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Robotics, IEEE Transactions on

Issue 4 • Date Aug. 2013

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Displaying Results 1 - 25 of 25
  • Table of Contents

    Page(s): C1
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  • IEEE Transactions on Robotics publication information

    Page(s): C2
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  • Learning UAV Stability and Control Derivatives Using Gaussian Processes

    Page(s): 813 - 824
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (961 KB) |  | HTML iconHTML  

    The stability and control derivatives of an unmanned aerial vehicle (UAV) map the platform's control inputs to its dynamic response. The modeling is labor intensive and requires coarse approximations. Similarly, models constructed through flight tests are only applicable to a narrow flight envelope, and classical system identification approaches require prior knowledge of the model structure, which, in some instances, may only be partially known. The goal of this study is to tackle these problems by introducing a new system identification method based on the dependent Gaussian processes. This allows high-fidelity nonlinear flight dynamic models to be constructed through experimental data. The proposed algorithm captures the cross coupling between input parameters and learns the system stability and control derivatives. In addition, it captures any dependences embodied in the outputs. This paper provides both the theoretical underpinnings and practical application of this approach. The theory was tested in simulation on a highly coupled oblique wing aircraft and was demonstrated on a delta-wing UAV platform using real flight data. The results are compared against an alternative parameteric model and show improvements in identifying the coupling between flight modes, the ability to provide uncertainty estimates and robustness, and applicability to a broader flight envelope. View full abstract»

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  • Mapping Synergies From Human to Robotic Hands With Dissimilar Kinematics: An Approach in the Object Domain

    Page(s): 825 - 837
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    One of the major limitations to the use of advanced robotic hands in industries is the complexity of the control system design due to the large number of motors needed to actuate their degrees of freedom. It is our belief that the development of a unified control framework for robotic hands will allow us to extend the use of these devices in many areas. Borrowing the terminology from software engineering, there is a need for middleware solutions to control the robotic hands independently from their specific kinematics and focus only on the manipulation tasks. To simplify and generalize the control of robotic hands, we take inspiration from studies in neuroscience concerning the sensorimotor organization of the human hand. These studies demonstrated that, notwithstanding the complexity of the hand, a few variables are able to account for most of the variance in the patterns of configurations and movements. The reduced set of parameters that humans effectively use to control their hands, which are known in the literature as synergies, can represent the set of words for the unified control language of robotic hands, provided that we solve the problem of mapping human hand synergies to actions of the robotic hands. In this study, we propose a mapping designed in the manipulated object domain in order to ensure a high level of generality with respect to the many dissimilar kinematics of robotic hands. The role of the object is played by a virtual sphere, whose radius and center position change dynamically, and the role of the human hand is played by a hand model referred to as “paradigmatic hand,” which is able to capture the idea of synergies in human hands. View full abstract»

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  • Rehabilitation Exoskeleton Design: Exploring the Effect of the Anterior Lunge Degree of Freedom

    Page(s): 838 - 846
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1155 KB) |  | HTML iconHTML  

    As our robotics community advances its understanding toward the optimal design of robotic exoskeletons for human gait training, the question we ask in this paper is how the anterior lunge degree of freedom in the robotic exoskeleton affects human gait training. Answering this question requires both novel robotic design and novel protocols for human gait training to characterize this effect. To the best of the authors' knowledge, this is the first study to characterize the effect of an exoskeleton's degrees of freedom on human gait adaptation. We explored this question using the Active Leg EXoskeleton (ALEX) II. The study presented was performed using ALEX II under the following two configurations: 1) locking the anterior/posterior translation in the exoskeleton, while allowing other degrees-of-freedom (labeled as locked mode) and 2) keeping the anterior/posterior degree of freedom unlocked (labeled as unlocked mode). Healthy subjects walked at self-selected speeds on a treadmill and were trained to walk with a new gait template, scaled down from their normal template. While both groups showed adaptation and retention over a 26-min period following training, the unlocked group showed better performance in terms of adaptation and retention compared with the locked group. View full abstract»

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  • Transferring Human Impedance Behavior to Heterogeneous Variable Impedance Actuators

    Page(s): 847 - 862
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    This paper presents a comparative study of approaches to control robots with variable impedance actuators (VIAs) in ways that imitate the behavior of humans. We focus on problems where impedance modulation strategies are recorded from human demonstrators for transfer to robotic systems with differing levels of heterogeneity, both in terms of the dynamics and actuation. We categorize three classes of approach that may be applied to this problem, namely, 1) direct, 2) feature-based, and 3) inverse optimal approaches to transfer. While the first is restricted to highly biomorphic plants, the latter two are shown to be sufficiently general to be applied to various VIAs in a way that is independent of the mechanical design. As instantiations of such transfer schemes, 1) a constraint-based method and 2) an apprenticeship learning framework are proposed, and their suitability to different problems in robotic imitation, in terms of efficiency, ease of use, and task performance, is characterized. The approaches are compared in simulation on systems of varying complexity, and robotic experiments are reported for transfer of behavior from human electromyographic data to two different variable passive compliance robotic devices. View full abstract»

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  • Large-Payload Climbing in Complex Vertical Environments Using Thermoplastic Adhesive Bonds

    Page(s): 863 - 874
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    Despite many approaches proposed in the past, robotic climbing in a complex vertical environment is still a big challenge. We present here an alternative climbing technology that is based on thermoplastic adhesive (TPA) bonds. The approach has a great advantage because of its large payload capacity and viability to a wide range of flat surfaces and complex vertical terrains. The large payload capacity comes from a physical process of thermal bonding, while the wide applicability benefits from rheological properties of TPAs at higher temperatures and intermolecular forces between TPAs and adherends when being cooled down. A particular type of TPA has been used in combination with two robotic platforms, featuring different foot designs, including heating/cooling methods and construction of footpads. Various experiments have been conducted to quantitatively assess different aspects of the approach. Results show that an exceptionally high ratio of 500% between dynamic payloads and body mass can be achieved for stable and repeatable vertical climbing on flat surfaces at a low speed. Assessments on four types of typical complex vertical terrains with a measure, i.e., terrain shape index ranging from -0.114 to 0.167, return a universal success rate of 80%-100%. View full abstract»

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  • Slip-Turn for Biped Robots

    Page(s): 875 - 887
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    This paper presents a method for generating a turning motion in a humanoid robot by allowing the feet of the robot to slip on the ground. As humans, we exploit the fact that our feet can slip on the ground, and allowing humanoid robots to realize this same motion is a worthwhile study. In this paper, we propose the hypothesis that a turning motion is caused by the effect of minimizing the power generated by floor friction. A model of rotation from this friction is then described based on our hypothesis. The proposed model suggests that only the trajectory and shape of the robot's feet determine the amount of rotation from a slip, and that the friction coefficient between the floor and the soles of the robot, as well as the velocity of the feet, do not affect the resultant angle. Verification is conducted through an experiment with a humanoid robot known as HRP-2. Next, to obtain the foot motion necessary to realize the desired rotational angle, the inverse problem is solved by confining the trajectory of the center of the foot to an arc shape. This solution is verified through an experiment with another humanoid robot, HRP-4C. View full abstract»

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  • Planning Singularity-Free Paths on Closed-Chain Manipulators

    Page(s): 888 - 898
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1734 KB) |  | HTML iconHTML  

    This paper provides an algorithm for computing singularity-free paths on closed-chain manipulators. Given two nonsingular configurations of the manipulator, the method attempts to connect them through a path that maintains a minimum clearance with respect to the singularity locus at all points, which guarantees the controllability of the manipulator everywhere along the path. The method can be applied to nonredundant manipulators of general architecture, and it is resolution complete. It always returns a path whenever one exists at a given resolution or determines path nonexistence otherwise. The strategy relies on defining a smooth manifold that maintains a one-to-one correspondence with the singularity-free C-space of the manipulator, and on using a higher dimensional continuation technique to explore this manifold systematically from one configuration, until the second configuration is found. If desired, the method can also be used to compute an exhaustive atlas of the whole singularity-free component reachable from a given configuration, which is useful to rapidly resolve subsequent planning queries within such component, or to visualize the singularity-free workspace of any of the manipulator coordinates. Examples are included that demonstrate the performance of the method on illustrative situations. View full abstract»

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  • Reciprocal Collision Avoidance With Motion Continuity Constraints

    Page(s): 899 - 912
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    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (718 KB) |  | HTML iconHTML  

    This paper addresses decentralized motion planning among a homogeneous set of feedback-controlled, decision-making agents. It introduces the continuous control obstacle ( Cn-CO), which describes the set of Cn-continuous control sequences (and thus trajectories) that lead to a collision between interacting agents. By selecting a feasible trajectory from Cn-CO's complement, a collision-free motion is obtained. The approach represents an extension to the reciprocal velocity obstacle (RVO, ORCA) collision-avoidance methods so that trajectory segments verify Cn continuity rather than piecewise linearity. This allows the large class of robots capable of tracking Cn-continuous trajectories to employ it for partial motion planning directly-rather than as a mere tool for collision checking. This paper further establishes that both the original velocity obstacle method and several of its recently developed reciprocal extensions (which treat specific robot physiologies only) correspond to particular instances of Cn-CO. In addition to the described extension in trajectory continuity, Cn-CO thus represents a unification of existing RVO theory. Finally, the presented method is validated in simulation-and a parameter study reveals under which environmental and control conditions Cn-CO with admits significantly improved navigation performance compared with inflated approaches based on ORCA. View full abstract»

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  • Contingency Planning Over Probabilistic Obstacle Predictions for Autonomous Road Vehicles

    Page(s): 913 - 929
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2836 KB) |  | HTML iconHTML  

    This paper presents a novel optimization-based path planner that is capable of planning multiple contingency paths to directly account for uncertainties in the future trajectories of dynamic obstacles. This planner addresses the particular problem of probabilistic collision avoidance for autonomous road vehicles that are required to safely interact, in close proximity, with other vehicles with unknown intentions. The presented path planner utilizes an efficient spline-based trajectory representation and fast but accurate collision probability bounds to simultaneously optimize multiple continuous contingency paths in real time. These collision probability bounds are efficient enough for real-time evaluation, yet accurate enough to allow for practical close-proximity driving behaviors such as passing an obstacle vehicle in an adjacent lane. An obstacle trajectory clustering algorithm is also presented to enable the path planner to scale to multiple-obstacle scenarios. Simulation results show that the contingency planner allows for a more aggressive driving style than planning a single path without compromising the overall safety of the robot. View full abstract»

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  • Constrained Interaction and Coordination in Proximity-Limited Multiagent Systems

    Page(s): 930 - 944
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (790 KB) |  | HTML iconHTML  

    In this paper, we consider the problem of controlling the interactions of a group of mobile agents, subject to a set of topological constraints. Assuming proximity-limited interagent communication, we leverage mobility, unlike prior work, to enable adjacent agents to interact discriminatively, i.e., to actively retain or reject communication links on the basis of constraint satisfaction. Specifically, we propose a distributed scheme that consists of hybrid controllers with discrete switching for link discrimination, coupled with attractive and repulsive potentials fields for mobility control, where constraint violation predicates form the basis for discernment. We analyze the application of constrained interaction to two canonical coordination objectives, i.e., aggregation and dispersion, with maximum and minimum node degree constraints, respectively. For each task, we propose predicates and control potentials, and examine the dynamical properties of the resulting hybrid systems. Simulation results demonstrate the correctness of our proposed methods and the ability of our framework to generate topology-aware coordinated behavior. View full abstract»

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  • Underwater Reflex Navigation in Confined Environment Based on Electric Sense

    Page(s): 945 - 956
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    This paper shows how a sensor inspired by an electric fish could be used to help navigate in confined environments. Exploiting the morphology of the sensor, the physics of electric interactions, as well as taking inspiration from passive electrolocation in real fish, a set of reactive control laws encoding simple behaviors, such as avoiding any electrically contrasted object, or seeking a set of objects while avoiding others according to their electric properties, is proposed. These reflex behaviors are illustrated on simulations and experiments carried out on a setup dedicated to the study of electric sense. The approach does not require a model of the environment and is quite cheap to implement. View full abstract»

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  • Decentralized Extended Information Filter for Single-Beacon Cooperative Acoustic Navigation: Theory and Experiments

    Page(s): 957 - 974
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    We report a decentralized extended information filter (DEIF) algorithm designed for single-beacon cooperative acoustic navigation of one or more client underwater vehicles. In single-beacon cooperative acoustic navigation, ranges and state information from a single reference source (the server) are used to improve localization and navigation of an underwater vehicle (the client). The ranges and state information are obtained using underwater acoustic modems and a synchronous-clock time-of-flight paradigm. Apart from the server's acoustic data broadcasts, the client has no access to the server's position or sensor measurements. We show that at the instance of each range measurement update, the DEIF algorithm yields identical results for the current vehicle state estimate as the corresponding centralized extended information filter (CEIF), which fully tracks the joint probability distribution between the server and client. We compare the state estimation results of the DEIF algorithm with that of a CEIF and three other filters reported in the literature. The evaluation is performed using both simulated data and an experimental dataset comprised of one surface craft and two autonomous underwater vehicles. View full abstract»

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  • Active Visual Planning for Mobile Robot Teams Using Hierarchical POMDPs

    Page(s): 975 - 985
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    Key challenges to widespread deployment of mobile robots include collaboration and the ability to tailor sensing and information processing to the task at hand. Partially observable Markov decision processes (POMDPs), which are an instance of probabilistic sequential decision-making, can be used to address these challenges in domains characterized by partial observability and nondeterministic action outcomes. However, such formulations tend to be computationally intractable for domains that have large complex state spaces and require robots to respond to dynamic changes. This paper presents a hierarchical decomposition of POMDPs that incorporates adaptive observation functions, constrained convolutional policies, and automatic belief propagation, enabling robots to retain capabilities for different tasks, direct sensing to relevant locations, and determine the sequence of sensing and processing algorithms best suited to any given task. A communication layer is added to the POMDP hierarchy for belief sharing and collaboration in a team of robots. All algorithms are evaluated in simulation and on physical robots, localizing target objects in dynamic indoor domains. View full abstract»

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  • Active Visual Object Search in Unknown Environments Using Uncertain Semantics

    Page(s): 986 - 1002
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    In this paper, we study the problem of active visual search (AVS) in large, unknown, or partially known environments. We argue that by making use of uncertain semantics of the environment, a robot tasked with finding an object can devise efficient search strategies that can locate everyday objects at the scale of an entire building floor, which is previously unknown to the robot. To realize this, we present a probabilistic model of the search environment, which allows for prioritizing the search effort to those parts of the environment that are most promising for a specific object type. Further, we describe a method for reasoning about the unexplored part of the environment for goal-directed exploration with the purpose of object search. We demonstrate the validity of our approach by comparing it with two other search systems in terms of search trajectory length and time. First, we implement a greedy coverage-based search strategy that is found in previous work. Second, we let human participants search for objects as an alternative comparison for our method. Our results show that AVS strategies that exploit uncertain semantics of the environment are a very promising idea, and our method pushes the state-of-the-art forward in AVS. View full abstract»

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  • Intensity-Based Ultrasound Visual Servoing: Modeling and Validation With 2-D and 3-D Probes

    Page(s): 1003 - 1015
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    In this paper, we present an ultrasound (US) visual servoing to control a robotic system equipped with a US probe. To avoid the difficult and time-consuming image segmentation process, we develop a new approach taking as visual input directly the intensity of the image pixels. The analytic form of the interaction matrix that relates the variation of the intensity features to the motion of the probe is established and used to control the six degrees of freedom (dof) of the robotic system. Our approach is applied with a 2-D and a 3-D US probe, and the results that are obtained with both sensors are compared in simulation. The 2-D probe shows good performances for tracking tasks and the 3-D one, which ensures a larger domain of convergence, is more particularly used for positioning tasks. The intensity-based approach is validated through experimental results performed with a realistic abdominal phantom and with animal soft tissue. View full abstract»

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  • On 3-D Motion Estimation From Feature Tracks in 2-D FS Sonar Video

    Page(s): 1016 - 1030
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (13113 KB) |  | HTML iconHTML  

    Visual odometry involves the computation of 3-D motion and (or) trajectory by tracking features in the video or image sequences recorded by the camera(s) on some autonomous terrestrial, aerial, and marine robotics platform. For exploration, mapping, inspection, and surveillance operations within turbid waters, high-frequency 2-D forward-scan sonar systems offer a significant advantage over cameras by providing both imagery with target details and attractive tradeoff in range, resolution, and data rate. Operating these at grazing incidence gives larger scene coverage and improved image quality due to the dominance of diffuse backscattered reflectance but induces cast shadows that are typically more distinct than brightness patterns due to the direct reflectance of casting objects. For the computation of 3-D motion by automatic video processing, the estimation accuracy and robustness can be enhanced by integrating the visual cues from shadow dynamics with the image flow of stationary 3-D objects, both induced by sonar motion. In this paper, we present the mathematical models of image flow for 3-D objects and their cast shadows, utilize them in devising various 3-D sonar motion estimation solutions, and study their robustness. We present results of experiments with both synthetic and real data in order to assess the accuracy and performance of these methods. View full abstract»

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  • A Novel Layer Jamming Mechanism With Tunable Stiffness Capability for Minimally Invasive Surgery

    Page(s): 1031 - 1042
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    This paper presents a novel “layer jamming” mechanism that can achieve variable stiffness. The layer jamming mechanism exploits the friction present between layers of thin material, which can be controlled by a confining pressure. Due to the mechanism's hollow geometry, compact size, and light weight, it is well suited for various minimally invasive surgery applications, where stiffness change is required. This paper describes the concept, the mathematical model, and a tubular snake-like manipulator prototype. Various characteristics of layer jamming, such as stiffness and yield strength, are studied both theoretically and experimentally. View full abstract»

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  • A Spatial Weight Error Control for a Class of Hyper-Redundant Robots

    Page(s): 1043 - 1050
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (663 KB) |  | HTML iconHTML  

    This paper treats the control problem of a class of hyper-redundant robots. The dynamic model of the arm is described by hyperbolic partial differential equations with uncertain components. By using a spatial weighted error control, the infinite dimensional system control becomes a finite-dimensional control problem. The stability analysis and the resulting controllers are obtained using the concept of boundary geometric control and a spatial weighted error control technique. A robust algorithm that is based on weighted error sliding mode control is discussed. The boundary tendon control determines the system evolution toward a prescribed switching surface, and in order to avoid the oscillations around the switching surface, a damping control determines a direct evolution, along the switching surface, toward the origin. Numerical simulations and experimental results are also provided to verify the effectiveness of the presented approach. View full abstract»

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  • Planning Reliable Paths With Pose SLAM

    Page(s): 1050 - 1059
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    The maps that are built by standard feature-based simultaneous localization and mapping (SLAM) methods cannot be directly used to compute paths for navigation, unless enriched with obstacle or traversability information, with the consequent increase in complexity. Here, we propose a method that directly uses the Pose SLAM graph of constraints to determine the path between two robot configurations with lowest accumulated pose uncertainty, i.e., the most reliable path to the goal. The method shows improved navigation results when compared with standard path-planning strategies over both datasets and real-world experiments. View full abstract»

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  • Adaptive Controller and Observer for a Magnetic Microrobot

    Page(s): 1060 - 1067
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    This paper discusses the control design of a magnetically guided microrobotic system in blood vessels to perform minimally invasive medical procedures. Such microrobots consist of a polymer-bonded aggregate of nanosized ferromagnetic particles and a possible payload that can be propelled by the gradient coils of a magnetic device. A fine modeling is developed and used to define an optimal trajectory which minimizes the control efforts. We then synthesize an adaptive backstepping law that ensures a Lyapunov stable and fine tracking, despite modeling errors, and estimates some key uncertain parameters. As the controller synthesis uses the microrobot unmeasured velocity, the design of a high-gain observer is also addressed. Simulations and experiment illustrate the robustness to both noise measurement and some uncertain physiological parameters for a 250-μm radius microrobot that navigates in a fluidic environment. View full abstract»

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  • Open Access

    Page(s): 1068
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  • IEEE Robotics and Automation Society Information

    Page(s): C3
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  • IEEE Transactions on Robotics information for authors

    Page(s): C4
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Aims & Scope

IEEE Transactions on Robotics covers both theory and applications on topics including: kinematics, dynamics, control, and simulation of robots and intelligent machines and systems.

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Meet Our Editors

Editor-in-Chief
Frank Park
Seoul National University