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Publication Metadata only A monolithic opto-coupler based sensor for contact force detection in artificial hand(Ieee, 2016) N/A; N/A; Department of Mechanical Engineering; Shams, Sarmad; Lazoğlu, İsmail; PhD Student; Faculty Member; Department of Mechanical Engineering; Graduate School of Sciences and Engineering; College of Engineering; N/A; 179391This paper presents a monolithic opto-coupler based force sensor design to detect the contact forces of the fingertip of the artificial hand during grasp process. Effective and precise measurement of the contact force is always a challenge for the humid and temperature varying environment. In this paper, we propose a novel design of force sensor with optical technique. The optical technique is preferred over other techniques because of its simpler electronics and less immunity to temperature variation under humid environment. Simulation results conducted using Finite Element Method (FEM) analysis confirmed the deflection is linear for the forces from 0 to +/- 100 N. The maximum stress found at 100 N is 252.39 MPa. Also, modal analysis is performed to ensure the sensor is durable and operative while handling different vibrating objects. Calibration experiment of the sensor is performed using multipoint calibration process and curve fitting technique.Publication Metadata only A monolithic opto-coupler based sensor for contact force detection in artificial hand(Institute of Electrical and Electronics Engineers (IEEE), 2016) N/A; Department of Mechanical Engineering; Shams, Sarmad; Lazoğlu, İsmail; PhD Student; Faculty Member; Department of Mechanical Engineering; Manufacturing and Automation Research Center (MARC); Graduate School of Sciences and Engineering; College of Engineering; N/A; 179391This paper presents a monolithic opto-coupler based force sensor design to detect the contact forces of the fingertip of the artificial hand during grasp process. Effective and precise measurement of the contact force is always a challenge for the humid and temperature varying environment. In this paper, we propose a novel design of force sensor with optical technique. The optical technique is preferred over other techniques because of its simpler electronics and less immunity to temperature variation under humid environment. Simulation results conducted using Finite Element Method (FEM) analysis confirmed the deflection is linear for the forces from 0 to ±100 N. The maximum stress found at 100 N is 252.39 MPa. Also, modal analysis is performed to ensure the sensor is durable and operative while handling different vibrating objects. Calibration experiment of the sensor is performed using multipoint calibration process and curve fitting technique.Publication Metadata only A new control architecture for physical human-robot interaction based on haptic communication(Ieee, 2014) N/A; N/A; Department of Mechanical Engineering; Aydın, Yusuf; Arghavani, Nasser; Başdoğan, Çağatay; PhD Student; PhD Student; Faculty Member; Department of Mechanical Engineering; Graduate School of Sciences and Engineering; Graduate School of Sciences and Engineering; College of Engineering; 328776; N/A; 125489In the near future, humans and robots are expected to perform collaborative tasks involving physical interaction in various different environments such as homes, hospitals, and factories. One important research topic in physical Human-Robot Interaction (pHRI) is to develop tacit and natural haptic communication between the partners. Although there are already several studies in the area of Human-Robot Interaction, the number of studies investigating the physical interaction between the partners and in particular the haptic communication are limited and the interaction in such systems is still artificial when compared to natural human-human collaboration. Although the tasks involving physical interaction such as the table transportation can be planned and executed naturally and intuitively by two humans, there are unfortunately no robots in the market that can collaborate and perform the same tasks with us. In this study, we propose a new controller for the robotic partner that is designed to a) detect the intentions of the human partner through haptic channel using a fuzzy controller b) adjust its contribution to the task via a variable impedance controller and c) resolve the conflicts during the task execution by controlling the internal forces. The results of the simulations performed in Simulink/Matlab show that the proposed controller is superior to the stand-alone standard/variable impedance controllers.Publication Metadata only A realistic simulation environment for mri-based robust control of untethered magnetic robots with intra-operational imaging(IEEE-Inst Electrical Electronics Engineers Inc, 2020) Tiryaki, Mehmet Efe; Erin, Önder; N/A; Department of Mechanical Engineering; Sitti, Metin; Faculty Member; Department of Mechanical Engineering; School of Medicine; College of Engineering; 297104Dual-use of magnetic resonance imaging (MRI) devices for robot tracking and actuation has transformed them into potential medical robotics platforms for targeted therapies and minimally invasive surgeries. In this letter, we present the dynamic simulations of anMRI-based tracking and actuation scheme, which performs intra-operational imaging while controlling untethered magnetic robots. In our realistic rigid-body simulation, we show that the robot could be controlled with a 1D projection-based position feedback while performing intra-operational echo-planar imaging (EPI). From the simulations, we observe that the velocity estimation error is the main source of the controller instability for low MRI sequence frequencies. To minimize the velocity estimation errors, we constrain the controller gains according to maximum closed-loop rates achievable for different sequence durations. Using the constrained controller in simulations, we confirm that EPI imaging could be introduced to the sequence as an intra-operational imaging method. Although the intro-operational imaging increases the position estimation error to 2.0 mm for a simulated MRI-based position sensing with a 0.6 mm Gaussian noise, it does not cause controller instability up to 128 k-space lines.With the presented approach, continuous physiological images could be acquired during medical operations while a magnetic robot is actuated and tracked inside an MRI device.Publication Metadata only An adaptive admittance controller for collaborative drilling with a robot based on subtask classification via deep learning(Elsevier, 2022) Aydin, Yusuf; N/A; N/A; N/A; Department of Mechanical Engineering; Güler, Berk; Niaz, Pouya Pourakbarian; Madani, Alireza; Başdoğan, Çağatay; Master Student; Master Student; Master Student; Faculty Member; Department of Mechanical Engineering; Graduate School of Sciences and Engineering; Graduate School of Sciences and Engineering; Graduate School of Sciences and Engineering; College of Engineering; N/A; N/A; N/A; 125489In this paper, we propose a supervised learning approach based on an Artificial Neural Network (ANN) model for real-time classification of subtasks in a physical human-robot interaction (pHRI) task involving contact with a stiff environment. In this regard, we consider three subtasks for a given pHRI task: Idle, Driving, and Contact. Based on this classification, the parameters of an admittance controller that regulates the interaction between human and robot are adjusted adaptively in real time to make the robot more transparent to the operator (i.e. less resistant) during the Driving phase and more stable during the Contact phase. The Idle phase is primarily used to detect the initiation of task. Experimental results have shown that the ANN model can learn to detect the subtasks under different admittance controller conditions with an accuracy of 98% for 12 participants. Finally, we show that the admittance adaptation based on the proposed subtask classifier leads to 20% lower human effort (i.e. higher transparency) in the Driving phase and 25% lower oscillation amplitude (i.e. higher stability) during drilling in the Contact phase compared to an admittance controller with fixed parameters.Publication Metadata only Are tutor robots for everyone? the influence of attitudes, anxiety, and personality on robot-led language learning(Springer, 2022) Kumkale, G. Tarcan; Department of Psychology; Department of Psychology; Department of Psychology; N/A; Department of Psychology; Küntay, Aylin C.; Kanero, Junko; Oranç, Cansu; Koşkulu, Sümeyye; Göksun, Tilbe; Faculty Member; Researcher; Researcher; Master Student; Faculty Member; Department of Psychology; College of Social Sciences and Humanities; College of Social Sciences and Humanities; College of Social Sciences and Humanities; Graduate School of Social Sciences and Humanities; College of Social Sciences and Humanities; 178879; N/A; N/A; N/A; 47278Do some individuals benefit more from social robots than others? Using a second language (L2) vocabulary lesson as an example, this study examined how individual differences in attitudes toward robots, anxiety in learning L2, and personality traits may be related to the learning outcomes. One hundred and two native Turkish-speaking adults were taught eight English words in a one-on-one lesson either with the NAO robot (N = 51) or with a human tutor (N = 51). The results in both production and receptive language tests indicated that, following the same protocol, the two tutors are fairly comparable in teaching L2 vocabulary. Negative attitudes toward robots and anxiety in L2 learning impeded participants from learning vocabulary in the robot tutor condition whereas the personality trait of extroversion negatively predicted vocabulary learning in the human tutor condition. This study is among the first to demonstrate how individual differences can affect learning outcomes in robot-led sessions and how general attitudes toward a type of device may affect the ways humans learn using the device.Publication Metadata only BirdBot achieves energy-efficient gait with minimal control using avian-inspired leg clutching(American Association for the Advancement of Science (AAAS), 2022) Badri-Sprowitz, Alexander; Sarvestani, Alborz Aghamaleki; Daley, Monica A.; N/A; Department of Mechanical Engineering; Sitti, Metin; Faculty Member; Department of Mechanical Engineering; School of Medicine; College of Engineering; 297104Designers of legged robots are challenged with creating mechanisms that allow energy-efficient locomotion with robust and minimalistic control. Sources of high energy costs in legged robots include the rapid loading and high forces required to support the robot's mass during stance and the rapid cycling of the leg's state between stance and swing phases. Here, we demonstrate an avian-inspired robot leg design, BirdBot, that challenges the reliance on rapid feedback control for joint coordination and replaces active control with intrinsic, mechanical coupling, reminiscent of a self-engaging and disengaging clutch. A spring tendon network rapidly switches the leg's slack segments into a loadable state at touchdown, distributes load among joints, enables rapid disengagement at toe-off through elastically stored energy, and coordinates swing leg flexion. A bistable joint mediates the spring tendon network's disengagement at the end of stance, powered by stance phase leg angle progression. We show reduced knee-flexing torque to a 10th of what is required for a nonclutching, parallel-elastic leg design with the same kinematics, whereas spring-based compliance extends the leg in stance phase. These mechanisms enable bipedal locomotion with four robot actuators under feedforward control, with high energy efficiency. The robot offers a physical model demonstration of an avian-inspired, multiarticular elastic coupling mechanism that can achieve self-stable, robust, and economic legged locomotion with simple control and no sensory feedback. The proposed design is scalable, allowing the design of large legged robots. BirdBot demonstrates a mechanism for self-engaging and disengaging parallel elastic legs that are contact-triggered by the foot's own lever-arm action.Publication Metadata only Chiropractic alters TMS induced motor neuronal excitability: preliminary findings(Springer International Publishing Ag, 2014) Haavik, Heidi; Niazi, Imran Khan; Duehr, Jens; Kinget, Mat; Ugincius, Paulius; Department of Physics; N/A; Sebik, Oğuz; Yılmaz, Gizem; Türker, Kemal Sıtkı; Researcher; PhD Student; Faculty Member; Department of Physics; College of Sciences; Graduate School of Health Sciences; School of Medicine; Koç University Hospital; N/A; N/A; 6741The objective of this study was to use the electromyography (EMG) via surface and intramuscular single motor unit recordings to further characterize the immediate sensorimotor effects of spinal manipulation and a control intervention using TMS. The results provide evidence that spinal manipulation of dysfunctional spinal segments increases low threshold motoneurone excitability.Publication Metadata only Co-exploring the design space of emotional AR visualizations(Springer international Publishing ag, 2021) N/A; Department of Media and Visual Arts; Şemsioğlu, Sinem; Yantaç, Asım Evren; PhD Student; Faculty Member; Department of Media and Visual Arts; KU Arçelik Research Center for Creative Industries (KUAR) / KU Arçelik Yaratıcı Endüstriler Uygulama ve Araştırma Merkezi (KUAR); Koç Üniversitesi KARMA Gerçeklik Teknolojileri Eğitim, Uygulama ve Yayma Merkezi (KARMA) / Koç University KARMA Mixed Reality Technologies Training, Implementation and Dissemination Centre (KARMA); N/A; College of Social Sciences and Humanities; N/A; 52621Designing for emotional expression has become a popular topic of study in HCI due to advances in affective computing technologies. With increasing use of video-conferencing and video use in social media for different needs such as leisure, work, social communication, video filters, AR effects and holograms are also getting popular. in this paper, we suggest a framework for emotion visualization for natural user interface technologies such as augmented or Mixed Reality. the framework has been developed based on our analysis of visualizations formed during a series of emotion visualization workshops.Publication Metadata only Communicative cues for reach-to-grasp motions: From humans to robots(Assoc Computing Machinery, 2018) N/A; N/A; N/A; Department of Computer Engineering; Department of Computer Engineering; Kebüde, Doğancan; Eteke, Cem; Sezgin, Tevfik Metin; Akgün, Barış; Master Student; PhD Student; Faculty Member; Faculty Member; Department of Computer Engineering; Graduate School of Sciences and Engineering; Graduate School of Sciences and Engineering; College of Engineering; College of Engineering; N/A; N/A; 42946; 258784Intent communication is an important challenge in the context of human-robot interaction. The aim of this work is to identify subtle non-verbal cues that make communication among humans fluent and use them to generate intent expressive robot motion. A human human reach-to-grasp experiment (n = 14) identified two temporal and two spatial cues: (1) relative time to reach maximum hand aperture (MA), (2) overall motion duration (OT), (3) exaggeration in motion (Exg), and (4) change in grasp modality (GM). Results showed there was statistically significant difference in the temporal cues between no-intention and intention conditions. In a follow-up experiment (n = 30), reach-to-grasp motions of a simulated robot containing different cue combinations were shown to the participants. They were asked to guess the target object during robot's motion, based on the assumption that intent expressive motion would result in earlier and more accurate guesses. Results showed that, OT, GM and several cue combinations led to faster and more accurate guesses which imply they can be used to generate communicative motion. However, MA had no effect, and surprisingly Exg had a negative effect on expressiveness.