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REFERENCE LINKING PLATFORM OF KOREA S&T JOURNALS
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IEMEK Journal of Embedded Systems and Applications
Journal Basic Information
Journal DOI :
Institute of Embedded Engineering of Korea
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Volume & Issues
Volume 3, Issue 4 - Dec 2008
Volume 3, Issue 3 - Sep 2008
Volume 3, Issue 2 - Jun 2008
Volume 3, Issue 1 - Mar 2008
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User-Oriented Controller Design for Multi-Axis Manipulators
Son, HeonSuk ; Kang, DaeHoon ; Lee, JangMyung ;
IEMEK Journal of Embedded Systems and Applications, volume 3, issue 2, 2008, Pages 49~56
This paper proposes a PC-based open architecture controller for a multi-axis robotic manipulator. The designed controller can be applied for various multi-axes robotic manipulators since the motion controller is implemented on a PC with its peripheral devices. The accuracy of the controller based on the computed torque method has been measured with the dynamic model of manipulator. Since the controller is implemented in the PC-based architecture, it is free from the user circumstances and the operating environment. Dynamics of the manipulator have been compensated by the feed forward path in the inner loop and the resulting linear outer loop has been controlled by PD algorithm. Using the specialized language, it can be more efficient in programming and in driving of the multi-axis robot. Unlike the conventional controller that is used to control only a specific robot, this controller can be easily changed for various types of robots. This paper proposes a PC-based controller that has a simple architecture with its simple interface circuits than general commercial controllers. The maintenance and the performance of the controller can be easily improved for a specific robot. In fact, using a Samsung multi-axis robot, AT1, the controller performance and convenience of the PC-based controller have been verified by comparing to the commercial one.
Robust Vision-Based Autonomous Navigation Against Environment Changes
Kim, Jungho ; Kweon, In So ;
IEMEK Journal of Embedded Systems and Applications, volume 3, issue 2, 2008, Pages 57~65
Recently many researches on intelligent robots have been studied. An intelligent robot is capable of recognizing environments or objects to autonomously perform specific tasks using sensor readings. One of fundamental problems in vision-based robot applications is to recognize where it is and to decide safe path to perform autonomous navigation. However, previous approaches only consider well-organized environments that there is no moving object and environment changes. In this paper, we introduce a novel navigation strategy to handle occlusions caused by moving objects using various computer vision techniques. Experimental results demonstrate the capability to overcome such difficulties for autonomous navigation.
Motion Control Algorithm for Crawler Type In-Pipe Robot
Bae, Ki-Man ; Lee, Sang-Ryong ; Lee, Sang-il ; Lee, Choon-Young ;
IEMEK Journal of Embedded Systems and Applications, volume 3, issue 2, 2008, Pages 66~73
The pipes have been laid underground while the industry is developing. We have to take maintenance procedure when the pipes are cracked or ruptured. It is very difficult jop to check pipe's crack because the pipes are narrow and laid underground. Using in-pipe robot, we can check the conditions of inner section of pipes, therefore, we designed a crawler type robot to search cracked pipe. In this paper, we have made a special focus on the control of the robot using differential drive algorithm to move in curved section of pipes. The detailed design of the robot with experimental result show the effectiveness of the robot in pipe maintenance.
Omnidirectional Camera System Design for a Security Robot
Kim, Kilsu ; Do, Yongtae ;
IEMEK Journal of Embedded Systems and Applications, volume 3, issue 2, 2008, Pages 74~81
This paper describes a low-cost omnidirectional camera system designed for the intruder detection capability of a security robot. Moving targets on sequential images are detected first by an adaptive background subtraction technique, and the targets are identified as intruders if they fail to enter a password within a preset time. A warning message is then sent to the owner's mobile phone. The owner can check scene pictures posted by the system on the web. The system developed worked well in experiments including a situation when the indoor lighting was suddenly changed.
Development of Biped Walking Robot with Stable Walking
Seo, Chang-Jun ;
IEMEK Journal of Embedded Systems and Applications, volume 3, issue 2, 2008, Pages 82~90
In this paper, we introduce a biped walking robot which can do static walking with 22 degree-of-freedoms. The developed biped walking robot is 480mm tall and 2500g, and is constructed by 22 RC servo motors. Before making an active algorithm, we generate the motions of robot with a motion simulator developed using C language. The two dimensional simulator is based on the inverse kinematics and D-H transform. The simulator implements various motions as we input the ankle's trajectory. Also the simulator is developed by applying the principle of inverted pendulum to acquisite the center of gravity. As we use this simulator, we can get the best appropriate angle of ankle or pelvic when the robot lifts up its one side leg during the walking. We implement the walking motions which is based on the data(angle) getting from both of simulators. The robot can be controlled by text shaped command through RF signal of wireless modem which is connected with laptop computer by serial cable.
Robot's Emotion Generation Model based on Generalized Context Input Variables with Personality and Familiarity
Kwon, Dong-Soo ; Park, Jong-Chan ; Kim, Young-Min ; Kim, Hyoung-Rock ; Song, Hyunsoo ;
IEMEK Journal of Embedded Systems and Applications, volume 3, issue 2, 2008, Pages 91~101
For a friendly interaction between human and robot, emotional interchange has recently been more important. So many researchers who are investigating the emotion generation model tried to naturalize the robot's emotional state and to improve the usability of the model for the designer of the robot. And also the various emotion generation of the robot is needed to increase the believability of the robot. So in this paper we used the hybrid emotion generation architecture, and defined the generalized context input of emotion generation model for the designer to easily implement it to the robot. And we developed the personality and loyalty model based on the psychology for various emotion generation. Robot's personality is implemented with the emotional stability from Big-Five, and loyalty is made of familiarity generation, expression, and learning procedure which are based on the human-human social relationship such as balance theory and social exchange theory. We verify this emotion generation model by implementing it to the 'user calling and scheduling' scenario.
Map Building and Localization Based on Wave Algorithm and Kalman Filter
Saitov, Dilshat ; Choi, Jeong Won ; Park, Ju Hyun ; Lee, Suk Gyu ;
IEMEK Journal of Embedded Systems and Applications, volume 3, issue 2, 2008, Pages 102~108
This paper describes a mapping and localization based on wave algorithm and Kalman filter for effective SLAM. Each robot in a multi robot system has its own task such as building a map for its local position. By combining their data into a shared map, the robot scans actively seek to verify their relative locations. For simultaneous localization the algorithm which is well known as Kalman Filter (KF) is used. For modelling the robot position we wish to know three parameters (x, y coordinates and its orientation) which can be combined into a vector called a state variable vector. The Kalman Filter is a smart way to integrate measurement data into an estimate by recognizing that measurements are noisy and that sometimes they should ignored or have only a small effect on the state estimate. In addition to an estimate of the state variable vector, the algorithm provides an estimate of the state variable vector uncertainty i.e. how confident the estimate is, given the value for the amount of error in it.
Robust Localization Algorithm for Mobile Robots in a Dynamic Environment with an Incomplete Map
Lee, Jung-Suk ; Chung, Wan Kyun ; Nam, Sang Yep ;
IEMEK Journal of Embedded Systems and Applications, volume 3, issue 2, 2008, Pages 109~118
We present a robust localization algorithm using particle filter for mobile robots in a dynamic environment. It is difficult to describe moving obstacles like people or other robots on the map and the environment is changed after mapping. A mobile robot cannot estimate its pose robustly with this incomplete map because sensor observations are corrupted by un-modeled obstacles. The proposed algorithms provide robustness in such a dynamic environment by suppressing the effect of corrupted sensor observations with a selective update or a sampling from non-corrupted window. A selective update method makes some particles keep track of the robot, not affected by the corrupted observation. In a sampling from non-corrupted window method, particles are always sampled from several particle sets which use only non-corrupted observation. The robustness of proposed algorithm is validated with experiments and simulations.
Object Tracking Algorithm of Swarm Robot System for using Polygon Based Q-Learning and Cascade SVM
Seo, Sang-Wook ; Yang, Hyung-Chang ; Sim, Kwee-Bo ;
IEMEK Journal of Embedded Systems and Applications, volume 3, issue 2, 2008, Pages 119~125
This paper presents the polygon-based Q-leaning and Cascade Support Vector Machine algorithm for object search with multiple robots. We organized an experimental environment with ten mobile robots, twenty five obstacles, and an object, and then we sent the robots to a hallway, where some obstacles were lying about, to search for a hidden object. In experiment, we used four different control methods: a random search, a fusion model with Distance-based action making (DBAM) and Area-based action making (ABAM) process to determine the next action of the robots, and hexagon-based Q-learning and dodecagon-based Q-learning and Cascade SVM to enhance the fusion model with DBAM and ABAM process.