Won Suk You

Global localization for a small mobile robot using magnetic patterns

In this paper, we present a global localization and local pose error compensation method in a known structured environment using magnetic landmarks. In previous our research, it was possible to compensate the pose error (xe, ye, qe) of a mobile robot correctly on the surface of structured environment with magnetic landmarks. In this work, we propose a methodology of arranging magnetic landmarks on the map such that properly arranged magnetic patterns ease the global localization of a mobile agent. Among total six patterns of magnetic-bar in square arrangement, five unique landmarks are obtained. Therefore, a heuristic pattern search method is applied to build the virtual map using five landmarks. In order to obtain the global pose information, the robot identifies the pattern of magnets, and obtains the current global pose information by comparing the measured neighboring patterns with the map information that is saved in advance. Experimental results show the effectiveness of the magnetic-pattern landmarks for the global localization and local pose control of a mobile robot.

Development of robotic laboratory automation platform with intelligent mobile agents for clinical chemistry

In this research, we propose an innovative robotic platform for clinical tests suitable for small or medium sized laboratories using small-sized multiple mobile robots and a robotic arm. The proposed robotic platform is referred to as “BioRobot platform”. The BioRobot platform not only provides flexibility in test process by carrying out various clinical tests simultaneously through multiple mobile agents, but also increases productivity by having controllable throughput according to amount of tests. Therefore, the various algorithms which are related to robotic technologies have been applied in this platform to operate the entire hardware and several mobile agents simultaneously. To evaluate the performance of the BioRobot platform, various control methods are implemented, which provides parallel processing and scalability. The feasibility of the BioRobot platform with three mobile robotic agents is validated through preliminary experiments.

Robotic laboratory automation platform based on mobile agents for flexible clinical tests

In this research, we propose an innovative robotic platform for clinical tests suitable for small or medium sized laboratories. The proposed robotic platform, called “BioRobot platform”, is composed of multiple mobile agents which deliver microplates from one site to another in the platform, a miniature robotic arm, microplate loaders, photometry scanner or other testing devices, and an incubator where mobile agents reside depending on various tests. The BioRobot platform not only provides flexibility in tests by carrying out various clinical tests simultaneously through multiple mobile agents, but also increases productivity by having controllable throughput according to amount of tests. Also, to minimizes the delay time and provides parallel processing, the novel reduced idle time scheduling algorithm is implemented in the platform. The performance of the BioRobot platform is experimentally tested and its feasibility is validated.

Exploration and reconstruction of unknown object by active touch of robot hand

This paper proposes a method of exploring the global shape of an unknown object using information on local geometric features. In the first, we introduce a rolling and sliding motion of a fingertip with a force/torque sensor to estimate an unknown local curvature. Also, a recognition algorithm for local geometry using normal curvature equations is presented, which are composed of principal curvatures and principal direction. Finally, to reconstruct the global shape of the object, we propose an interpolation method using principal curvatures at contact points. The proposed method is verified using a hand-arm system consisting of an industrial robot arm and an anthropomorphic robot hand with a 6-axis force/torque sensor. The effectiveness of the proposed method is experimentally validated for different type of objects.

Point-of-Care Test Equipment for Flexible Laboratory Automation

Blood tests are some of the core clinical laboratory tests for diagnosing patients. In hospitals, an automated process called total laboratory automation, which relies on a set of sophisticated equipment, is normally adopted for blood tests. Noting that the total laboratory automation system typically requires a large footprint and significant amount of power, slim and easy-to-move blood test equipment is necessary for specific demands such as emergency departments or small-size local clinics. In this article, we present a point-of-care test system that can provide flexibility and portability with low cost. First, the system components, including a reagent tray, dispensing module, microfluidic disk rotor, and photometry scanner, and their functions are explained. Then, a scheduler algorithm to provide a point-of-care test platform with an efficient test schedule to reduce test time is introduced. Finally, the results of diagnostic tests are presented to evaluate the system.

Localization Using Magnetic Patterns for Autonomous Mobile Robot

In this paper, we present a method of localization using magnetic landmarks. With this method, it is possible to compensate the pose error (x e , y e , θ e ) of a mobile robot correctly and localize its current position on a global coordinate system on the surface of a structured environment with magnetic landmarks. A set of four magnetic bars forms total six different patterns of landmarks and these patterns can be read by the mobile robot with magnetic hall sensors. A sequential motion strategy for a mobile robot is proposed to find the geometric center of magnetic landmarks by reading the nonlinear magnetic field. The mobile robot first moves into the center region of the landmark where it can read the magnetic pattern, after which tracking and global localization can be easily achieved by recognizing the patterns of neighboring landmarks. Experimental results show the effectiveness of the sequential motion strategy for estimating the center of the first encountered landmark as well as the performance of tracking and global localization of the proposed system.

Design of anthropomorphic robot hand with IMC joints

This paper presents a novel anthropomorphic robot hand with IMC joints. IMC joints are applied to robot hand to grasp various objects regardless of the size and get large overlapped workspace between thumb and other fingers, which allow all the fingertips to be located on a single spot in a wide range. Desinged IMC joints of robot hand are always rotated with 1:1 ratio by mechanical constraint using passive tendon. Actuation module consists of miniature BLDC motor and ballscrew drives two IMC joints with a single motor. To evaluate the advantages of robot hand with IMC joints, grasping experiments are performed.

Design of backdrivable soft robotic finger mechanism

This paper presents a new joint actuation mechanism, called Active DIP-PIP (ADP) joint, for robotic finger. The mechanism consists of a pair of moveable pulleys and springs to generate both linked and adjustable motion. While the set of DIP (Distal-Interphalangeal) and PIP (Proximal-Interphalangeal) joint shows coupled movement in free space, it moves adaptively when it contacts with an object. The torsion springs attached on each joints ensure 1:1 ratio movement while finger is moving freely and produce additional joint torque while grasping an object. In addition, actuation module composed of miniature BLDC motor and ball screw allows each joint to be back drivable.

Kinematic design optimization of improved branched tendon mechanism using genetic algorithm

This paper presents the improved branched tendon mechanism by including additional design parameters to the original branched tendon design, and a kinematic design optimization technique for this mechanism using genetic algorithm. The significance of additional design parameters and the feature of improved branched tendon mechanism are also explained. Unlike traditional joint pulley-tendon mechanism that always has the same length of moment arm, the improved branched tendon mechanism uses special tendon which is divided into two just before it is attached to the remote link. By optimizing these divided two different lengthes of tendons and other design parameters, creating various moment arm on a single joint with respect to the flexion angle of joint and limiting maximum moment arm to ensure all the tendons to be inside of the fingers outer frame are possible at the same time. Total 12 variables, 4 given and 8 independent, are used to represent the mechanism mathematically and the objective function is defined to maximize the moment arm throughout the flexion of the joint while not exceeding joint radius. Optimizing the kinematic model of improved branched tendon mechanism with genetic algorithm, it is possible to minimize the loss of the moment arm to 311% throughout the flexion. Meanwhile, overall actuation mechanism becomes much simple than traditional joint pulley-tendon mechanism.

Force/torque sensor calibration method by using deep-learning

The force/torque sensor is an important tool that gives a robot an ability to interact with their usage environments. Calibration is essential for these force/torque sensors to convert the raw sensor values to accurate forces and torques. However, in practice, the multi-axis force/torque sensor requires complex multi-step data processing, because of the coupling effects and nonlinearity of sensors. Moreover, accuracy is not guaranteed. To solve this problem, we propose an accurate force/torque sensor calibration method that can calibrate the sensor in single step by using deep-learning algorithm, and introduce the method for modeling the DNN(deep neural network) used in this calibration process. In addition, we also explain some tricks for learning, and then verify the calibration results through several experiments.