many applications in the automation field. The hardware of the robotic controller and the other design details are clearly presented in this paper.
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Marín Garcés, Josep, Carlos Veiga Almagro, Giacomo Lunghi, et al. "MiniCERNBot Educational Platform: Antimatter Factory Mock-up Missions for Problem-Solving STEM Learning." Sensors 21, no. 4 (2021): 1398. http://dx.doi.org/10.3390/s21041398.
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Mechatronics and robotics appeared particularly effective in students’ education, allowing them to create non-traditional solutions in STEM disciplines, which have a direct impact and interaction with the world surrounding them. This paper presents the current state of the MiniCERNBot Educational Robotic platform for high-school and university students. The robot provides a comprehensive educative system with tutorials and tasks tuned for different ages on 3D design, mechanical assembly, control, programming, planning, and operation. The system is inspired to existing robotic systems and typical robotic interventions performed at CERN, and includes an education mock-up that follows the example of a previous real operation performed in CERN’s Antimatter Factory. The paper describes the learning paths where the MiniCERNBot platform can be used by students, at different ages and disciplines. In addition, it describes the software and hardware architecture, presenting results on modularity and network performance during education exercises. In summary, the objective of the study is improving the way STEM educational and dissemination activities at CERN Robotics Lab are performed, as well as their possible synergies with other education institutions, such as High-Schools and Universities, improving the learning collaborative process and inspiring students interested in technical studies. To this end, a new educational robotic platform has been designed, inspired on real scientific operations, which allows the students practice multidisciplinary STEM skills in a collaborative problem-solving way, while increasing their motivation and comprehension of the research activities.
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Vijayan, Asha, Chaitanya Nutakki, Dhanush Kumar, Krishnashree Achuthan, Bipin Nair, and Shyam Diwakar. "Enabling a Freely Accessible Open Source Remotely Controlled Robotic Articulator with a Neuro-Inspired Control Algorithm." International Journal of Online Engineering (iJOE) 13, no. 01 (2017): 61. http://dx.doi.org/10.3991/ijoe.v13i01.6288.
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Internet-enabled technologies for robotics education are gaining importance as online platforms promoting skill training. Understanding the use and design of robotics are now introduced at university undergraduate levels, but in developing economies establishing usable hardware and software platforms face several challenges like cost, equipment etc. Remote labs help providing alternatives to some of the challenges. We developed an online laboratory for bioinspired robotics using a low-cost 6 degree-of-freedom robotic articulator with a neuro-inspired controller. Cerebellum-inspired neural network algorithm approximates forward and inverse kinematics for movement coordination. With over 210000 registered users, the remote lab has been perceived as an interactive online learning tool and a practice platform. Direct feedback from 60 students and 100 university teachers indicated that the remote laboratory motivated self-organized learning and was useful as teaching material to aid robotics skill education.
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Kinahan, David J., Philip L. Early, Abhishek Vembadi, et al. "Xurography actuated valving for centrifugal flow control." Lab on a Chip 16, no. 18 (2016): 3454–59. http://dx.doi.org/10.1039/c6lc00568c.
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Martinez-Hernandez, Uriel, Benjamin Metcalfe, Tareq Assaf, Leen Jabban, James Male, and Dingguo Zhang. "Wearable Assistive Robotics: A Perspective on Current Challenges and Future Trends." Sensors 21, no. 20 (2021): 6751. http://dx.doi.org/10.3390/s21206751.
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Wearable assistive robotics is an emerging technology with the potential to assist humans with sensorimotor impairments to perform daily activities. This assistance enables individuals to be physically and socially active, perform activities independently, and recover quality of life. These benefits to society have motivated the study of several robotic approaches, developing systems ranging from rigid to soft robots with single and multimodal sensing, heuristics and machine learning methods, and from manual to autonomous control for assistance of the upper and lower limbs. This type of wearable robotic technology, being in direct contact and interaction with the body, needs to comply with a variety of requirements to make the system and assistance efficient, safe and usable on a daily basis by the individual. This paper presents a brief review of the progress achieved in recent years, the current challenges and trends for the design and deployment of wearable assistive robotics including the clinical and user need, material and sensing technology, machine learning methods for perception and control, adaptability and acceptability, datasets and standards, and translation from lab to the real world.
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Maddipatla, Yashwanth, Sibo Tian, Xiao Liang, Minghui Zheng, and Beiwen Li. "VR Co-Lab: A Virtual Reality Platform for Human–Robot Disassembly Training and Synthetic Data Generation." Machines 13, no. 3 (2025): 239. https://doi.org/10.3390/machines13030239.
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This research introduces a virtual reality (VR) training system for improving human–robot collaboration (HRC) in industrial disassembly tasks, particularly for e-waste recycling. Conventional training approaches frequently fail to provide sufficient adaptability, immediate feedback, or scalable solutions for complex industrial workflows. The implementation leverages Quest Pro’s body-tracking capabilities to enable ergonomic, immersive interactions with planned eye-tracking integration for improved interactivity and accuracy. The Niryo One robot aids users in hands-on disassembly while generating synthetic data to refine robot motion planning models. A Robot Operating System (ROS) bridge enables the seamless simulation and control of various robotic platforms using Unified Robotics Description Format (URDF) files, bridging virtual and physical training environments. A Long Short-Term Memory (LSTM) model predicts user interactions and robotic motions, optimizing trajectory planning and minimizing errors. Monte Carlo dropout-based uncertainty estimation enhances prediction reliability, ensuring adaptability to dynamic user behavior. Initial technical validation demonstrates the platform’s potential, with preliminary testing showing promising results in task execution efficiency and human–robot motion alignment, though comprehensive user studies remain for future work. Limitations include the lack of multi-user scenarios, potential tracking inaccuracies, and the need for further real-world validation. This system establishes a sandbox training framework for HRC in disassembly, leveraging VR and AI-driven feedback to improve skill acquisition, task efficiency, and training scalability across industrial applications.
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Abreu, Paulo, Manuel Romano Barbosa, and António Mendes Lopes. "Experiments with a Virtual Lab for Industrial Robots Programming." International Journal of Online Engineering (iJOE) 11, no. 5 (2015): 10. http://dx.doi.org/10.3991/ijoe.v11i5.4752.
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This paper presents the use of a virtual lab for teaching industrial robots programming to university students. The virtual lab, that replicates the existing physical lab, is built using an industrial simulation software package, RobotStudio™. The capabilities of this tool are explored in order to complement the introduction of theoretical concepts with practical programming experience. In addition to illustrate the use of different coordinate systems in a robotic cell, a description of the tool center point calibration and examples of evaluating different moving strategies to cover a plane surface, are also presented.
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Wilkins, Alex. "Is Amazon's robotic lab a vision of the automated future?" New Scientist 262, no. 3488 (2024): 15. http://dx.doi.org/10.1016/s0262-4079(24)00769-3.
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Behery, Mohamed, Philipp Brauner, Aline Kluge-Wilkes, et al. "Digital Shadows for Robotic Assembly in the World Wide Lab." Procedia CIRP 120 (2023): 165–70. http://dx.doi.org/10.1016/j.procir.2023.08.030.
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Alejandro, Diaz Giron Gidi, Faes-Petersen Regina, Nuccio Giordano Fabiola, and Villegas Tovar Eduardo. "The road to becoming a certified robotic surgeon." World Journal of Advanced Research and Reviews 7, no. 1 (2020): 187–96. https://doi.org/10.5281/zenodo.4316865.
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Surgical educators are challenged with introducing new technologies into general surgery training. There has been a rapid and widespread adoption of the robotic surgical system with a lag in the development of a comprehensive training and credentialing framework. A literature search on robotic surgical training techniques and benchmarks were conducted to provide an evidence-based road map for the development of a robotic surgical skills for the novice robotic surgeon. A structured training curriculum is suggested incorporating evidence-based training techniques and benchmarks for progress. This usually involves sequential progression from observation, case assisting, acquisition of basic robotic skills in the dry and wet lab setting along with achievement of individual and team-based non-technical skills, modular console training under supervision, and finally independent practice. There is a need for a standardized curriculum for training and assessment of robotic surgeons to proficiency, followed by high stakes testing for certification. A standardized process for certifying the skills of a robotic surgeon has begun to emerge.
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Groth, Paul, and Jessica Cox. "Indicators for the use of robotic labs in basic biomedical research: a literature analysis." PeerJ 5 (November 8, 2017): e3997. http://dx.doi.org/10.7717/peerj.3997.
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Robotic labs, in which experiments are carried out entirely by robots, have the potential to provide a reproducible and transparent foundation for performing basic biomedical laboratory experiments. In this article, we investigate whether these labs could be applicable in current experimental practice. We do this by text mining 1,628 papers for occurrences of methods that are supported by commercial robotic labs. Using two different concept recognition tools, we find that 86%–89% of the papers have at least one of these methods. This and our other results provide indications that robotic labs can serve as the foundation for performing many lab-based experiments.
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Butterworth, Jessica, Margaux Sadry, Danielle Julian, and Fiona Haig. "Assessment of the training program for Versius, a new innovative robotic system for use in minimal access surgery." BMJ Surgery, Interventions, & Health Technologies 3, no. 1 (2021): e000057. http://dx.doi.org/10.1136/bmjsit-2020-000057.
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ObjectivesThe Versius surgical system has been developed for use in robot-assisted minimal access surgery (MAS). This study aimed to evaluate the effectiveness of the Versius training program.DesignA 3.5-day program following 10 hours of online didactic training. Participants were assessed during the technical training using the Global Evaluative Assessment of Robotic Skills (GEARS).SettingDry box exercises were conducted in classrooms, and wet lab sessions simulated an operating room environment using cadaveric specimens.ParticipantsSeventeen surgical teams participated; surgeons represented general, colorectal, obstetrics/gynecology, and urology specialties. All surgeons had previous laparoscopic MAS experience, while experience with robotics varied.Main outcomes measuresParticipants were scored on a five-point Likert Scale for each of six validated GEARS domains (depth perception, bimanual dexterity, efficiency, force sensitivity, autonomy, and robotic control). Additional metrics used to chart surgeon performance included: combined instrument path length; combined instrument angular path; and time taken to complete each task.ResultsParticipants demonstrated an overall improvement in performance during the study, with a mean GEARS Score of 21.0 (SD: 1.9) in Assessment 1 increasing to 23.4 (SD: 2.9) in Validation. Greatest improvements were observed in the depth perception and robotic control domains. Greatest differences were observed when stratifying by robotic experience; those with extensive experience consistently scored higher than those with some or no experience.ConclusionsThe Versius training program is effective; participants were able to successfully operate the system by program completion, and more surgeons achieved intermediate-level and expert-level GEARS scores in Validation compared with Assessment 1.
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Fell, Cody, Trent L. Brooks-Richards, Maria A. Woodruff, and Mark C. Allenby. "Soft pneumatic actuators for mimicking multi-axial femoropopliteal artery mechanobiology." Biofabrication 14, no. 3 (2022): 035005. http://dx.doi.org/10.1088/1758-5090/ac63ef.
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Abstract Tissue biomanufacturing aims to produce lab-grown stem cell grafts and biomimetic drug testing platforms but remains limited in its ability to recapitulate native tissue mechanics. The emerging field of soft robotics aims to emulate dynamic physiological locomotion, representing an ideal approach to recapitulate physiologically complex mechanical stimuli and enhance patient-specific tissue maturation. The kneecap’s femoropopliteal artery (FPA) represents a highly flexible tissue across multiple axes during blood flow, walking, standing, and crouching positions, and these complex biomechanics are implicated in the FPA’s frequent presentation of peripheral artery disease. We developed a soft pneumatically actuated (SPA) cell culture platform to investigate how patient-specific FPA mechanics affect lab-grown arterial tissues. Silicone hyperelastomers were screened for flexibility and biocompatibility, then additively manufactured into SPAs using a simulation-based design workflow to mimic normal and diseased FPA extensions in radial, angular, and longitudinal dimensions. SPA culture platforms were seeded with mesenchymal stem cells, connected to a pneumatic controller, and provided with 24 h multi-axial exercise schedules to demonstrate the effect of dynamic conditioning on cell alignment, collagen production, and muscle differentiation without additional growth factors. Soft robotic bioreactors are promising platforms for recapitulating patient-, disease-, and lifestyle-specific mechanobiology for understanding disease, treatment simulations, and lab-grown tissue grafts.
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Ghayoor, F. "A MATLAB-based virtual robotics laboratory: Demonstrated by a two-wheeled inverted pendulum." International Journal of Electrical Engineering & Education 57, no. 4 (2018): 301–20. http://dx.doi.org/10.1177/0020720918816006.
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In this paper, a procedure for designing a MATLAB-based virtual robotics laboratory is described that provides a realistic three-dimensional animation for the robot’s motion. The proposed laboratory allows students to obtain the linear model and stability condition of a robotic system, without getting involved in its mathematical modeling. The structure of a two-wheeled inverted pendulum robot has been used for demonstrating the laboratory’s features. As part of this virtual experiment, design and evaluation of proportional–integral–derivative, model predictive control, and fuzzy controllers for maintaining the two-wheeled inverted pendulum’s balance are considered. A set of graphical–user interfaces is designed for providing the interaction with the system. This virtual lab is readily extensible for other robotics structures and controllers, and its output data is promptly available for further analysis by other MATLAB toolboxes.
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Siddiqui, Nazema Y., Megan E. Tarr, Elizabeth J. Geller, et al. "Establishing Benchmarks For Minimum Competence With Dry Lab Robotic Surgery Drills." Journal of Minimally Invasive Gynecology 23, no. 4 (2016): 633–38. http://dx.doi.org/10.1016/j.jmig.2016.03.014.
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Newcomb, L. K., M. S. Bradley, T. Truong, et al. "Correlation of Virtual Reality Simulation and Dry Lab Robotic Technical Skills." Journal of Minimally Invasive Gynecology 24, no. 7 (2017): S74. http://dx.doi.org/10.1016/j.jmig.2017.08.199.
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Newcomb, Laura K., Megan S. Bradley, Tracy Truong, et al. "Correlation of Virtual Reality Simulation and Dry Lab Robotic Technical Skills." Journal of Minimally Invasive Gynecology 25, no. 4 (2018): 689–96. http://dx.doi.org/10.1016/j.jmig.2017.11.006.
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Mullens, Cody Lendon, Alexandra L. Van Horn, James Wallis Marsh, et al. "Development of a Senior Medical Student Robotic Surgery Training Elective." Journal of Medical Education and Curricular Development 8 (January 2021): 238212052110240. http://dx.doi.org/10.1177/23821205211024074.
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As robotic surgery has become more widespread, early exposure to the robotic platform is becoming increasingly important, not only to graduate medical education, but also for medical students pursuing surgical residency. In an effort to orient students to robotic technology and decrease the learning curve for what is likely to become an integral part of residency training, we created a formal, elective robotic surgery curriculum for senior medical students. Throughout this 2-week fourth year rotation, students completed online training modules and assessment; mastered exercises on the simulator system related to the console, camera, energy, dexterity, and suturing skills; attended didactics; utilized the dual console during one-on-one simulation lab sessions with attending robotic surgery experts; and translated new skills to biotissue anastomoses as well as bedside-assisting in the operating room. During cases, students were able to have more meaningful observation experiences, recognizing the significance of various robotic approaches employed and utilization of specific instruments. Future aims of this rotation will assess student experience as it impacts readiness for surgical residency.
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Thapa, Shekhar, Glen C. Rains, Wesley M. Porter, et al. "Robotic Multi-Boll Cotton Harvester System Integration and Performance Evaluation." AgriEngineering 6, no. 1 (2024): 803–22. http://dx.doi.org/10.3390/agriengineering6010046.
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Several studies on robotic cotton harvesters have designed their end-effectors and harvesting algorithms based on the approach of harvesting a single cotton boll at a time. These robotic cotton harvesting systems often have slow harvesting times per boll due to limited computational speed and the extended time taken by actuators to approach and retract for picking individual cotton bolls. This study modified the design of the previous version of the end-effector with the aim of improving the picking ratio and picking time per boll. This study designed and fabricated a pullback reel to pull the cotton plants backward while the rover harvested and moved down the row. Additionally, a YOLOv4 cotton detection model and hierarchical agglomerative clustering algorithm were implemented to detect cotton bolls and cluster them. A harvesting algorithm was then developed to harvest the cotton bolls in clusters. The modified end-effector, pullback reel, vacuum conveying system, cotton detection model, clustering algorithm, and straight-line path planning algorithm were integrated into a small red rover, and both lab and field tests were conducted. In lab tests, the robot achieved a picking ratio of 57.1% with an average picking time of 2.5 s per boll. In field tests, picking ratio was 56.0%, and it took an average of 3.0 s per boll. Although there was no improvement in the lab setting over the previous design, the robot’s field performance was significantly better, with a 16% higher picking ratio and a 46% reduction in picking time per boll compared to the previous end-effector version tested in 2022.
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Bridges, Craig A., Bishnu Prasad Thapaliya, Xiaoguang Sun, et al. "(Invited) Electrochemistry in a Lab of the Future." ECS Meeting Abstracts MA2023-02, no. 1 (2023): 74. http://dx.doi.org/10.1149/ma2023-02174mtgabs.
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Advanced research laboratories are producing ever more data and introducing more advanced methods of data analysis and feedback to control these laboratories. These "labs of the future" are intended to revolutionize the way that research is done, enabling in some cases the exploration of higher dimensional problems and better research outcomes. At ORNL, the Autonomous Chemistry Laboratory (ACL) is being developed as a self-driving laboratory to accelerate materials discovery and innovation. A combination of robotic tools are being integrated with computational tools to analyze reaction results and predict optimal directions for future investigation. We have developed an electrochemical workstation integrated with materials synthesis and discovery. The capabilities and concept for the ACL will be presented.
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Ahmad, Lina, Wassim Jabi, and Marco Sosa. "Nonplanar Robotic Printing of Earth-Based Material: A Case Study Using Cob-like Mixture." Buildings 14, no. 8 (2024): 2589. http://dx.doi.org/10.3390/buildings14082589.
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The study presents an integration of cob with robotic processes. By challenging conventional monolithic earth-building methods, the study proposes the use of spatial nonplanar formations that are robotically fabricated, presenting an alternative geometric language for earth construction. The research methodology is derived from existing factors within the robotic lab, encompassing both constant and variable parameters. Through an experimental approach, the variables are systematically manipulated while observing the outcomes to identify patterns and relationships. Incremental refinements to the research conditions result in an optimal equilibrium state within the defined lab parameters. An empirical investigation approach serves as the foundation for controlling the printing process; wherein an iterative adjustment of the robot extrusion parameters is based on the behaviour of the deposited material. The outcome is several robotically printed cob nonplanar prototypes. Depending on their geometric formations and complexity, the printing process combined three variations: continuous, intervals, and modular. The latter enabled the production of a cob arch, serving as proof of feasibility for the creation of modular cob structures through a segmented assembly process. The study contributes to expanding the possibilities of cob construction by leveraging robotic technologies and paving the way for innovative applications of cob in contemporary architecture practices.
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Suthar, Bhivraj, Tanmay Shrivastava, and Lamyanba Heisnam. "Validation of End Effector Matrix for Robotic Kit OWI-535 using Matlab and Robo Analyzer." IAES International Journal of Robotics and Automation (IJRA) 5, no. 1 (2016): 54. http://dx.doi.org/10.11591/ijra.v5i1.pp54-60.
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This paper presents the validation of the end effector matrix having D-H parameter of the 4 DOF educational manipulator OWI-535 by MAT-LAB and Robo Analyzer. Transformation matrix of order 4x4 which describes end effecter’s position and orientation with respect to the base reference frame. MAT-LAB programming which gives details about the translation steps of the manipulator simultaneously. Forward kinematics of OWI 535 robotic kit has been calculated by Mat-lab as well as Robo Analyzer. We had calculated the End effector matrix in both software and compare it. We found that the results are similar up to three digit in some elements and up to two digits from decimal in few elements and it was different after three digit from the decimal in end effector matrix.
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Pransky, Joanne. "The Pransky interview: Dr Aaron Edsinger, CEO and cofounder at Hello Robot Inc." Industrial Robot: An International Journal 45, no. 6 (2018): 710–14. http://dx.doi.org/10.1108/ir-09-2018-0186.
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Purpose The purpose of this paper is to present a “Q&A interview” conducted by Joanne Pransky of Industrial Robot Journal as a method to impart the combined technological, business and personal experience of a prominent, robotic industry PhD-turned entrepreneur regarding the evolution, commercialization and challenges of bringing a technological invention to market. Design/methodology/approach The interviewee is Dr Aaron Edsinger, a proven entrepreneur and inventor in the field of human-collaborative robotics. Dr Edsinger shares his journey that led him from developing humanoids at Rodney Brooks’ Computer Science and Artificial Intelligence Laboratory at MIT, to cofounding four companies, two of which got purchased by Google. Findings Dr Edsinger received a BS degree in Computer Systems Engineering from Stanford, an MS in Computer Science from the Massachusetts Institute of Technology (MIT) and a PhD in Computer Science from MIT and did post-doctorate research in the Humanoid Robotics Group at the MIT Computer Science and Artificial Intelligence Lab. He co-founded his first company Meka Robotics in 2007 and that same year, he started his second company, HStar Technologies. In 2011, he cofounded Redwood Robotics, and in 2013, he sold Meka and Redwood to Google. From 2013 to 2017, he was a Robotics Director at Google. In August of 2017, he cofounded Hello Robot Inc. Originality/value Dr Edsinger’s work in robotics grew out of the San Francisco robotic art scene in the 1990s. Since then, he has collaborated and built over a dozen research and artistic robot platforms and has been granted 28 patents. His world-class robotic systems encompass Dr Edsinger’s innovative research in dexterous manipulation in unstructured environments, force controlled compliant actuation, human safe robotics, integrated mechatronic engineering and the design of humanoid robots. Domo, the humanoid robot he built, was named one of Time magazine’s Best Inventions of the Year for 2007. Out of the eight robot companies Google purchased in 2013, two were cofounded by Dr Edsinger. In 2017, Dr Edsinger left Google to cofound his new company, Hello Robot Inc, a stealth mode consumer robot company.
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Wang, Weitian, Rui Li, Longxiang Guo, Z. Max Diekel, and Yunyi Jia. "Hands-Free Maneuvers of Robotic Vehicles via Human Intentions Understanding Using Wearable Sensing." Journal of Robotics 2018 (2018): 1–10. http://dx.doi.org/10.1155/2018/4546094.
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Intelligent robotic vehicles are more and more fully automated, without steering wheels, gas/brake pedals, or gearshifts. However, allowing the human driver to step in and maneuver the robotic vehicle under specific driving requirements is a necessary issue that should be considered. To this end, we propose a wearable-sensing-based hands-free maneuver intention understanding approach to assist the human to naturally operate the robotic vehicle without physical contact. The human intentions are interpreted and modeled based on the fuzzy control using the forearm postures and muscle activities information detected by a wearable sensory system, which incorporates electromyography (EMG) sensors and inertial measurement unit (IMU). Based on the maneuver intention understanding model, the human can flexibly, intuitively, and conveniently control diverse vehicle maneuvers only using his intention expressions. This approach was implemented by a series of experiments in the practical situations on a lab-based 1/10 robotic vehicle research platform. Experimental results and evaluations demonstrated that, by taking advantage of the nonphysical contact and natural handleability of this approach, the robotic vehicle was successfully and effectively maneuvered to finish the driving tasks with considerable accuracy and robustness in human-robotic vehicle interaction.
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Mocan, Bogdan, Claudiu Schonstein, Mircea Murar, et al. "Upper-Limb Robotic Exoskeleton for Early Cardiac Rehabilitation Following an Open-Heart Surgery—Mathematical Modelling and Empirical Validation." Mathematics 11, no. 7 (2023): 1598. http://dx.doi.org/10.3390/math11071598.
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Robotic exoskeletons have the potential to enhance the quality of life of patients undergoing cardiac rehabilitation. Recent studies found that the use of such devices was associated with significant improvements in physical function, mobility, and overall well-being for individuals recovering from a cardiac event. These improvements were seen across a range of measures, including cardiovascular fitness, muscle strength, and joint range of motion. In addition, the use of robotic exoskeletons may help to accelerate the rehabilitation process, allowing patients to make faster progress towards their goals. This article proposes a new robotic exoskeleton structure with 12 DOFs (6 DOFs on each arm) in a symmetrical construction for upper limbs intended to be used in the early rehabilitation of cardiac patients following open-heart surgery or a major cardiac event. The mathematical modelling and empirical validation of the robotic exoskeleton prototype are described. The matrix exponential algorithm, kinetic energy, and generalized forces were employed to overcome the problem of high complexity regarding the kinematic and dynamic model of the robotic exoskeleton. The robotic exoskeleton prototype was empirically validated by assessing its functionalities in a lab and medical environment.
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Wei, Fangqiang, Mingen Xu, Xuecong Lai, et al. "Three‐dimensional printed dry lab training models to simulate robotic‐assisted pancreaticojejunostomy." ANZ Journal of Surgery 89, no. 12 (2019): 1631–35. http://dx.doi.org/10.1111/ans.15544.
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Miles, Ben, and Peter L. Lee. "Achieving Reproducibility and Closed-Loop Automation in Biological Experimentation with an IoT-Enabled Lab of the Future." SLAS TECHNOLOGY: Translating Life Sciences Innovation 23, no. 5 (2018): 432–39. http://dx.doi.org/10.1177/2472630318784506.
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A robotic cloud laboratory driven by a state-of-the-art unified laboratory operating system integrates automated hardware, humans, and sensors. This lab of the future system enables researchers to transparently and collaboratively create, optimize, and organize biological experiments to achieve more reproducible results, perform around-the-clock experimentation, and more efficiently navigate the vast parameter space of biology.
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Choksi, Sarah, Sanjeev Narasimhan, Mattia Ballo, et al. "Automatic assessment of robotic suturing utilizing computer vision in a dry-lab simulation." Artificial Intelligence Surgery 5, no. 2 (2025): 160–9. https://doi.org/10.20517/ais.2024.84.
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Aim: Automated surgical skill assessment is poised to become an invaluable asset in surgical residency training. In our study, we aimed to create deep learning (DL) computer vision artificial intelligence (AI) models capable of automatically assessing trainee performance and determining proficiency on robotic suturing tasks. Methods: Participants performed two robotic suturing tasks on a bench-top model created by our lab. Videos were recorded of each surgeon performing a backhand suturing task and a railroad suturing task at 30 frames per second (FPS) and downsampled to 15 FPS for the study. Each video was segmented into four sub-stitch phases: needle positioning, targeting, driving, and withdrawal. Each sub-stitch was annotated with a binary technical score (ideal or non-ideal), reflecting the operator’s skill while performing the suturing action. For DL analysis, 16-frame overlapping clips were sampled from the videos with a stride of 1. To extract the features useful for classification, two pretrained Video Swin Transformer models were fine-tuned using these clips: one to classify the sub-stitch phase and another to predict the technical score. The model outputs were then combined and used to train a Random Forest Classifier to predict the surgeon's proficiency level. Results: A total of 102 videos from 27 surgeons were evaluated using 3-fold cross-validation, 51 videos for the backhand suturing task and 51 videos for the railroad suturing task. Performance was assessed on sub-stitch classification accuracy, technical score accuracy, and surgeon proficiency prediction. The clip-based Video Swin Transformer models achieved an average classification accuracy of 70.23% for sub-stitch classification and 68.4% for technical score prediction on the test folds. Combining the model outputs, the Random Forest Classifier achieved an average accuracy of 66.7% in predicting surgeon proficiency. Conclusion: This study shows the feasibility of creating a DL-based automatic assessment tool for robotic-assisted surgery. Using machine learning models, we predicted the proficiency level of a surgeon with 66.7% accuracy. Our dry lab model proposes a standardized training and assessment tool for suturing tasks using computer vision.
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Bested, Stephen R., Gerome A. Manson, and Luc Tremblay. "Combining Unassisted and Robot-Guided Practice Benefits Motor Learning for a Golf Putting Task." Journal of Motor Learning and Development 7, no. 3 (2019): 408–25. http://dx.doi.org/10.1123/jmld.2018-0040.
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Robotic guidance has been employed with limited effectiveness in neurologically intact and patient populations. For example, our lab has effectively used robotic guidance to acutely improve movement smoothness of a discrete trajectory without influencing movement endpoint distributions. The purpose of the current study was to investigate the efficacy of combining robotic guidance and unassisted trials in the learning of a golf putting task. Participants completed a pre-test, an acquisition phase, and an immediate and delayed (24-hour) post-test. During the pre-test, kinematic data from the putter was converted into highly accurate, consistent, and smooth trajectories delivered by a robot arm. During acquisition, three groups performed putts towards three different targets with robotic guidance on either 0%, 50%, or 100% of acquisition trials. Only the 50% guidance group statistically reduced both the ball endpoint distance and variability between the pre-test and the immediate or 24-hr post-test. The results of the 50% guidance group yielded seminal evidence that combining both unassisted and robotic guidance trials (i.e., mixed practice) could facilitate at least short-term motor learning for a golf putting task. Such work is relevant to incorporating robotic guidance in sport skills and other practical areas (e.g., rehabilitation).
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Bier, Henriette, Arwin Hidding, Casper Van Engelenburg, and Tarique Ali. "Advancing Sustainable Approaches in Architecture by Means of Design-to-Robotic-Production." SPOOL 11, no. 1 (2024): 65–70. http://dx.doi.org/10.47982/spool.2024.1.04.
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The construction sector accounts for about 40% of material-, energy- and process-related carbon dioxide (CO2) emissions , which can be reduced by introducing data-driven Circular Economy (CE) approaches . For instance, Design-to-Robotic-Production (D2RP) methods developed in the Robotic building lab, at Technical University (TU) Delft are embedding data-driven systems into building processes. Their potential to contribute to sustainability through increased material-, process-, and energy-efficiency has been explored in several case studies that are presented in this paper. The assumption is that by using these methods and reclaimed wood to minimize demand for new resources and reduce deforestation along the way, CO2 emissions can be considerably reduced.
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Cetin, Kamil, Harun Tugal, Yvan Petillot, Matthew Dunnigan, Leonard Newbrook, and Mustafa Suphi Erden. "A Robotic Experimental Setup with a Stewart Platform to Emulate Underwater Vehicle-Manipulator Systems." Sensors 22, no. 15 (2022): 5827. http://dx.doi.org/10.3390/s22155827.
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This study presents an experimental robotic setup with a Stewart platform and a robot manipulator to emulate an underwater vehicle–manipulator system (UVMS). This hardware-based emulator setup consists of a KUKA IIWA14 robotic manipulator mounted on a parallel manipulator, known as Stewart Platform, and a force/torque sensor attached to the end-effector of the robotic arm interacting with a pipe. In this setup, we use realistic underwater vehicle movements either communicated to a system in real-time through 4G routers or recorded in advance in a water tank environment. In addition, we simulate both the water current impact on vehicle movement and dynamic coupling effects between the vehicle and manipulator in a Gazebo-based software simulator and transfer these to the physical robotic experimental setup. Such a complete setup is useful to study the control techniques to be applied on the underwater robotic systems in a dry lab environment and allows us to carry out fast and numerous experiments, circumventing the difficulties with performing similar experiments and data collection with actual underwater vehicles in water tanks. Exemplary controller development studies are carried out for contact management of the UVMS using the experimental setup.
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Hwang, Gilgueng, Preeda Chantanakajornfung, and Hideki Hashimoto. "Versatile Robotic Biomanipulation with Haptic Interface." Journal of Robotics and Mechatronics 19, no. 5 (2007): 585–91. http://dx.doi.org/10.20965/jrm.2007.p0585.
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This paper presents a multi-scale extension of versatile robotic biomanipulation powered by single-master multislave (SMMS) bilateral teleoperation. We tested the potential possibility of SMMS multiscale extension to variety of biomanipulation applications. Our target goal is to design a multi-scale biotweezing tool. The SMMS configuration was previously proven useful for single manipulation control. First, cell handling experiments such as pick-and-place, injection, and cell indentation with probing from meso- to nanoscale are shown using salmon roe, modeled styren block and a dried yeast cell representing biological applications. A simulation environment was constructed to emulate potential experiments on the subnanoscale. Based on our lab-on-a-tip approach, we expect our proposal to become a multifunctional platform for biomanipulation. We describe an SMMS biomanipulation experiment on the extracellular scale and simulation for potential subcellular applications. Virtual reality (VR) simulation is used in rapid prototype manipulation or assembly models prior to actual biomanipulation experiments and is used as an experimental platform.
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B Lima, Glaydson Luiz, Osamu Saotome, and Ijar M. Da Fonseca. "Inspection and control system for experiments in space robotics." South Florida Journal of Development 2, no. 3 (2021): 4094–104. http://dx.doi.org/10.46932/sfjdv2n3-023.
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The communication subsystem is one among the various subsystems of a telerobotic space system. It is responsible for coordinating the commands received from the teleoperator control subsystem to the robotic arm, for reading signals from the sensors, and for stating the communication of the telerobot with the ground station. The telerobotic experiment under development by the ITA space robotics research group was developed with the purpose of investigating a robotic space system dynamics and control, including the study of the working and integration of all subsystems involved in the teleoperation control. The lab experiment consists of two identical units of robot manipulators, each of them mounted on its own floating air-supported platform. The objective is to simulate computationally the operations of rendezvous and capture in the microgravity' orbital environment, emulated by the floating manipulators' dynamics. The closed circuit for this system involves the in time position detection, transmission and data processing by using a position-tracking (X, Y, and Z) computer system combined with a Kinect sensor (RGB-D). The computer system comprises two computers capable of processing the positional images with greater accuracy. One of them receive and send the sensor data to a second computer which performs the data processing by proper algorithms in Matlab® and Simulink and sends commands to the robotic arm via WIFI (UDP protocol) network. The robot receives and executes the control signals moving the robotic arms whose position is again detected by the kinect sensor and informed back to the computer system, closing the control mesh and allowing the safe capture of the target. This work deals with the communication subsystem of the space robot experiment and its ability to set an integrated and efficient communication satisfying the telerobot control requirements
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Pransky, Joanne. "The Pransky interview: Professor Jacob Rosen, Co-Founder of Applied Dexterity and ExoSense." Industrial Robot: An International Journal 43, no. 5 (2016): 457–62. http://dx.doi.org/10.1108/ir-06-2016-0162.
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Purpose The following article is a “Q&A interview” conducted by Joanne Pransky of Industrial Robot journal as a method to impart the combined technological, business and personal experience of a prominent, robotic industry engineer-turned-entrepreneur regarding the evolution, commercialization and challenges of bringing a technological invention to market. The paper aims to discuss these issues. Design/methodology/approach The interviewee is Jacob Rosen, a Professor of Medical Robotics at the Department of Mechanical and Aerospace Engineering, University of California, Los Angeles (UCLA), where he directs the Bionics Lab. Professor Rosen is also the Director of Surgical Robotics Engineering at the UCLA School of Medicine’s Center for Advanced Surgical and Interventional Technology and has joint appointments at UCLA’s Department of Surgery and UCLA’s Department of Bioengineering. Professor Rosen is the co-founder of the companies Applied Dexterity, ExoSense and SPI. As a pioneer in medical robotics devices and technologies, Professor Rosen describes his unique approaches and philosophies. Findings Dr Rosen received his BSc degree in Mechanical Engineering, MSc and PhD degrees in Biomedical Engineering from Tel-Aviv University in 1987, 1993 and 1997, respectively. From 1987 to 1992, he served as an officer in the Israeli Defense Forces studying human–machine interfaces. From 1993 to 1997, he was a research associate at Tel-Aviv University, as well as held a position at a startup company developing innovative orthopedic spine/pelvis implants. From 2001-2013, he held faculty positions at the University of Washington and at University of California, Santa Cruz. Originality/value Dr Rosen developed several key systems in the field of medical robotics, such as the Blue and the Red Dragon, for minimally invasive surgical skill evaluation; RAVEN, a surgical robotic system for telesurgery; and several generations of upper and lower limb exoskeletons including the Exo-UL7 – a dual arm wearable robotic system. He is a co-author of 100 manuscripts in the field of medical robotics and a co-author and co-editor of two books entitled “Surgical Robotics – Systems, Applications, and Visions” and “Redundancy in Robot Manipulators and Multi-robot systems” published by Springer. Professor Rosen has filed eight different patent applications and also works as an expert witness and consultant on design, patent protection & litigation and malpractice regarding surgical robotics.
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Tiwari, Akhilesh Kumar. "Robotics Module in Enhancing Interactive Stem Education." Journal of Ravishankar University (PART-B) 32, no. 1 (2019): 34–37. http://dx.doi.org/10.52228/jrub.2019-32-1-7.
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Teaching robotics to young students can increase their ability to be creative, innovative thinkers and more productive members of society throughout their school years. Indian government have already recognized the importance of robotics in the classroom teaching and started ATAL tinkering lab to be included in school education system. By teaching the basics of robotics to the students, one can open up a whole new world for them and exciting opportunities which they wouldn't have access to. In traditional teaching methods of science and engineering, students lack experience in applying physical principles to the physical situation in real time. Students are not engaged in creating interest in interactive learning. To overcome above problem, this paper presents a new and versatile interactive learning tool using the Whizbrabo Robotic Education Module. This module describes the method of an educational tool based on robotics to study electrical component interfacing, pcb design, mechanical structure design and elementary programming skill. The module has been demonstrated to school students of higher secondary, and undergraduate student of various colleges. The key advantages of robotics in school education will enhance the level of programming, creativity and prepare them for the future, turn their frustration into innovation and promote inclusiveness. Robotics has a lot of educational potential.
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Park, M. H., B. J. Jin, T. J. Yun, J. S. Son, C. G. Kim, and I. S. Kim. "Control of the weld quality using welding parameters in a robotic welding process." Journal of Achievements in Materials and Manufacturing Engineering 1, no. 87 (2018): 32–40. http://dx.doi.org/10.5604/01.3001.0012.0737.
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Purpose: Since the welding automations have widely been required for industries and engineering, the development of the predicted model has become more important for the increased demands for the automatic welding systems where a poor welding quality becomes apparent if the welding parameters are not controlled. The automated welding system must be modelling and controlling the changes in weld characteristics and produced the output that is in some way related to the change being detected as welding quality. To be acceptable a weld quality must be positioned accurately with respect to the joints, have good appearance with sufficient penetration and reduce low porosity and inclusion content. Design/methodology/approach: To achieve the objectives, two intelligent models involving the use of a neural network algorithm in arc welding process with the help of a numerical analysis program MATLAB have been developed. Findings: The results represented that welding quality was fully capable of quantifying and qualifying the welding faults. Research limitations/implications: Welding parameters in the arc welding process should be well established and categorized for development of the automatic welding system. Furthermore, typical characteristics of welding quality are the bead geometry, composition, microstructure and appearance. However, an intelligent algorithm that predicts the optimal bead geometry and accomplishes the desired mechanical properties of the weldment in the robotic GMA (Gas Metal Arc) welding should be required. The developed algorithm should expand a wide range of material thicknesses and be applicable in all welding position for arc welding process. Furthermore, the model must be available in the form of mathematical equations for the automatic welding system. Practical implications: The neural network models which called BP (Back Propagation) and LM (Levenberg-Marquardt) neural networks to predict optimal welding parameters on the required bead reinforcement area in lab joint in the robotic GMA welding process have been developed. Experimental results have been employed to find the optimal algorithm to predict bead reinforcement area by BP and LM neural networks in lab joint in the robotic GMA welding. The developed intelligent models can be estimated the optimal welding parameters on the desired bead reinforcement area and weld criteria, establish guidelines and criteria for the most effective joint design for the robotic arc welding process. Originality/value: In this study, intelligent models, which employed the neural network algorithms, one of AI (Artificial Intelligence) technologies have been developed to study the effects of welding parameters on bead reinforcement area and to predict the optimal bead reinforcement area for lab joint in the robotic GMA welding process. BP (Back Propagation) and LM (Levenberg-Marquardt) neural network algorithm have been used to develop the intelligent model.
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CHIEN, ANDY, FU-HAN HSIEH, CHING HUANG, FEI-CHUN CHANG, NAI-HSIN MENG, and LI-WEI CHOU. "THE DEVELOPMENT OF AN EMG CONTROLLER-BASED ROBOTIC GAIT TRAINING SYSTEM AND ITS CLINICAL FEASIBILITY FOR SUBACUTE STROKE PATIENTS IN IMPROVING LOCOMOTIVE FUNCTION." Journal of Mechanics in Medicine and Biology 19, no. 02 (2019): 1940018. http://dx.doi.org/10.1142/s0219519419400189.
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One-third of stroke survivors fail to regain independent ambulation and strokes have been identified as a significant source of long-term disability and a tremendous health burden. Robot-assisted gait rehabilitation is gaining traction and advocators for its inclusion as part of the routine post-stroke rehabilitation program are on the increase. However, despite the recent technological advances in the development and design of better robotics, the research evidence on the best model of robotic training remains sparse and unclear. It is therefore the aim of the current study to comparatively investigate the clinical feasibility and efficacy of a recently developed HIWIN Robotic Gait Training System (MRG-P100) combined with the use of a lab-developed MBS-E100 EMG system as a controller on facilitating the development of an appropriate gait pattern for motor impaired subacute stroke patients. The results indicated that due to the heterogeneity of stroke-induced changes in muscle characteristics, an “auto-fit” algorithm was required to allow constant monitoring and updating of the appropriate threshold based on EMG signals captured during previous gait cycle in order to determine the desired muscle activation threshold for the current gait cycle. Eighteen participants were tested using the new auto-fit algorithm and results demonstrated a significantly more fluent and physiologically appropriate gait pattern.
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Tibbets, John H. "Not too Far from the Tree." Mechanical Engineering 140, no. 02 (2018): 28–33. http://dx.doi.org/10.1115/1.2018-feb1.
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This article explores the concept of robotic harvesting and use of computer, sensors, and artificial intelligence in the field of harvesting. More powerful computers, better sensors, and improved artificial intelligence promise to make machines competitive with human laborers for picking the apple harvest. Israel-based FFRobotics is one of the two companies racing to commercialize the world’s first mechanical apple picker. FFRobotics plan to test their apple-picking robot on Washington’s 2018 harvest, which runs from mid-August through mid-November. Modern orchard designs also allow engineers to build simpler apple-picking systems, according to Amir Degani, founder of the Civil, Environmental, and Agricultural Robotics Lab at Technion-Israel Institute of Technology in Haifa. Degani advised with FFRobotics on developing its robotic arm. FFRobotics is still struggling with whether to go with open- or closed-loop controller. The open-loop system recognizes a specific fruit and sends the gripper to that location. If a strong wind moves the apple left or right, the gripper does not follow. The closed-loop system tracks the movement of the fruit by distinctive points on the apple’s face as guides and adjusts the arm as it moves closer to the apple. While closed-loop systems are more effective, they are also too expensive.