Search results for: telepresence robot

Authors: Adedayo Ajayi, Patrick Luk, Liyun Lao

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This paper studies the supportive needs for the electrical infrastructure of the green airport. In particular, the core objective revolves around the choice of electric grid configuration required to meet the expected electrified loads, i.e., the taxiing and charging loads of hybrid /pure electric aircraft in the airport. Further, reliability and resilience are critical aspects of a newly proposed grid; the concept of mobile energy storage as energy as a service (EAAS) for grid support in the proposed green airport is investigated using an autonomous electric taxiing robot (A-ETR) at a case study (Cranfield Airport). The performance of the model is verified and validated through DigSILENT power factory simulation software to compare the networks in terms of power quality, short circuit fault levels, system voltage profile, and power losses. Contingency and reliability index analysis are further carried out to show the potential of EAAS on the grid. The results demonstrate that the low voltage a.c network ( LVAC) architecture gives better performance with adequate compensation than the low voltage d.c (LVDC) microgrid architecture for future green airport electrification integration. And A-ETR can deliver energy as a service (EaaS) to improve the airport's electrical power system resilience and energy supply.

Keywords: reliability, voltage profile, flightpath 2050, green airport

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Authors: Seyed Esmail Seyedi Bariran, Khairul Salleh Mohamed Sahari

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In robotics literature, the simultaneous localization and mapping (SLAM) is commonly associated with a priori-posteriori problem. The autonomous vehicle needs a neutral map to spontaneously track its local position, i.e., “localization” while at the same time a precise path estimation of the environment state is required for effective route planning and obstacle avoidance. On the other hand, the environmental noise factors can significantly intensify the inherent uncertainties in using odometry information and measurements obtained from the robot’s exteroceptive sensor which in return directly affect the overall performance of the corresponding SLAM. Therefore, the current work is primarily dedicated to provide a diagnostic analysis of six SLAM algorithms including FastSLAM, L-SLAM, GraphSLAM, Grid SLAM and DP-SLAM. A SLAM simulated environment consisting of two sets of landmark locations and robot waypoints was set based on modified EKF and UKF in MATLAB using two separate maps for indoor and outdoor route planning subject to natural and artificial obstacles. The simulation results are expected to provide an unbiased platform to compare the estimation performances of the five SLAM models as well as on the reliability of each SLAM model for indoor and outdoor applications.

Keywords: route planning, obstacle, estimation performance, FastSLAM, L-SLAM, GraphSLAM, Grid SLAM, DP-SLAM

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Authors: Brian Romansky

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There are many practical, commercially available robots and semi-autonomous systems that are currently available for use in a wide variety of construction tasks. Adoption of these technologies has the potential to reduce the time and cost to deliver a project, reduce variability and risk in delivery time, increase quality, and improve safety on the job site. These benefits come with a cost for equipment rental or contract fees, access to specialists to configure the system, and time needed for set-up and support of the machines while in use. Calculation of the net ROI (Return on Investment) requires detailed information about the geometry of the site, the volume of work to be done, the overall project schedule, as well as data on the capabilities and past performance of available robotic systems. Assembling the required data and comparing the ROI for several options is complex and tedious. Many project managers will only consider the use of a robot in targeted applications where the benefits are obvious, resulting in low levels of adoption of automation in the construction industry. This work demonstrates how data already resident in many BIM (Building Information Model) projects can be used to automate ROI estimation for a sample set of commercially available construction robots. Calculations account for set-up and operating time along with scheduling support tasks required while the automated technology is in use. Configuration parameters allow for prioritization of time, cost, or safety as the primary benefit of the technology. A path toward integration and use of automatic ROI calculation with a database of available robots in a BIM platform is described.

Keywords: automation, BIM, robot, ROI.

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Authors: Seongcheol Kwon, Jeongmin Kim, Kwang Ryel Ryu

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We assume an IoT-based smart-home environment where the on-off status of each of the electrical appliances including the room lights can be recognized in a real time by monitoring and analyzing the smart meter data. At any moment in such an environment, we can recognize what the household or the user is doing by referring to the status data of the appliances. In this paper, we focus on a smart-home service that is to activate a robot vacuum cleaner at right time by recognizing the user situation, which requires a situation-aware model that can distinguish the situations that allow vacuum cleaning (Yes) from those that do not (No). We learn as our candidate models a few classifiers such as naïve Bayes, decision tree, and logistic regression that can map the appliance-status data into Yes and No situations. Our training and test data are obtained from simulations of user behaviors, in which a sequence of user situations such as cooking, eating, dish washing, and so on is generated with the status of the relevant appliances changed in accordance with the situation changes. During the simulation, both the situation transition and the resulting appliance status are determined stochastically. To compare the performances of the aforementioned classifiers we obtain their learning curves for different types of users through simulations. The result of our empirical study reveals that naïve Bayes achieves a slightly better classification accuracy than the other compared classifiers.

Keywords: situation-awareness, smart home, IoT, machine learning, classifier

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Authors: Brahmi Brahim, Mohammad Habibur Rahman, Maarouf Saad, Cristóbal Ochoa Luna

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A repetitive training movement is an efficient method to improve the ability and movement performance of stroke survivors and help them to recover their lost motor function and acquire new skills. The ETS-MARSE is seven degrees of freedom (DOF) exoskeleton robot developed to be worn on the lateral side of the right upper-extremity to assist and rehabilitate the patients with upper-extremity dysfunction resulting from stroke. Practically, rehabilitation activities are repetitive tasks, which make the assistive/robotic systems to suffer from repetitive/periodic uncertainties and external perturbations induced by the high-order dynamic model (seven DOF) and interaction with human muscle which impact on the tracking performance and even on the stability of the exoskeleton. To ensure the robustness and the stability of the robot, a new nonlinear backstepping control was implemented with designed tests performed by healthy subjects. In order to limit and to reject the periodic/repetitive disturbances, an iterative estimator was integrated into the control of the system. The estimator does not need the precise dynamic model of the exoskeleton. Experimental results confirm the robustness and accuracy of the controller performance to deal with the external perturbation, and the effectiveness of the iterative estimator to reject the repetitive/periodic disturbances.

Keywords: backstepping control, iterative control, Rehabilitation, ETS-MARSE

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Authors: Solomon Okorley

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With the emergence of artificial intelligence, a proposition that has been made with increasing conviction is the need to assign legal personhood to robots. A major problem that arises when dealing with robots is the issue of liability: who do it hold liable when a robot causes harm? The suggestion to assign legal personality to robots has been made to aid in the assignment of liability. This paper contends that it is premature to assign legal personhood to robots. The paper employed the doctrinal and comparative research methodology. The paper first discusses the various theories that underpin the granting of legal personhood to juridical personalities to ascertain whether these theories can aid in the proposition to assign legal personhood to robots. These theories include fiction theory, aggregate theory, realist theory, and organism theory. Except for the aggregate theory, the fiction theory, the realist theory and the organism theory provide a good foundation to the proposal for legal personhood to be assigned to robots. The paper considers whether robots should be assigned legal personhood from a jurisprudential approach. The legal positivists assert that no metaphysical presuppositions are needed to determine who could be a legal person: the sole deciding factor is the engagement in legal relations and this prerequisite could be fulfilled by robots. However, rationalists, religionists and naturalists assert that the satisfaction of the metaphysical criteria is the basis of legal personality and since robots do not possess this feature, they cannot be assigned legal personhood. This differing perspective shows that the jurisprudential school of thought to which one belongs influences the decision whether to assign legal personhood to robots. The paper makes arguments for and against the assigning of legal personhood to robots. Assigning legal personhood to robots is necessary for the assigning of liability; and since robots are independent in their operation, they should be assigned legal personhood. However, it is argued that the degree of autonomy is insufficient. Robots do not understand legal obligations; they do not have a will of their own and the purported autonomy that they possess is an ‘imputed autonomy’. A crucial question to be asked is ‘whether it is desirable to confer legal personhood on robots’ and not ‘whether legal personhood should be assigned to robots’. This is due to the subjective nature of the responses to such a question as well as the peculiarities of countries in response to this question. The main argument in support of assigning legal personhood to robots is to aid in assigning liability. However, it is argued conferring legal personhood on robots is not the only way to deal with liability issues. Since any of the stakeholders involved with the robot system can be held liable for an accident, it is not desirable to assign legal personhood to robot. It is forecasted that in the epoch of strong artificial intelligence, granting robots legal personhood is plausible; however, in the current era, it is premature.

Keywords: autonomy, legal personhood, premature, jurisprudential

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Authors: Vinicius G. Goecks, Gregory M. Gremillion, William D. Nothwang

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Modern approaches to train intelligent agents rely on prolonged training sessions, high amounts of input data, and multiple interactions with the environment. This restricts the application of these learning algorithms in robotics and real-world applications, in which there is low tolerance to inadequate actions, interactions are expensive, and real-time processing and action are required. This paper addresses this issue introducing CyberSteer, a novel approach to efficiently design intrinsic reward functions based on human intention to guide deep reinforcement learning agents with no environment-dependent rewards. CyberSteer uses non-expert human operators for initial demonstration of a given task or desired behavior. The trajectories collected are used to train a behavior cloning deep neural network that asynchronously runs in the background and suggests actions to the deep reinforcement learning module. An intrinsic reward is computed based on the similarity between actions suggested and taken by the deep reinforcement learning algorithm commanding the agent. This intrinsic reward can also be reshaped through additional human demonstration or critique. This approach removes the need for environment-dependent or hand-engineered rewards while still being able to safely shape the behavior of autonomous robotic agents, in this case, based on human intention. CyberSteer is tested in a high-fidelity unmanned aerial vehicle simulation environment, the Microsoft AirSim. The simulated aerial robot performs collision avoidance through a clustered forest environment using forward-looking depth sensing and roll, pitch, and yaw references angle commands to the flight controller. This approach shows that the behavior of robotic systems can be shaped in a reduced amount of time when guided by a non-expert human, who is only aware of the high-level goals of the task. Decreasing the amount of training time required and increasing safety during training maneuvers will allow for faster deployment of intelligent robotic agents in dynamic real-world applications.

Keywords: human-robot interaction, intelligent robots, robot learning, semisupervised learning, unmanned aerial vehicles

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Authors: Catherine McWhorter

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Robotics is a fast-evolving field lacking comprehensive and harm-mitigating regulation; it also lacks critical data on how human-robot interaction (HRI) may affect human psychology. As most anthropomorphic robots are intended as substitutes for humans, this paper asserts that the commercial robotics industry should be preemptively regulated at the federal level such that robots capable of embodying a victim role in criminal scenarios (“vicbots”) are prohibited until clinical studies determine their effects on the user and society. The results of these studies should then inform more permanent legislation that strives to mitigate risks of harm without infringing upon fundamental rights or stifling innovation. This paper explores these concepts through the lens of the sex robot industry. The sexbot industry offers some of the most realistic, interactive, and customizable robots for sale today. From approximately 2010 until 2017, some sex robot producers, such as True Companion, actively promoted ‘vicbot’ culture with personalities like “Frigid Farrah” and “Young Yoko” but received significant public backlash for fetishizing rape and pedophilia. Today, “Frigid Farrah” and “Young Yoko” appear to have vanished. Sexbot producers have replaced preprogrammed vicbot personalities in favor of one generic, customizable personality. According to the manufacturer ainidoll.com, when asked, there is only one thing the user won’t be able to program the sexbot to do – “…give you drama”. The ability to customize vicbot personas is possible with today’s generic personality sexbots and may undermine the intent of some current legislative efforts. Current debate on the effects of vicbots indicates a lack of consensus. Some scholars suggest vicbots may reduce the rate of actual sex crimes, and some suggest that vicbots will, in fact, create sex criminals, while others cite their potential for rehabilitation. Vicbots may have value in some instances when prescribed by medical professionals, but the overall uncertainty and lack of data further underscore the need for preemptive regulation and clinical research. Existing literature on exposure to media violence and its effects on prosocial behavior, human aggression, and addiction may serve as launch points for specific studies into the hyperrealism of vicbots. Of course, the customization, anthropomorphism and artificial intelligence of sexbots, and therefore more mainstream robots, will continue to evolve. The existing sexbot industry offers an opportunity to preemptively regulate and to research answers to these and many more questions before this type of technology becomes even more advanced and mainstream. Robots pose complicated moral, ethical, and legal challenges, most of which are beyond the scope of this paper. By examining the possibility for custom vicbots via the sexbots industry, reviewing existing literature on regulation, media violence, and vicbot user effects, this paper strives to underscore the need for preemptive federal regulation prohibiting vicbot capabilities in robots while advocating for further research into the potential for the user and societal harm by the same.

Keywords: human-robot interaction effects, regulation, research, robots

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Authors: Jason R. King, Hugh H. T. Liu

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This research presents simulation and experimental work in the visual servoing of a quadrotor Unmanned Aerial Vehicle (UAV) to stabilize overtop of a moving target. Most previous work in the field assumes static or slow-moving, unpredictable targets. In this experiment, the target is assumed to be a friendly ground robot moving freely on a horizontal plane, which shares information with the UAV. This information includes velocity and acceleration information of the ground target to aid the quadrotor in its tracking task. The quadrotor is assumed to have a downward-facing camera which is fixed to the frame of the quadrotor. Only onboard sensing for the quadrotor is utilized for the experiment, with a VICON motion capture system in place used only to measure ground truth and evaluate the performance of the controller. The experimental platform consists of an ArDrone 2.0 and a Create Roomba, communicating using Robot Operating System (ROS). The addition of the target’s information is demonstrated to help the quadrotor in its tracking task using simulations of the dynamic model of a quadrotor in Matlab Simulink. A nested PID control loop is utilized for inner-loop control the quadrotor, similar to previous works at the Flight Systems and Controls Laboratory (FSC) at the University of Toronto Institute for Aerospace Studies (UTIAS). Experiments are performed with ground truth provided by an indoor motion capture system, and the results are analyzed. It is demonstrated that a velocity controller which incorporates the additional information is able to perform better than the controllers which do not have access to the target’s information.

Keywords: quadrotor, target tracking, unmanned aerial vehicle, UAV, UAS, visual servoing

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Authors: Hamidreza Hoshyarmanesh, Hosein Madieh, Sanju Lama, Yaser Maddahi, Garnette R. Sutherland, Kourosh Zareinia

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This paper illustrates the concept of an algorithm to register specified markers on the neuroArm surgical manipulators, an image-guided MR-compatible tele-operated robot for microsurgery and stereotaxy. Two range-finding algorithms, namely time-of-flight and phase-shift, are evaluated for registration and supervisory control. The time-of-flight approach is implemented in a semi-field experiment to determine the precise position of a tiny retro-reflective moving object. The moving object simulates a surgical tool tip. The tool is a target that would be connected to the neuroArm end-effector during surgery inside the magnet bore of the MR imaging system. In order to apply flight approach, a 905-nm pulsed laser diode and an avalanche photodiode are utilized as the transmitter and receiver, respectively. For the experiment, a high frequency time to digital converter was designed using a field-programmable gate arrays. In the phase-shift approach, a continuous green laser beam with a wavelength of 530 nm was used as the transmitter. Results showed that a positioning error of 0.1 mm occurred when the scanner-target point distance was set in the range of 2.5 to 3 meters. The effectiveness of this non-contact approach exhibited that the method could be employed as an alternative for conventional mechanical registration arm. Furthermore, the approach is not limited by physical contact and extension of joint angles.

Keywords: 3D laser scanner, intraoperative MR imaging, neuroArm, real time registration, robot-assisted surgery, supervisory control

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Authors: Naghmeh Zamani, Ashkan Pourkand, David Grow

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This paper presents the design and mechanical model of a hybrid impedance/admittance haptic device optimized for applications, like bone drilling, spinal awl probe use, and other surgical techniques were high force is required in the tool-axial direction, and low impedance is needed in all other directions. The performance levels required cannot be satisfied by existing, off-the-shelf haptic devices. This design may allow critical improvements in simulator fidelity for surgery training. The device consists primarily of two low-mass (carbon fiber) plates with a rod passing through them. Collectively, the device provides 6 DOF. The rod slides through a bushing in the top plate and it is connected to the bottom plate with a universal joint, constrained to move in only 2 DOF, allowing axial torque display the user’s hand. The two parallel plates are actuated and located by means of four cables pulled by motors. The forward kinematic equations are derived to ensure that the plates orientation remains constant. The corresponding equations are solved using the Newton-Raphson method. The static force/torque equations are also presented. Finally, we present the predicted distribution of location error, cables velocity, cable tension, force and torque for the device. These results and preliminary hardware fabrication indicate that this design may provide a revolutionary approach for haptic display of many surgical procedures by means of an architecture that allows arbitrary workspace scaling. Scaling of the height and width can be scaled arbitrarily.

Keywords: cable direct driven robot, haptics, parallel plates, bone drilling

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Authors: David Blaine, George Raschbaum

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The evaluation of DHCP has synthesized SCSI disks, and current trends suggest that the exploration of e-business that would allow for further study into robots will soon emerge. Given the current status of embedded algorithms, hackers worldwide obviously desire the exploration of replication, which embodies the confusing principles of programming languages. In our research we concentrate our efforts on arguing that erasure coding can be made "fuzzy", encrypted, and game-theoretic.

Keywords: SCHI disks, robot, algorithm, hacking, programming language

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Authors: Alexandros Lioulemes, Michail Theofanidis, Varun Kanal, Konstantinos Tsiakas, Maher Abujelala, Chris Collander, William B. Townsend, Angie Boisselle, Fillia Makedon

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This paper presents a home-based robot-rehabilitation instrument, called ”MAGNI Dynamics”, that utilized a vision-based kinematic/dynamic module and an adaptive haptic feedback controller. The system is expected to provide personalized rehabilitation by adjusting its resistive and supportive behavior according to a fuzzy intelligence controller that acts as an inference system, which correlates the user’s performance to different stiffness factors. The vision module uses the Kinect’s skeletal tracking to monitor the user’s effort in an unobtrusive and safe way, by estimating the torque that affects the user’s arm. The system’s torque estimations are justified by capturing electromyographic data from primitive hand motions (Shoulder Abduction and Shoulder Forward Flexion). Moreover, we present and analyze how the Barrett WAM generates a force-field with a haptic controller to support or challenge the users. Experiments show that by shifting the proportional value, that corresponds to different stiffness factors of the haptic path, can potentially help the user to improve his/her motor skills. Finally, potential areas for future research are discussed, that address how a rehabilitation robotic framework may include multisensing data, to improve the user’s recovery process.

Keywords: human-robot interaction, kinect, kinematics, dynamics, haptic control, rehabilitation robotics, artificial intelligence

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Authors: Javier Romera, Alberto Justo, Ignacio Fidalgo, Joshue Perez, Javier Araluce

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Nowadays, individuals with mobility needs face a significant challenge when docking vehicles. In many cases, after parking, they encounter insufficient space to exit, leading to two undesired outcomes: either avoiding parking in that spot or settling for improperly placed vehicles. To address this issue, the following paper presents a parking control system employing gestural teleoperation. The system comprises three main phases: capturing body markers, interpreting gestures, and transmitting orders to the vehicle. The initial phase is centered around the MediaPipe framework, a versatile tool optimized for real-time gesture recognition. MediaPipe excels at detecting and tracing body markers, with a special emphasis on hand gestures. Hands detection is done by generating 21 reference points for each hand. Subsequently, after data capture, the project employs the MultiPerceptron Layer (MPL) for indepth gesture classification. This tandem of MediaPipe's extraction prowess and MPL's analytical capability ensures that human gestures are translated into actionable commands with high precision. Furthermore, the system has been trained and validated within a built-in dataset. To prove the domain adaptation, a framework based on the Robot Operating System (ROS), as a communication backbone, alongside CARLA Simulator, is used. Following successful simulations, the system is transitioned to a real-world platform, marking a significant milestone in the project. This real vehicle implementation verifies the practicality and efficiency of the system beyond theoretical constructs.

Keywords: gesture detection, mediapipe, multiperceptron layer, robot operating system

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Authors: Titanilla Komenda

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Human-machine-collaboration defines a direct interaction between humans and machines to fulfil specific tasks. Those so-called collaborative machines are used without fencing and interact with humans in predefined workspaces. Even though, human-machine-collaboration enables a flexible adaption to variable degrees of freedom, industrial applications are rarely found. The reasons for this are not technical progress but rather limitations in planning processes ensuring safety for operators. Until now, humans and machines were mainly considered separately in the planning process, focusing on ergonomics and system performance respectively. Within human-machine-collaboration, those aspects must not be seen in isolation from each other but rather need to be analysed in interaction. Furthermore, a simulation model is needed that can validate the system performance and ensure the safety for the operator at any given time. Following on from this, a holistic simulation model is presented, enabling a simulative representation of collaborative tasks – including both, humans and machines. The presented model does not only include a geometry and a motion model of interacting humans and machines but also a numerical behaviour model of humans as well as a Boole’s probabilistic sensor model. With this, error scenarios can be simulated by validating system behaviour in unplanned situations. As these models can be defined on the basis of Failure Mode and Effects Analysis as well as probabilities of errors, the implementation in a collaborative model is discussed and evaluated regarding limitations and simulation times. The functionality of the model is shown on industrial applications by comparing simulation results with video data. The analysis shows the impact of considering human factors in the planning process in contrast to only meeting system performance. In this sense, an optimisation function is presented that meets the trade-off between human and machine factors and aids in a successful and safe realisation of collaborative scenarios.

Keywords: human-machine-system, human-robot-collaboration, safety, simulation

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Authors: Damith Tennakoon, Mojgan Jadidi, Seyedreza Razavialavi

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With recent advancements of automation in robotics, from self-driving cars to autonomous 4-legged quadrupeds, one industry that has been stagnant is the construction industry. The methodologies used in a modern-day construction site consist of arduous physical labor and the use of heavy machinery, which has not changed over the past few decades. The dangers of a modern-day construction site affect the health and safety of the workers due to performing tasks such as lifting and moving heavy objects and having to maintain unhealthy posture to complete repetitive tasks such as painting, installing drywall, and laying bricks. Further, training for heavy machinery is costly and requires a lot of time due to their complex control inputs. The main focus of this research is using immersive wearable technology and robotic arms to perform the complex and intricate skills of modern-day construction workers while alleviating the physical labor requirements to perform their day-to-day tasks. The methodology consists of mounting a stereo vision camera, the ZED Mini by Stereolabs, onto the end effector of an industrial grade robotic arm, streaming the video feed into the Virtual Reality (VR) Meta Quest 2 (Quest 2) head-mounted display (HMD). Due to the nature of stereo vision, and the similar field-of-views between the stereo camera and the Quest 2, human-vision can be replicated on the HMD. The main advantage this type of camera provides over a traditional monocular camera is it gives the user wearing the HMD a sense of the depth of the camera scene, specifically, a first-person view of the robotic arm’s end effector. Utilizing the built-in cameras of the Quest 2 HMD, open-source hand-tracking libraries from OpenXR can be implemented to track the user’s hands in real-time. A mixed-reality (XR) Unity application can be developed to localize the operator's physical hand motions with the end-effector of the robotic arm. Implementing gesture controls will enable the user to move the robotic arm and control its end-effector by moving the operator’s arm and providing gesture inputs from a distant location. Given that the end effector of the robotic arm is a gripper tool, gripping and opening the operator’s hand will translate to the gripper of the robot arm grabbing or releasing an object. This human-robot interaction approach provides many benefits within the construction industry. First, the operator’s safety will be increased substantially as they can be away from the site-location while still being able perform complex tasks such as moving heavy objects from place to place or performing repetitive tasks such as painting walls and laying bricks. The immersive interface enables precision robotic arm control and requires minimal training and knowledge of robotic arm manipulation, which lowers the cost for operator training. This human-robot interface can be extended to many applications, such as handling nuclear accident/waste cleanup, underwater repairs, deep space missions, and manufacturing and fabrication within factories. Further, the robotic arm can be mounted onto existing mobile robots to provide access to hazardous environments, including power plants, burning buildings, and high-altitude repair sites.

Keywords: construction automation, human-robot interaction, hand-tracking, mixed reality

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Authors: Arun Prasad, Abhishek Tiwari, Rekha Jaiswal, Vivek Chaudhary

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Background: Robotic Roux en Y gastric bypass is being done for some time but is technically difficult, requiring operating in both the sub diaphragmatic and infracolic compartments of the abdomen. This can mean a dual docking of the robot or a hybrid partial laparoscopic and partial robotic surgery. The Mini /One anastomosis /omega loop gastric bypass (MGB) has the advantage of having all dissection and anastomosis in the supracolic compartment and is therefore suitable technically for robotic surgery. Methods: We have done 208 robotic mini gastric bypass surgeries. The robot is docked above the head of the patient in the midline. Camera port is placed supra umbilically. Two ports are placed on the left side of the patient and one port on the right side of the patient. An assistant port is placed between the camera port and right sided robotic port for use of stapler. Distal stomach is stapled from the lesser curve followed by a vertical sleeve upwards leading to a long sleeve pouch. Jejunum is taken at 200 cm from the duodenojejunal junction and brought up to do a side to side gastrojejunostomy. Results: All patients had a successful robotic procedure. Mean time taken was 85 minutes. There were major intraoperative or post operative complications. No patient needed conversion or re-explorative surgery. Mean excess weight loss over a period of 2 year was about 75%. There was no mortality. Patient satisfaction score was high and was attributed to the good weight loss and minimal dietary modifications that were needed after the procedure. Long term side effects were anemia and bile reflux in a small number of patients. Conclusions: MGB / OAGB is gaining worldwide interest as a short simple procedure that has been shown to very effective and safe bariatric surgery. The purpose of this study was to report on the safety and efficacy of robotic surgery for this procedure. This is the first report of totally robotic mini gastric bypass.

Keywords: MGB, mini gastric bypass, OAGB, robotic bariatric surgery

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Authors: José Manuel Palma, Paula Pereira, Margarida Tomás

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Foreseen the future: Human factors integration in European Horizon Projects The development of new technology as artificial intelligence, smart sensing, robotics, cobotics or intelligent machinery must integrate human factors to address the need to optimize systems and processes, thereby contributing to the creation of a safe and accident-free work environment. Human Factors Integration (HFI) consistently pose a challenge for organizations when applied to daily operations. AGILEHAND and FORTIS projects are grounded in the development of cutting-edge technology - industry 4.0 and 5.0. AGILEHAND aims to create advanced technologies for autonomously sort, handle, and package soft and deformable products, whereas FORTIS focuses on developing a comprehensive Human-Robot Interaction (HRI) solution. Both projects employ different approaches to explore HFI. AGILEHAND is mainly empirical, involving a comparison between the current and future work conditions reality, coupled with an understanding of best practices and the enhancement of safety aspects, primarily through management. FORTIS applies HFI throughout the project, developing a human-centric approach that includes understanding human behavior, perceiving activities, and facilitating contextual human-robot information exchange. it intervention is holistic, merging technology with the physical and social contexts, based on a total safety culture model. In AGILEHAND we will identify safety emergent risks, challenges, their causes and how to overcome them by resorting to interviews, questionnaires, literature review and case studies. Findings and results will be presented in “Strategies for Workers’ Skills Development, Health and Safety, Communication and Engagement” Handbook. The FORTIS project will implement continuous monitoring and guidance of activities, with a critical focus on early detection and elimination (or mitigation) of risks associated with the new technology, as well as guidance to adhere correctly with European Union safety and privacy regulations, ensuring HFI, thereby contributing to an optimized safe work environment. To achieve this, we will embed safety by design, and apply questionnaires, perform site visits, provide risk assessments, and closely track progress while suggesting and recommending best practices. The outcomes of these measures will be compiled in the project deliverable titled “Human Safety and Privacy Measures”. These projects received funding from European Union’s Horizon 2020/Horizon Europe research and innovation program under grant agreement No101092043 (AGILEHAND) and No 101135707 (FORTIS).

Keywords: human factors integration, automation, digitalization, human robot interaction, industry 4.0 and 5.0

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Authors: Michael K. O. Ayomoh, Oyindamola A. Omotuyi

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Autonomous mobile robots deployed to explore or operate in a never explored or an abandoned sub-surface mine requires extreme effectiveness in coordination and communication. In a bid to transmit information from the depth of the mine to the external surface in real-time and amidst diverse physical, chemical and virtual impediments, the concept of unified cooperative robots is seen to be a proficient approach. This paper presents an effective [human → robot → task] coordination framework for effective exploration of an abandoned underground mine. The problem addressed in this research is basically the development of a globalized optimization model premised on time series differentiation and geometrical configurations for effective positioning of the two classes of robots in the cooperation namely the outermost stationary master (OSM) robots and the innermost dynamic task (IDT) robots for effective bi-directional signal transmission. In addition, the synchronization of a vision system and wireless communication system for both categories of robots, fiber optics system for the OSM robots in cases of highly sloppy or vertical mine channels and an autonomous battery recharging capability for the IDT robots further enhanced the proposed concept. The OSM robots are the master robots which are positioned at strategic locations starting from the mine open surface down to its base using a fiber-optic cable or a wireless communication medium all subject to the identified mine geometrical configuration. The OSM robots are usually stationary and function by coordinating the transmission of signals from the IDT robots at the base of the mine to the surface and in a reverse order based on human decisions at the surface control station. The proposed scheme also presents an optimized number of robots required to form the cooperation in a bid to reduce overall operational cost and system complexity.

Keywords: sub-surface mine, wireless communication, outermost stationary master robots, inner-most dynamic robots, fiber optic

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Authors: Darius Jakimavicius

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Artificial intelligence is the subject of intense debate in the international arena, identified both as a technological breakthrough and as a component of the strategic stability effect. Both the kinetic and non-kinetic development of AI and its application in the national strategies of the great powers may trigger a change in the security situation. Artificial intelligence is generally faster, more capable and more efficient than humans, and there is a temptation to transfer decision-making and control responsibilities to artificial intelligence. Artificial intelligence, which, once activated, can select and act on targets without further intervention by a human operator, blurs the boundary between human or robot (machine) warfare, or perhaps human and robot together. Artificial intelligence acts as a force multiplier that speeds up decision-making and reaction times on the battlefield. The role of humans is increasingly moving away from direct decision-making and away from command and control processes involving the use of force. It is worth noting that the autonomy and precision of AI systems make the process of strategic stability more complex. Deterrence theory is currently in a phase of development in which deterrence is undergoing further strain and crisis due to the complexity of the evolving models enabled by artificial intelligence. Based on the concept of strategic stability and deterrence theory, it is appropriate to develop further research on the development and impact of AI in order to assess AI from both a scientific and technical perspective: to capture a new niche in the scientific literature and academic terminology, to clarify the conditions for deterrence, and to identify the potential uses, impacts and possibly quantities of AI. The research problem is the impact of artificial intelligence developed by great powers on strategic stability. This thesis seeks to assess the impact of AI on strategic stability and deterrence principles, with human exclusion from the decision-making and control loop as a key axis. The interaction between AI and human actions and interests can determine fundamental changes in great powers' defense and deterrence, and the development and application of AI-based great powers strategies can lead to a change in strategic stability.

Keywords: artificial inteligence, strategic stability, deterrence theory, decision making loop

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Authors: Christa Fricke, Sibylle Meyer, Gert G. Wagner

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Our research focuses on the question of whether assistive and social robotics could pose a promising strategy to support the independent living of elderly people and potentially relieve relatives of any anxieties. To answer the question of how elderly people perceive the potential of robotics, we analysed the data from the Berlin Aging Study BASE-II (https://www.base2.mpg.de/de) (N=1463) and data from the German SYMPARTNER study (http://www.sympartner.de) (N=120) and compared those to a control group made up of people younger than 30 years (BASE II: N=241; SYMPARTNER: N=30). BASE-II is a cohort study of people living in Berlin, Germany. The sample covers more than 2200 cases; a questionnaire on the use and acceptance of assistive and social robots was carried out with a sub-sample of 1463 respondents in 2015. The SYMPARTNER study was done by SIBIS institute of Social Research, Berlin and included a total of 120 persons between the ages of 60 and 87 in Berlin and the rural German federal state of Thuringia. Both studies included a control group of persons between the ages of 20 and 35 (BASE II: N=241; SYMPARTNER: N=30). Additional data, representative for the whole population in Germany, will be surveyed in fall 2017 (Survey “Technikradar” [technology radar] by the National Academy of Science and Engineering). Since this survey is including some identical questions as BASE-II/SYMPARTNER, comparative results can be presented at 20th International Conference on Social Robotics in New York 2018. The complexity of the data gathered in BASE-II and SYMPARTNER, encompassing detailed socio-economic background characteristics as well as personality traits such as the personal attitude to risk taking, locus of control and Big Five, proves highly valuable and beneficial. Results show that participants’ expressions of resentment against robots are comparatively low. Participants’ personality traits play a role, however the effect sizes are small. Only 15 percent of participants received domestic robots with great scepticism. Participants aged older than 70 years expressed greatest rejection of the robotic assistant. The effect sizes however account for only a few percentage points. Overall, participants were surprisingly open to the robot and its usefulness. The analysis also shows that men’s acceptance of the robot is generally greater than that of women (with odds ratios of about 0.6 to 0.7). This applies to both assistive robots in the private household and in care environments. Men expect greater benefits of the robot than women. Women tend to be more sceptical of their technical feasibility than men. Interview results prove our hypothesis that men, in particular of the age group 60+, are more accustomed to delegate household chores to women. A delegation to machines instead of humans, therefore, seems palpable. The answer to the title question of this planned presentation is: social and assistive robots at home robots are not only accepted by men – but by fewer women than men.

Keywords: acceptance, care, gender, household

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Authors: Yaghoubi N., Moore Z., Van Der Veen S. M., Pidcoe P. E., Thomas J. S., Dexheimer B.

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Optoelectronic 3D motion capture systems, such as the Vicon kinematic system, are widely utilized in biomedical research to track joint motion. These systems are considered powerful and accurate measurement tools with <2 mm average error. However, these systems are costly and may be difficult to implement and utilize in a clinical setting. 3D virtual reality (VR) is gaining popularity as an affordable and accessible tool to investigate motor control and perception in a controlled, immersive environment. The HTC Vive VR system includes puck-style trackers that seamlessly integrate into its VR environments. These affordable, wireless, lightweight trackers may be more feasible for clinical kinematic data collection. However, the accuracy of HTC Vive Trackers (3.0), when compared to optoelectronic 3D motion capture systems, remains unclear. In this preliminary study, we compared the HTC Vive Tracker system to a Vicon kinematic system in a simulated lumbar flexion task. A 6-DOF robot arm (SCORBOT ER VII, Eshed Robotec/RoboGroup, Rosh Ha’Ayin, Israel) completed various reaching movements to mimic increasing levels of hip flexion (15°, 30°, 45°). Light reflective markers, along with one HTC Vive Tracker (3.0), were placed on the rigid segment separating the elbow and shoulder of the robot. We compared position measures simultaneously collected from both systems. Our preliminary analysis shows no significant differences between the Vicon motion capture system and the HTC Vive tracker in the Z axis, regardless of hip flexion. In the X axis, we found no significant differences between the two systems at 15 degrees of hip flexion but minimal differences at 30 and 45 degrees, ranging from .047 cm ± .02 SE (p = .03) at 30 degrees hip flexion to .194 cm ± .024 SE (p < .0001) at 45 degrees of hip flexion. In the Y axis, we found a minimal difference for 15 degrees of hip flexion only (.743 cm ± .275 SE; p = .007). This preliminary analysis shows that the HTC Vive Tracker may be an appropriate, affordable option for gross motor motion capture when the Vicon system is not available, such as in clinical settings. Further research is needed to compare these two motion capture systems in different body poses and for different body segments.

Keywords: lumbar, vivetracker, viconsystem, 3dmotion, ROM

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Authors: F. Boufera, F. Debbat

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This paper deals with an approach based on limit-cycles method for the problem of obstacle avoidance of mobile robots in unknown environments for any form of obstacles. The purpose of this approach is the improvement of limit-cycles method in order to obtain safe and flexible navigation. The proposed algorithm has been successfully tested in different configuration on simulation.

Keywords: mobile robot, navigation, avoidance of obstacles, limit-cycles method

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Authors: Luo Jiaoyang, Yu Hongyang

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In this paper, we explore a method that can be used in the working scene of intelligent industrial robots to confirm the identity information of operators to ensure that the robot executes instructions in a sufficiently safe environment. This approach uses three information modalities, namely visible light, depth, and sound. We explored a variety of fusion modes for the three modalities and finally used the joint feature learning method to improve the performance of the model in the case of noise compared with the single-modal case, making the maximum noise in the experiment. It can also maintain an accuracy rate of more than 90%.

Keywords: multimodal, kinect, machine learning, distance image

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Authors: Saradha Priya

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Developing virtual human is very important to meet the challenges occurred in many applications where human find difficult or risky to perform the task. A robot is a machine that can perform a task automatically or with guidance. Robotics is generally a combination of artificial intelligence and physical machines (motors). Computational intelligence involves the programmed instructions. This project proposes a robotic vehicle that has a camera, PIR sensor and text command based movement. It is specially designed to perform surveillance and other few tasks in the most efficient way. Serial communication has been occurred between a remote Base Station, GUI Application, and PC.

Keywords: Zigbee, camera, pirsensor, wireless transmission, DC motor

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Authors: Abisha Isaac Mohanlal

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Amidst all suspicions and cynicism raised by the legal fraternity, Artificial Intelligence has found its way into the legal system and has revolutionized the conventional forms of legal services delivery. Be it legal argumentation and research or resolution of complex legal disputes; artificial intelligence has crept into all legs of modern day legal services. Its impact has been largely felt by way of big data, legal expert systems, prediction tools, e-lawyering, automated mediation, etc., and lawyers around the world are forced to upgrade themselves and their firms to stay in line with the growth of technology in law. Researchers predict that the future of legal services would belong to artificial intelligence and that the age of human lawyers will soon rust. But as far as the Judiciary is concerned, even in the developed countries, the system has not fully drifted away from the orthodoxy of preferring Natural Intelligence over Artificial Intelligence. Since Judicial decision-making involves a lot of unstructured and rather unprecedented situations which have no single correct answer, and looming questions of legal interpretation arise in most of the cases, discretion and Emotional Intelligence play an unavoidable role. Added to that, there are several ethical, moral and policy issues to be confronted before permitting the intrusion of Artificial Intelligence into the judicial system. As of today, the human judge is the unrivalled master of most of the judicial systems around the globe. Yet, scientists of Artificial Intelligence claim that robot judges can replace human judges irrespective of how daunting the complexity of issues is and how sophisticated the cognitive competence required is. They go on to contend that even if the system is too rigid to allow robot judges to substitute human judges in the recent future, Artificial Intelligence may still aid in other judicial tasks such as drafting judicial documents, intelligent document assembly, case retrieval, etc., and also promote overall flexibility, efficiency, and accuracy in the disposal of cases. By deconstructing the major challenges that Artificial Intelligence has to overcome in order to successfully invade the human- dominated judicial sphere, and critically evaluating the potential differences it would make in the system of justice delivery, the author tries to argue that penetration of Artificial Intelligence into the Judiciary could surely be enhancive and reparative, if not fully transformative.

Keywords: artificial intelligence, judicial decision making, judicial systems, legal services delivery

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Authors: Jaydip M. Desai, Antonio Valdevit, Arthur Ritter

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Robotic surgery is used to enhance minimally invasive surgical procedure. It provides greater degree of freedom for surgical tools but lacks of haptic feedback system to provide sense of touch to the surgeon. Surgical robots work on master-slave operation, where user is a master and robotic arms are the slaves. Current, surgical robots provide precise control of the surgical tools, but heavily rely on visual feedback, which sometimes cause damage to the inner organs. The goal of this research was to design and develop a real-time simulink based robotic system to study force feedback mechanism during instrument-object interaction. Setup includes three Velmex XSlide assembly (XYZ Stage) for three dimensional movement, an end effector assembly for forceps, electronic circuit for four strain gages, two Novint Falcon 3D gaming controllers, microcontroller board with linear actuators, MATLAB and Simulink toolboxes. Strain gages were calibrated using Imada Digital Force Gauge device and tested with a hard-core wire to measure instrument-object interaction in the range of 0-35N. Designed simulink model successfully acquires 3D coordinates from two Novint Falcon controllers and transfer coordinates to the XYZ stage and forceps. Simulink model also reads strain gages signal through 10-bit analog to digital converter resolution of a microcontroller assembly in real time, converts voltage into force and feedback the output signals to the Novint Falcon controller for force feedback mechanism. Experimental setup allows user to change forward kinematics algorithms to achieve the best-desired movement of the XYZ stage and forceps. This project combines haptic technology with surgical robot to provide sense of touch to the user controlling forceps through machine-computer interface.

Keywords: surgical robot, haptic feedback, MATLAB, strain gage, simulink

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Authors: Tamara Grujic, Mirjana Bonkovic

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Measurements and quantitative analysis of kinematic parameters of human hand movements have an important role in different areas such as hand function rehabilitation, modeling of multi-digits robotic hands, and the development of machine-man interfaces. In this paper the assessment and evaluation of the reach-to-grasp movement by using computerized and robot-assisted method is described. Experiment involved the measurements of hand positions of seven healthy subjects during grasping three objects of different shapes and sizes. Results showed that three dominant phases of reach-to-grasp movements could be clearly identified.

Keywords: human hand, kinematics, measurement and analysis, reach-to-grasp movement

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Authors: Shunyi Yang, Jingjing Yan, Siyu Dong, Xiangguo Cui

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Current architectural façade design practices incorporate various daylighting and solar radiation analysis methods. These emphasize the impact of geometry on façade design. There is scope to extend this knowledge into methods that address material translucency, porosity, and form. Such approaches can also achieve these conditions through adaptive robotic manufacturing approaches that exploit material dynamics within the design, and alleviate fabrication waste from molds, ultimately accelerating the autonomous manufacturing system. Besides analyzing the environmental solar radiant in building facade design, there is also a vacancy research area of how lighting effects can be precisely controlled by engaging the instant real-time data-driven robot control and manipulating the material properties. Ceramics carries a wide range of transmittance and deformation potentials for robotics control with the research of its material property. This paper presents one semi-autonomous system that engages with real-time data-driven robotics control, hardware kit design, environmental building studies, human interaction, and exploratory research and experiments. Our objectives are to investigate the relationship between different clay bodies or ceramics’ physio-material properties and their transmittance; to explore the feedback system of instant lighting data in robotic fabrication to achieve precise lighting effect; to design the sufficient end effector and robot behaviors for different stages of deformation. We experiment with architectural clay, as the material of the façade that is potentially translucent at a certain stage can respond to light. Studying the relationship between form, material properties, and porosity can help create different interior and exterior light effects and provide façade solutions for specific architectural functions. The key idea is to maximize the utilization of in-progress robotics fabrication and ceramics materiality to create a highly integrated autonomous system for lighting facade design and manufacture.

Keywords: light transmittance, data-driven fabrication, computational design, computer vision, gamification for manufacturing

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Authors: Dohun Kim

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Technological innovations have stimulated flipped learning in many disciplines, including language teaching. It is a specific type of blended learning, which combines onsite (i.e. face-to-face) with online experiences to produce effective, efficient and flexible learning. Flipped learning literally ‘flips’ conventional teaching and learning activities upside down: it leverages technologies to deliver a lecture and direct instruction—other asynchronous activities as well—outside the classroom to reserve onsite time for interaction and activities in the upper cognitive realms: applying, analysing, evaluating and creating. Unlike the conventional flipped approaches, which focused on video lecture, followed by face-to-face or on-site session, new innovative methods incorporate various means and structures to serve the needs of different academic disciplines and classrooms. In the light of such innovations, this study adopted ‘student-engaged’ approaches to interpreter training and contrasts them with traditional classrooms. To this end, students were also encouraged to engage in asynchronous activities online, and innovative technologies, such as Telepresence, were employed. Based on the class implementation, a thorough examination was conducted to examine how we can structure and implement flipped classrooms for language and interpreting training while actively engaging learners. This study adopted a quantitative research method, while complementing it with a qualitative one. The key findings suggest that the significance of the instructor’s role does not dwindle, but his/her role changes to a moderator and a facilitator. Second, we can apply flipped learning to both theory- and practice-oriented modules. Third, students’ integration into the community of inquiry is of significant importance to foster active and higher-order learning. Fourth, cognitive presence and competence can be enhanced through strengthened and integrated teaching and social presences. Well-orchestrated teaching presence stimulates students to find out the problems and voices the convergences and divergences, while fluid social presence facilitates the exchanges of knowledge and the adjustment of solutions, which eventually contributes to consolidating cognitive presence—a key ingredient that enables the application and testing of the solutions and reflection thereon.

Keywords: blended learning, Community of Inquiry, flipped learning, interpreter training, student-centred learning

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