Robotics Laboratory Research Articles

Enacting Identity Work and Identity Regulation in the Digitalisation of Industrial R&D

This paper draws on professional identity theory to explain how industrial R&D scientists within a large UK firm reconstruct their identities in the context of digitalisation. Whereas scientists routinely conducted most of their experiments manually, the firm’s digitalisation strategy introduced advanced laboratory robotics and data analytics tools which disrupted routine R&D work. We unpack the processes of identity regulation and identity work to identify key factors shaping acceptance and resistance to the firm’s digitalisation efforts. We show how scientists negotiate and adapt to challenges such as a steep learning curve, as well as how managers and co-workers developed strategies to address emerging issues. By examining the interplay between identity regulation and identity work, we argue that R&D scientists undertake three types of identity work to reconstruct their professional identity, namely positive reframing, learning, and technology shaping. We contribute to the literature by offering an analysis of identity construction in the context of the digitalisation of science and developing a conceptual framework that reveals the complex interplay between identity regulation and identity work in the context of digitalisation.

Surgical Residents’ Perception of Multi-Specialty Learning

Perceptions are important and can affect efficacy of trainer-trainee interactions. Inherent bias toward other specialties may influence the perceived benefit of a multi-specialty learning environment. The aim of this work was to determine surgical resident perceptions regarding the utility of learning from faculty and with learners from other surgical specialties. We measured surgical residents' perceptions before and after a multi-specialty robotic simulation event. Pre- and post-activity surveys were administered electronically to all residents determining previous experience with robotic surgery, perceptions of learning from faculty in different surgical sub-specialties, and of learning from and with residents in other surgical specialties. Robotic simulation laboratory. General surgery (GS), Obstetrics and gynecology (OBG), and Urology (URO) residents in one academic healthcare program. Prior to the simulation, OBG and URO residents perceived highest utility in learning from faculty within their own specialty. While OBG residents reported high pre-activity agreement that learning from other faculty was useful, more than 50% of GS and URO residents were neutral or disagreed that learning from OBG faculty was useful. Pre-activity, all specialties perceived highest value in learning from and about residents of their own specialty. Following the educational event, all specialties reported increased agreement that learning from faculty of different specialties had utility. Following the simulation, the cohort reported the multi-specialty learning environment improved their knowledge and confidence in robotic surgery. Participation in a multi-specialty educational event can improve perceptions of surgical residents regarding the utility of being taught by faculty in different specialties. Resident opinion of the benefits of learning with and about learners from other specialties can also be improved. Multi-specialty learning environments are important in developing communities of practice to allow socialization and promotion of positive identity development in our surgical residents, which may ultimately benefit efficacy of learning and patient care.

The Assistant Personal Robot Project: From the APR-01 to the APR-02 Mobile Robot Prototypes

This paper describes the evolution of the Assistant Personal Robot (APR) project developed at the Robotics Laboratory of the University of Lleida, Spain. This paper describes the first APR-01 prototype developed, the basic hardware improvement, the specific anthropomorphic improvements, and the preference surveys conducted with engineering students from the same university in order to maximize the perceived affinity with the final APR-02 mobile robot prototype. The anthropomorphic improvements have covered the design of the arms, the implementation of the arm and symbolic hand, the selection of a face for the mobile robot, the selection of a neutral facial expression, the selection of an animation for the mouth, the application of proximity feedback, the application of gaze feedback, the use of arm gestures, the selection of the motion planning strategy, and the selection of the nominal translational velocity. The final conclusion is that the development of preference surveys during the implementation of the APR-02 prototype has greatly influenced its evolution and has contributed to increase the perceived affinity and social acceptability of the prototype, which is now ready to develop assistance applications in dynamic workspaces.

VGG16-random fourier hybrid model for masked face recognition.

With the recent COVID-19 pandemic, wearing masks has become a necessity in our daily lives. People are encouraged to wear masks to protect themselves from the outside world and thus from infection with COVID-19. The presence of masks raised serious concerns about the accuracy of existing facial recognition systems since most of the facial features are obscured by the mask. To address these challenges, a new method for masked face recognition is proposed that combines a cropping-based approach (upper half of the face) with an improved VGG-16 architecture. The finest features from the un-occluded facial region are extracted using a transfer learned VGG-16 model (Forehead and eyes). The optimal cropping ratio is investigated to give an enhanced feature representation for recognition. To avoid the overhead of bias, the obtained feature vector is mapped into a lower-dimensional feature representation using a Random Fourier Feature extraction module. Comprehensive experiments on the Georgia Tech Face Dataset, Head Pose Image Dataset, and Face Dataset by Robotics Lab show that the proposed approach outperforms other state-of-the-art approaches for masked face recognition.

Sistem Informasi Peminjaman Alat Di Laboratorium Otomasi Dan Robotik Fakultas Teknik Universitas Sebelas Maret Surakarta

The Faculty of Engineering, Universitas Sebelas Maret (UNS) Surakarta has an information system to record data on borrowing tools in the automation and robotics laboratories, although they still use manual bookkeeping archives. This manual system has a weakness, namely it takes a lot of time to make a data report on borrowing tools. In addition, the existing tool lending system has not run optimally, so it is necessary to develop a system so that existing data can be integrated. The method used for the development of the tool lending system uses the System Development Life Cycle with the Waterfall model. The tool lending system is made using the PHP language and MySQL database as a data storage medium. The purpose of developing this information system is to speed up and simplify the process of borrowing tools, recaping data on borrowing tools, and making reports on borrowing laboratory equipment. This laboratory equipment loan system can be accessed by students, laboratory heads and admins. With the creation of the new system, it is hoped that it can assist and improve the performance of the UNS Faculty of Engineering staff, making it more effective and efficient in collecting data on borrowing tools in the automation and robotics laboratory.

Eğitim ve Araştırma Amaçlı Sanal Robotik Laboratuvarı ve Materyallerinin Geliştirilmesi

Robotic era is near, has never been before. In this new era, robotic education must have quality and accessibility for everyone. In this study, a disruptive technology for future of distance education based on virtual robotic laboratory (U-Plat) is presented. The created robotics education platform allows users to access a virtual robotics laboratory and training programs using internet interfaces. This environment allows them to control simulated robots, analyze and evaluate the results of experiments performed. U-Plat gives researchers, students and people working in the field of robotics the chance to learn Robot Operating System (ROS) and increase their knowledge with robotics training from beginner to advanced level. Also, U-Plat gives researchers opportunity to try their codes in online platform. Compared to traditional learning methods, U-Plat can be seen as an easier and more effective learning/teaching platform for ROS exercises, as it is an open source system. The user experience has been tried to be provided in all training tools with a very simplified and easily understandable interface. All designed training tools are provided through a web interface supported by advanced cloud systems and Docker container infrastructure. As a result, U-Plat is a novel robotic learning platform that can lead future laboratory research and distance robotic education.

Indoor Temperature and Relative Humidity Dataset of Controlled and Uncontrolled Environments

The large volume of data generated with the increasing development of Internet of Things applications has encouraged the development of a large number of works related to data management, wireless communication technologies, the deployment of sensor networks with limited resources, and energy consumption. Different types of new or well-known algorithms have been used for the processing and analysis of data acquired through sensor networks, algorithms for compression, filtering, calibration, analysis, or variables being common. In some cases, databases available on the network, public government databases, data generated from sensor networks deployed by the authors themselves, or values generated by simulation are used. In the case that the work approach is more related to the algorithm than to the characteristics of the sensor networks, these data source options may have some limitations such as the availability of databases, the time required for data acquisition, the need for the deployment of a real sensors network, and the reliability or characteristics of acquired data. The dataset in this article contains 4,164,267 values of timestamp, indoor temperature, and relative humidity acquired in the months of October and November 2019, with twelve temperature and humidity sensors Xiaomi Mijia at the laboratory of Control Systems and Robotics, and the De La Salle Museum of Natural Sciences, both of the Instituto Tecnológico Metropolitano, Medellín—Colombia. The devices were calibrated in a Metrology Laboratory accredited by the National Accreditation Body of Colombia (Organismo Nacional de Acreditación de Colombia—ONAC). The dataset is available in Mendeley Data repository.

Symbolic and Numerical Mathematical Modeling of the Jacobian of the Yaskawa Motoman - Gp7 Robot using Matlab©

Robotic manipulators have besides static positioning problems, but besides static we have in the robot its speeds and forces applied in any kind of movement. one of the show important activities of robot motion control is the definition of its movements in the workspace. to perform these moves its joints need I ‘m moving and to define these positions in the spaces we need to calculate the direct kinematics and the opposite we call the inverse kinematics. The main objective of this paper is to present a study on velocity analysis, known as the Jacobian matrix. The methodology employed in this exploratory scientific research will ok developed from experimental tests, bibliographic references and case studies applied at the Advanced robotics Institute (IAR). the robot under study is the YASKAWA-MOTOMAN-GP7 present at the robotics Laboratory of the IAR. The work brings as contribution the implementation of the Denavit-Hartenberg notation and the validation of the Jacobian matrix of the robot. The results are the determination of the equations of the inverse kinematics using the method based on the inverse Jacobian matrix. The code was implemented in MATLAB© software capable of proving the developed mathematical model, which is applicable in industrial robots.

Robotic Nursing Assistant Applications and Human Subject Tests through Patient Sitter and Patient Walker Tasks

This study presents the implementation of basic nursing tasks and human subject tests with a mobile robotic platform (PR2) for hospital patients. The primary goal of this study is to define the requirements for a robotic nursing assistant platform. The overall designed application scenario consists of a PR2 robotic platform, a human subject as the patient, and a tablet for patient–robot communication. The PR2 robot understands the patient’s request and performs the requested task by performing automated action steps. Two categories and three tasks are defined as: patient sitter tasks, include object fetching and temperature measurement, and patient walker tasks, including supporting the patient while they are using the walker. For this designed scenario and these tasks, human subject tests are performed with 27 volunteers in the Assistive Robotics Laboratory at the University of Texas at Arlington Research Institute (UTARI). Results and observations from human subject tests are provided. These activities are part of a larger effort to establish adaptive robotic nursing assistants (ARNA) for physical tasks in hospital environments.

Trajectory Planning and Execution of Delta Robot

<div><p class="4">The main purpose of this study is to plan and execute effective trajectory on the Delta robot through graphical user interface (GUI) and appropriate electronic circuits, and optimize the integration with the mechanical prototype designed and implemented by the robot laboratory of Nueva Granada Military University, while considering and respecting its different characteristics, such as mechanical structure, workspace, kinematics, dynamics and motion singularity allow the correct development and implementation of algorithms that can effectively describe and control the planned trajectory.</p></div>

Automated Bioprocess Feedback Operation in a High-Throughput Facility via the Integration of a Mobile Robotic Lab Assistant

The development of biotechnological processes is challenging due to the diversity of process parameters. For efficient upstream development, parallel cultivation systems have proven to reduce costs and associated timelines successfully while offering excellent process control. However, the degree of automation of such small-scale systems is comparatively low, and necessary sample analysis requires manual steps. Although the subsequent analysis can be performed in a high-throughput manner, the integration of analytical devices remains challenging, especially when cultivation and analysis laboratories are spatially separated. Mobile robots offer a potential solution, but their implementation in research laboratories is not widely adopted. Our approach demonstrates the integration of a small-scale cultivation system into a liquid handling station for an automated cultivation and sample procedure. The samples are transported via a mobile robotic lab assistant and subsequently analyzed by a high-throughput analyzer. The process data are stored in a centralized database. The mobile robotic workflow guarantees a flexible solution for device integration and facilitates automation. Restrictions regarding spatial separation of devices are circumvented, enabling a modular platform throughout different laboratories. The presented cultivation platform is evaluated on the basis of industrially relevant E. coli BW25113 high cell density fed-batch cultivation. The necessary magnesium addition for reaching high cell densities in mineral salt medium is automated via a feedback operation loop between the analysis station located in the adjacent room and the cultivation system. The modular design demonstrates new opportunities for advanced control options and the suitability of the platform for accelerating bioprocess development. This study lays the foundation for a fully integrated facility, where the physical connection of laboratory equipment is achieved through the successful use of a mobile robotic lab assistant, and different cultivation scales can be coupled through the common data infrastructure.

Lessons Learned from two iterations of LLAMA, an Electrically Powered, Dynamic Quadruped Robot

This paper presents the design, control, and initial performance from two iterations of human-scale (∼75 kg) quadrupedal robots built under the U.S. Army Research Laboratory (ARL) Robotics Collaborative Technology Alliance (RCTA) LLAMA (Legged Locomotion and Movement Adaptation) project. These all-electric, quadruped robots are designed with custom quasi-directdrive actuators powering 3-DOF, serial-parallel legs. To our knowledge, this is the first all-electric quadruped robot of this mass scale. The centralized energy management system uses a capacitor bank to supply burst loads and buffer regenerated energy. A hierarchical control scheme enables rapid motions (up to 1.8 m/s) over a variety of terrains. The onboard sensing suite enables deliberate, autonomous operation across rubble fields. In addition, we report on practical observations, lessons learned from field testing of two generations of the platform, and current drawbacks, such as low absolute payload (9 kg) and battery life (35 minutes). These lessons include strategies to address secondary effects at larger scales and parameters with the most impact to improve future designs.

A Project Based Learning Approach for Improving Students' Computational Thinking Skills.

An educational robotics lab has been planned for undergraduate students in an Electronic Engineering degree, using the Project Based Learning (PBL) approach and the NAO robot. Students worked in a research context, with the aim of making the functions of the NAO robot as social and autonomous as possible, adopting in the design process the Wolfram Language (WL), from the Mathematica software. Interfacing the programming environment of the NAO with Mathematica, they solved in part the problem of autonomy of the NAO, thus realizing enhanced functions of autonomous movement, recognition of human faces and speech for improving the system social interaction. An external repository was created to streamline processes and stow data that the robot can easily access. Self-assessment processes demonstrated that the course provided students with useful skills to cope with real life problems. Cognitive aspects of programming by WL have also been collected in the students’ feedback.

RoboParty: 20 Editions Building Robots and Motivating Youngsters for Science, Technology, Engineering, and Mathematics Subjects [Competitions

Robotic products and services are quickly getting into people’s homes, and it is important to prepare the youngsters for new challenges. One way to motivate them is through competitive events <xref ref-type="bibr" rid="ref1" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">[1]</xref> . Back in 2006, the Laboratory of Automation and Robotics <xref ref-type="bibr" rid="ref2" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">[2]</xref> at the University of Minho <xref ref-type="bibr" rid="ref3" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">[3]</xref> , Guimarães, Portugal, created a new event called <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">RoboParty</i> <xref ref-type="bibr" rid="ref4" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">[4]</xref> . The main objective is to teach youngsters how to build and program a robot from scratch in a collaborative, fun, and friendly environment. The first edition was held in 2007. Every year the event attracts up to 500 people from different countries. With 13 editions held at the University of Minho, three in Lisbon, and four abroad (in Brazil, Germany, Canada, and Denmark), this event is internationally recognized for its new approach toward learning robotics.

Difference-in-relation: Diffracting human-robot encounters

This article adopts Donna Haraway’s (1992) and Karen Barad’s (2007) lenses of reflection and diffraction to probe into human-robot relationships in-the-making. Dominant practices of human-robot interaction aspire to an optics of reflection based on the belief that the differences inherent to machines need masking or assimilating. I propose that diffracting human-robot encounters requires becoming-with and co-worlding with artefacts and their asymmetries. Entering the robot lab to witness my collaborative Machine Movement Lab project and its diffractive strategies in-the-making, as well as the material-bodily knowledges they enact, offers situated insights into how they make tangible difference patterns and relational ontologies at work in our more-than-human encounters.

The performance of gelling fibre wound dressings under clinically relevant robotic laboratory tests.

The effectiveness of wound dressing performance in exudate management is commonly gauged in simple, non‐realistic laboratory setups, typically, where dressing specimens are submersed in vessels containing aqueous solutions, rather than by means of clinically relevant test configurations. Specifically, two key fluid–structure interaction concepts: sorptivity—the ability of wound dressings to transfer exudate, including viscous fluids, away from the wound bed by capillary action and durability—the capacity of dressings to maintain their structural integrity over time and particularly, at removal events, have not been properly addressed in existing test protocols. The present article reviews our recent published research concerning the development of clinically relevant testing methods for wound dressings, focussing on the clinical relevance of the tests as well as on the standardisation and automation of laboratory measurements of dressing performance. A second objective of this work was to compile the experimental results characterising the performance of gelling fibre dressings, which were acquired using advanced testing methods, to demonstrate differences across products that apparently belong to the same “gelling fibre” family but differ remarkably in materials, structure and composition and, thereby, in performance.

Highly-automated, high-throughput replication of yeast-based logic circuit design assessments.

We describe an experimental campaign that replicated the performance assessment of logic gates engineered into cells of Saccharomyces cerevisiae by Gander et al. Our experimental campaign used a novel high-throughput experimentation framework developed under Defense Advanced Research Projects Agency’s Synergistic Discovery and Design program: a remote robotic lab at Strateos executed a parameterized experimental protocol. Using this protocol and robotic execution, we generated two orders of magnitude more flow cytometry data than the original experiments. We discuss our results, which largely, but not completely, agree with the original report and make some remarks about lessons learned. Graphical

Twinning coordination action for spreading excellence in Aerial Robotics

Twinning coordination action for spreading excellence in Aerial Robotics AeRoTwin is a twinning coordination action for spreading excellence in aerial robotics. The project’s overall goal is to decrease networking gaps and deficiencies between UNIZG-FER and internationally-leading counterparts in the EU by significantly enhancing the S and T capacity of the Laboratory for Robotics and Intelligent Control Systems (LARICS) at UNIZG-FER. The strategic research domains are cooperative robotic missions, aerial robot navigation and aerial robot configurability.

Implementation of Robots Integration in Scaled Laboratory Environment for Factory Automation

Robotic systems for research and development of factory automation are complex and unavailable for broad deployment in robotic laboratory settings. The usual robotic factory automation setup consists of series of sensors, robotic arms and mobile robots integrated and orchestrated by a central information system. Cloud-based integration has been gaining traction in recent years. In order to build such a system in a laboratory environment, there are several practical challenges that have to be resolved to come to a point when such a system can become operational. In this paper, we present the development of one such system composed of (i) a cloud-based system built on top of open platform for innovation in logistics, (ii) a prototyped mobile robot with a forklift to manipulate pallets in a “factory” floor, and (iii) industrial robot ABB IRB 140 with a customized gripper and various sensors. A mobile robot is designed as an autonomous four Mecanum wheels system with on-board LiDAR and RGB-D sensor for simultaneous localization and mapping. The paper shows a use case of the overall system and highlights the advantages of having a laboratory setting with real robots for the research of factory automation in a laboratory environment. Moreover, the proposed solution could be scaled and replicated in real factory automation applications.

An Open eLearning Platform for Robotics Training (OpenPLeRobot Project)

In Greece, educational robotics does not have the impact observed in other countries, mainly because of the limited number of structures that offer educational robotics courses, the cost of participation, the cost of robotic packages and the lack of time of young students combined with the inability to move independently. OpenPLeRobot project promotes development of innovative product of eLearning open platform for Robotics Training, with experimental learning procedures and promotes the idea of an integrated robotics toolbox of education and training, based upon innovative ICT tools, that simulates robotics applications in virtual reality environment, supported with robotics training equipment and ICT toolkits. OpenPLeRobot project is designed to support communication of trainers and trainees of robotics, through synchronous and asynchronous e- learning educational environment, in pre - school and school children and performs as a prototype robotics laboratory that stimulates creative robotics constructions and motivates computational logic in education. As a result this project has positive results at all levels of the educational process, and providing skills (teaching becomes more effective), motivation (the conscious and unconscious factors are enhanced), readiness (helps to build an adequate background of experiences), experience (enhances experience), adaptation (improves the ability of the individual to live harmoniously) and health (contributes to the proper normal physical health, but also to his mental health).