• IEMEK Journal of Embedded Systems and Applications
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• v.12 no.1
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• pp.1-10
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• 2017

Recently, with the ever-increasing complexity of industrial robot systems, it has been greatly attention to adopt a multi-core based motion controller with high cost-performance ratio. In this paper, we propose a software architecture that aims to utilize the computing power of multi-core processors. The key concept of our architecture is to use shared memory for the interplay between threads running on separate processor cores. And then, we have integrated our proposed architecture with an industrial standard compliant IDE for automatic code generation of motion runtime. For the performance evaluation, we constructed a test-bed consisting of a motion controller with Preempt-RT Linux based dual-core industrial PC and a 3-axis industrial robot platform. The experimental results show that the actuation time difference between axes is 10 ns in average and bounded up to 689 ns under $1000{\mu}s$ control period, which can come up with real-time performance for industrial robot.

• IEMEK Journal of Embedded Systems and Applications
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• v.16 no.4
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• pp.137-143
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• 2021

We propose an adaptive non-singular terminal sliding-mode control for the fast finite-time convergence (FANTSMC) in robot manipulator. The proposed FANTSMC approach is developed to be applied without singularity in robot manipulator, which has a new pole-placement control with the non-singular terminal sliding variable while generating the desirable control torque. Moreover, the switching gain is designed to suppress the time-delayed estimation error appropriately, which aims at providing the high robust tracking performance. Also, the proposed one employs one-sample delayed information to cancel out the system uncertainties and disturbances. For these reasons, it offers strong attraction within the finite time. It is shown that the tracking performance of the proposed FANTSMC approach is guaranteed to be uniformly ultimately bounded through the Lyapunov stability. The effectiveness of the proposed FANTSMC approach is illustrated in simulations, which is compared with that of the up-to-date control approach.

• IEMEK Journal of Embedded Systems and Applications
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• v.19 no.4
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• pp.175-184
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• 2024

This research addresses the problem of robot localization in corridor environments using LiDAR (Light Detection and Ranging). Due to the rank deficiency problem in scan matching with LiDAR alone, the accuracy of robot localization may degenerate seriously. This paper proposes an adaptive sampling-based particle filtering method using depth sensors to overcome the rank deficiency problem. The increase in the sample size in particle filters can be considered to solve the problem. But, it may cause much computation cost. In the proposed method, the sample size of the particle set in the proposed method is adjusted adaptively to the confidence of depth sensor data. The performance of the proposed method was test by real experiments in various environments. The experimental results showed that the proposed method was capable of reducing the estimation errors and more accurate than the conventional method.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.7
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• pp.697-703
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• 2011

This article describes a snake robot with 2-DOF actuator modules. The 2-DOF actuator modules make the snake robot move in the 3D space so that the snake robot can cross obstacles and rough terrain. Each 2-DOF actuator module is designed to have high torque output and an embedded controller. A cross bracket connecting the modules is designed be able to support the weight of two actuator modules. The developed snake robot shows 3-D motions such as side winding, standing/monitoring, and can climb in a narrow pipe with high torque modules. The snake robot moves fast with passive wheels in a plane while crossing obstacles.

• The Journal of Korea Robotics Society
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• v.12 no.3
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• pp.356-364
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• 2017

This paper presents a force control based on the observer without taking any force or torque measurement from the robot which allows realizing more stable and robust human robot interaction for the developed multi-functional upper limb rehabilitation robot. The robot has four functional training modes which can be classified by the human robot interaction types: passive, active, assistive, and resistive mode. The proposed observer consists of internal disturbance observer and external force observer for distinctive performance evaluation. Since four training modes can be quantitatively identified as impedance variation, position-based impedance control with feedback and feedforward controller was applied to the assistive training mode. The results showed that the proposed sensorless observer estimated cleaner and more accurate force compared to the force sensor and the impedance controller embedded with the proposed observer completed the assistive training mode safely and properly.

• Journal of the Ergonomics Society of Korea
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• v.21 no.2
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• pp.101-111
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• 2002

An intelligent robot, which has been developed recently, is no more a conventional robot widely known as an industrial robot. It is a computer system embedded in a machine and utilizes the machine as a medium not only for the communication between the human and the computer but also for the physical interaction among the human, the computer and their environment. Recent advances in computer technology have made it possible to create several of new types of human-computer interaction which are realized by utilizing intelligent machines. There is a continuing need for better understanding of how to design human/robot interface(HRI) to make for a more natural and efficient flow of information and feedback between robot systems and their users in both directions. In this paper, we explain the concept and the scope of HRI and review the current research trends of domestic and foreign HRL. The recommended research directions in the near future are also discussed based upon a comparative study of domestic and foreign HRI technology.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.256-261
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• 2005

In this research, we propose a path-planning algorithm for an autonomous mobile robot using geographical information, under the condition that the robot moves in unknown environment. All image inputted by camera at every sampling time are analyzed and geographical elements are recognized, and the geographical information is embedded in environmental map. The geographical information was transformed into 1-dimensional evaluation value that expressed the difficulty of movement for the robot. The robot goes toward the goal searching for path that minimizes the evaluation value at every sampling time. Then, the path is updated by integrating the exploited information and the prediction on unexploited environment. We used a sensor fusion method for improving the mobile robot dead reckoning accuracy. The experiment results that confirm the effectiveness of the proposed algorithm on the robot's reaching the goal successfully using geographical information are presented.

• International Journal of Safety
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• v.7 no.1
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• pp.1-4
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• 2008

Application of the Microsoft robotics studio (MSRS) to the design of a factory safety monitoring robot is presented. Basic structures of the MSRS and the service are introduced. The service is the key building block of the MSRS. Control of the safety monitoring robot is performed using four basic services: 1) the robot service which communicates with the embedded micro-processor and other services, 2) the sensor service that notifies the subscribing services of the change of the sensor value, 3) the motor service which controls the power levels to the motors, 4) the drive service which maneuvers the robot. With built-in capabilities of the MSRS, control of factory safety monitoring robot can be more easily performed.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.1097-1098
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• 2008

In this paper We are going experiment which can happen at the movement of the robot to reduce the Systematic distance error. The system get the experiment result by using BLDC Motor, Encoder, ultrasonic sensor. The Embedded XP is adopted as an operating system, And The robot was controlled by using RS232.

• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.765-766
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• 2006

The ecology of Physically Embedded Intelligent Systems (PEIS) is a new multi robotic framework conceived by integrating insights from the fields of autonomous robotics and ambient intelligence. A PEIS-Ecology is a network of intelligent robotic devices that can provide the user with assistance, information, communication, and entertainment services. In this paper we introduce the concept of PEIS Ecology, and illustrate a concrete realization of a PEIS-Ecology.