• 제어로봇시스템학회:학술대회논문집
• /
• 1986.10a
• /
• pp.337-340
• /
• 1986

A software package CARDS for general purpose robot design, control, and simulation has been developed and is presented here. CARDS (Computer Aided Robot Design and Simulation) consists of a collection of standardized subroutine modules that carry out typical kineamatic, dynamic, and control computations so that the user only needs to write a main program that further defines a particular robot configuration and the task to be performed. It provides users a complete simulation environment, so that it will be a valuable engineering tool for mechanical designers as well as electric control designers.

• 제어로봇시스템학회:학술대회논문집
• /
• 1987.10b
• /
• pp.105-108
• /
• 1987

In this paper, a new algorithm is proposed to obtain important corner and real corner points of the simple objects and the visual robot graphics simulation using the results is studied. This is capable of performing as a debugging tool for task programming of a visual robot. And the robot motion is also simulated on a CRT terminal.

• Journal of Institute of Control, Robotics and Systems
• /
• v.9 no.4
• /
• pp.304-309
• /
• 2003

Uninterrupted power supply has become indispensable during the maintenance task of active electric power lines as a result of today's highly information-oriented society and increasing demand of electric utilities. The maintenance task has the risk of electric shock and the danger of falling from high place. Therefore it is necessary to realize an autonomous robot system. In order to realize these tasks autonomously, the three dimensional position of target object such as electric line and the stand of insulator must be recognized accurately and rapidly. The approaching of an insulator and the wrenching of a nut task is selected as the typical task of the maintenance of active electric power distribution lines in this paper. Image recognition by multilayer neural network and optimal target position calculation method are newly proposed in order to recognize the center 3 dimensional position of the bolt hole in the stand of insulator. By the proposed image recognition method, it is proved that the center 3 dimensional position of the bolt hole can be recognized rapidly and accurately without regard to the pose of the stand of insulator. Finally the approaching and wrenching task is automatically realized using 6-link electro-hydraulic manipulators.

• Journal of the Korean Society for Precision Engineering
• /
• v.17 no.9
• /
• pp.181-188
• /
• 2000

This paper deals with an analysis of the compliance characteristic for effective peg-in-hole task using robot hand without inter-finger coupling. We first observe the fact that some of coupling stiffness elements cannot be planned arbitrary. next we classify the task of inserting a peg-in-a-hole into two contact styles between the peg and the hole. Then we analyze the conditions of the specified stiffness matrix in the operational space to successfully and more effectively achieve the give peg-in-hole task for each case. It is concluded that the location of compliance center on the peg and the coupling stiffness element existing between the translational and the rotational direction play important roles for successful peg-in-hole task. Simulation results are included to verify the feasibility of the analytic results.

• The Journal of Korea Robotics Society
• /
• v.16 no.4
• /
• pp.299-305
• /
• 2021

In this study, the task of robotic tidy-up is to clean the current environment up exactly like a target image. To perform a tidy-up task using a robot, it is necessary to estimate the pose of various objects and to classify the objects. Pose estimation requires the CAD model of an object, but these models of most objects in daily life are not available. Therefore, this study proposes an algorithm that uses point cloud and PCA to estimate the pose of objects without the help of CAD models in cluttered environments. In addition, objects are usually detected using a deep learning-based object detection. However, this method has a limitation in that only the learned objects can be recognized, and it may take a long time to learn. This study proposes an image matching based on few-shot learning and Siamese network. It was shown from experiments that the proposed method can be effectively applied to the robotic tidy-up system, which showed a success rate of 85% in the tidy-up task.

• The Journal of Korea Robotics Society
• /
• v.10 no.1
• /
• pp.42-51
• /
• 2015

Peg-in-hole assembly is the most representative task for a robot to perform under contact conditions. Various strategies for accomplishing the peg-in-hole task with a robot exist, but the existing strategies are not sufficiently practical to be used for various assembly tasks in a human environment because they require additional sensors or exclusive tools. In this paper, the peg-in-hole assembly experiment is performed with anthropomorphic hand arm robot without extra sensors or devices using "intuitive peg-in-hole strategy". From this work, the probability of applying the peg-in-hole strategy to a common assembly task is verified.

• 제어로봇시스템학회:학술대회논문집
• /
• 1996.10b
• /
• pp.503-506
• /
• 1996

An integrated Robot control system for SCARA robot is developed. The system consists of an off-line programming(OLP), software and a robot controller using four digital signal processor(TMS32OC50). The OLP has functions of teaching task, dynamic simulator, three dimensional animation, and trajectory planning. To develop robust dynamic control algorithm, a new sliding mode control algorithm for the robot is proposed. The trajectory tracking performance of these algorithm is evaluated by implementing to SCARA robot(SM5 type) using DSP controller which has conventional PI-FF control algorithm. To make SCARA robot operate according to off-line teaching, an interface between OLP and robot controller in the integrated system is designed. To demonstrate performance of the integrated system, the proposed control algorithm is applied to the system.

• Proceedings of the Korean Operations and Management Science Society Conference
• /
• 1995.04a
• /
• pp.869-879
• /
• 1995

The new field of learning control develops controllers that learn to improve their performance at executing a given task, based on experience performing this task. The simplest forms of learning control are based on the same concept as integral control, but operating in the domain of the repetitions of the task. In the previous paper, I had studied the use of such controllers in a decentralized system, such as a robot with the controller for each link acting independently. The basic result of the paper is to show that stability of the learning controllers for all subsystems when the coupling between subsystems is turned off, assures stability of the decentralized learning in the coupled system, provided that the sample time in the digital learning controller is sufficiently short. In this paper, we present two examples. The first illustrates the effect of coupling between subsystems in the system dynamics, and the second studies the application of decentralized learning control to robot problems. The latter example illustrates the application of decentralized learning control to nonlinear systems, and also studies the effect of the coupling between subsystems introduced in the input matrix by the discretization of the system equations. The conclusion is that for sufficiently small learning gain, and sufficiently small sample time, the simple learning control law based on integral control applied to each robot axis will produce zero tracking error in spite o the dynamic coupling in the robot equations. Of course, the results of this paper have much more general application than just to the robotics tracking problem. Convergence in decentralized systems is seen to depend only on the input and output matrices, provided the sample time is suffiently small.

• KIPS Transactions on Software and Data Engineering
• /
• v.8 no.12
• /
• pp.499-506
• /
• 2019

An intelligent robot should decide its behavior accordingly to the dynamic changes in the environment and user's requirements by evaluating options to choose the best one for the current situation. Many intelligent robot systems that use the Procedural Reasoning System (PRS) accomplishes such task management functions by defining the priority functions in the task model and evaluating the priority functions of the applicable tasks in the current situation. The priority functions, however, are defined locally inside of the plan, which exhibits limitation for the tasks for multi-domain services because global contexts for overall prioritization are hard to be expressed in the local priority functions. Furthermore, since the prioritization functions are not defined as an explicit module, reuse or extension of the them for general context is limited. In order to remove such limitations, we propose a policy-based meta-planning for general task management for multi-domain services, which provides the ability to explicitly define the utility of a task in the meta-planning process and thus the ability to evaluate task priorities for general context combining the modular priority functions. The ontological specification of the model also enhances the scalability of the policy model. In the experiments, adaptive behavior of a robot according to the policy model are confirmed by observing the appropriate tasks are selected in dynamic service environments.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.8 no.4
• /
• pp.8-17
• /
• 1998

Autonomous mobile robot agents(AMRAs) are robots which perform a given task by the same distributed self-organizing rules. In this paper, we let them form an equi-distance circle for the task of cooperative behaviors. Here, we suggest an algorithm to perform the taqk and then utilize a fuzzy system to improve the algorithm. It is shown that various cooperative activities appear in the simulation and particularly chaotic behaviors also appear by increasing the robot speed. Moreover, we prove the characteristics of this chaotic behaviors by calculating Lyapunov exponent.