• 제어로봇시스템학회:학술대회논문집
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• 1988.10b
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• pp.973-980
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• 1988

This two-part paper presents a control method that allows for stable interaction of a robot manipulator with the environment. In part 1, we focus on the input ouput relationships (unstructured modeling) of the robot and environment dynamics. This analysis leads to a general condition for stability of the robot and environment taken as a whole. This stability condition, for stable maneuver, prescribes a finite sensitivity for robot and environment where sensitivity of the robot(or the environment) is defined as a mapping forces into displacement. According to this stability condition, smaller sensitivity either in robot or in environment leads to narrower stability range. In the limit, when both systems have zero sensitivity, stability cannot be guaranteed. These models do not have any particular structure, yet they can model a wide variety of industrial and research robot manipulators and environment dynamic behavior. Although this approach of modeling may not lead to any design procedure, it will allow us to understand the fundamental issues in stability when a robot interacts with an environment.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.38 no.11
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• pp.941-949
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• 1989

This two-part paper presents a control method that allows for stable interaction of a robot manipulator with environment. In part 1, we focus on the input output relationships (unstructured modeling) of the robot and environment dynamics. This analysis leads to a general condition for stability of the robot and environment taken as a whole. This stability condition, for stable maneuver, prescribes a finite sensitivity for robot and environment where sensitivity of the robot (or the environment) is defined as a mapping forces into displacement. According to this stability condition, smaller sensitivity either in robot or in environment leads to narrower stability range. In the limit, when both systems have zero sensitivity, stability cannot be guaranteed. These models do not have any particular structure, yet they can model a wide variety of industrial and research robot manipulators and environment dynamic behavior. Although this approach of modeling may not lead to and design procedure, it will allow us to understand the fundamental issues in stability when a robot interacts with an environment.

• Proceedings of the KIEE Conference
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• 1986.07a
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• pp.119-122
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• 1986

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.8 no.5
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• pp.76-82
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• 1999

During operating given working a robot manipulator makes some problems such as the accumulation of the error or the deviation from the command trajectory. These problems are mainly due to the disturbance noise or unmodeled system parameters. To solve these problems most of robot manipulators equip the controller. But if exact controller gains are not seleced we can't decrease the working efficiency(such as compensation about error or deviation) of the robot manipulator. So in this paper we present the controller gain tuning law by which we can find the controller gain which satisfies the per-formance specification of the robot manipulator during working of the robot. The proposed algorithm is derived from the Laypunov direct method. And by the simulation on the 4-axis SCARA type robot(SAMSUNG SM5 Robot) we guarantee the performance of this algorithm.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.28 no.5
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• pp.539-546
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• 2004

Conventional robot manipulators actuated by motors with the speed reducer such as the harmonic drive have weakness in the load capacity, since the speed reducer does not have enough strength. To overcome this, a new type of the robot actuator based on the four-bar-link mechanism driven by the ball screw was proposed and constructed. Also, a new type of a revolute-jointed robot manipulator composed of the developed actuators was developed. The base axis is actuated by the motor with the conventional speed reducer, but the other axes are actuated by the proposed actuators. The kinematics and dynamics of the robot were analyzed, and the performance test of the robot was made. Through the test results, the performance of superior load capacity versus the robot weight is shown.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.11a
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• pp.759-763
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• 1996

This paper presents a new approach to the design of neural control system using digital signal processors in order to improve the precision and robustness. Robotic manipulators have become increasingly important in the field of flexible automation. High speed and high-precision trajectory tracking are indispensable capabilities for their versatile application. The need to meet demanding control requirement in increasingly complex dynamical control systems under significant uncertainties, leads toward design of intelligent manipulation robots. The TMS320C31 is used in implementing real time neural control to provide an enhanced motion control for robotic manipulators. In this control scheme, the networks introduced are neural nets with dynamic neurons, whose dynamics are distributed over all the network nodes. The nets are trained by the distributed dynamic back propagation algorithm. The proposed neural network control scheme is simple in structure, fast in computation, and suitable for implementation of real-time control. Performance of the neural controller is illustrated by simulation and experimental results for a SCARA robot.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.2211-2216
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• 2005

This paper describes a novel navigation algorithm using a locomotion interface with two 6-DOF parallel robotic manipulators. The suggested novel navigation system can induce user's real walking and generate realistic visual feedback during navigation, using robotic manipulators. For realistic visual feedback, the virtual environment is designed with three components; 3D object modeler for buildings and terrains, scene manager and communication manager component. The walking velocity of the user is directly translated to VR actions for navigation. Finally, the functions of the RPC interface are utilized for each interaction mode. The suggested navigation system can allow a user to explore into various virtual terrains with real walking and realistic visual feedback.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.11a
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• pp.743-747
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• 1996

A Potential Field Method is applied to the proposed algorithm for the planning of collision-free paths of redundant manipulators. The planning is carried out on the base of kinematic configuration. To make repulsive potentials, sources are distributed on the boundaries of obstacles. To escape from local minimum of the main potential and to attack other difficulties of the planning, various potentials are defined simultaneously, Inverse Kinematics Problems of the redundant manipulators are solved by unconstrained optimization method. Computer simulation result of the path planning is presented.

• Journal of Korean Institute of Industrial Engineers
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• v.25 no.3
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• pp.382-392
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• 1999

Industrial robots have increased in both the number and applications in today's material handling systems. However, traditional approaches to robot controling have had limited success in complicated environment, especially for real time applications. One of the main reasons for this is that most traditional methods use a set of kinematic equations to figure out the physical environment of the robot. In this paper, a neural network model to solve robot manipulator's inverse kinematics problem is suggested. It is composed of two Self-Organizing Feature Maps by which the workspace of robot environment and the joint space of robot manipulator is inter-linked to enable the learning of the inverse kinematic relationship between workspace and joint space. The proposed model has been simulated with two robot manipulators, one, consisting of 2 links in 2-dimensional workspace and the other, consisting of 3 links in 2-dimensional workspace, and the performance has been tested by accuracy of the manipulator's positioning and the response time.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.4
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• pp.406-410
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• 2008

This paper presents a new robot calibration algorithm with joint stiffness parameters for the enhanced positioning accuracy of industrial robot manipulators. This work is towards on-going development of an industrial robot calibration software which is able to identify both the kinematic and non-kinematic robot parameters. In this paper, the conventional kinematic calibration and its important considerations are briefly described first. Then, a new robot calibration algorithm which simultaneously identifies both the kinematic and joint stiffness parameters is presented and explained through a computer simulation with a 2 DOF manipulator. Finally, the developed algorithm is implemented to Hyundai HX165 robot and its resulting improvement of the positioning accuracy is addressed.