• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1115-1120
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• 2003

The present paper shows the possible development of particle swarm optimization (PSO) based fuzzy-neural networks (FNN) which can be employed as an important building block in real life robot systems, controlled by voice-based commands. The PSO is employed to train the FNNs which can accurately output the crisp control signals for the robot systems, based on fuzzy linguistic spoken language commands, issued by an user. The FNN is also trained to capture the user spoken directive in the context of the present performance of the robot system. Hidden Markov Model (HMM) based automatic speech recognizers are developed, as part of the entire system, so that the system can identify important user directives from the running utterances. The system is successfully employed in a real life situation for motion control of a redundant manipulator.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10b
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• pp.479-484
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• 1992

The resolved motion rate control (RMRC) is converting to Joint space trajectory from given Cartesian space trajectory. The RMRC requires the inverse of Jacobian matrix. Since the Jacobian matrix of the redundant robot is generally not square, the pseudo-inverse must be introduced. However the pseudo-inverse is not easy to be implemented on a digital computer in real time as well as mathematically complex. In this paper, a simple fuzzy resolved motion rate control (FRMRC) that can replace the RMRC using pseudo-inverse of Jacobian is proposed. The proposed FRMRC with appropriate fuzzy rules, membership functions and reasoning method can solve the mapping problem between the spaces without complexity. The mapped Joint space trajectory is sufficiently accurate so that it can be directly used to control redundant manipulators. Simulation results verify the efficiency of the proposed idea.

• The Journal of Korea Robotics Society
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• v.1 no.1
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• pp.81-88
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• 2006

Control of a robot manipulator in contact with the environment is usually conducted by the direct feedback control using a force-torque sensor or the indirect impedance control. In these methods, however, the control algorithms become complicated and the performance of position and force control cannot be improved because of the mechanical properties of the passive components. To cope with such problems, redundant actuation has been used to enhance the performance of position control and force control. In this research, a Double Actuator Unit (DAU) is proposed, with which the force control algorithm can be simplified and can make the robot ensure the safety during the external collision. The DAU is composed of two actuators; one controls the position and the other modulates the joint stiffness. Using this unit, it is possible to independently control the position and stiffness. The DAU based on the planetary gears is investigated in this paper. Performance using the DAU is also verified by various experiments. It is shown that the manipulator using this mechanism provides better safety during the impact with the environment by reducing the joint stiffness appropriately on detecting the collision of a manipulator.

• Transactions of the Korean Society of Mechanical Engineers
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• v.17 no.2
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• pp.267-276
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• 1993

This paper discusses the neural network application in the study on the obstacle avoidance of robot manipulator during the trajectory planning. The collision problem of two robot manipulators which are simultaneously moving in the same workspace is investigated. Instead of the traditional modeling method, this paper processing based on the calculation of joint angle in the cartesian coordinate with constrained condition shows the possibility of real time control. The problem of the falling into the local minima is cleared by the adaptive weight factor control using the temperature adding method. Computer simulations are shown for the verification.

• The Journal of Korea Robotics Society
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• v.12 no.4
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• pp.441-447
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• 2017

Robot arms are being increasingly used in various fields with special attention given to unmanned systems. In this research, we developed a high payload dual-arm robot, in which the forearm module is replaceable to meet the assigned task, such as object handling or lifting humans in a rescue operation. With each forearm module specialized for an assigned task (e.g. safety for rescue and redundant joints for object handling task), the robot can conduct various tasks more effectively than could be done previously. In this paper, the design of the high payload dual-arm robot with replaceable forearm function is described in detail. Two forearms are developed here. Each of forearm has quite a different goal. One of the forearms is specialized for human rescue in human familiar flat aspect and compliance parts. Other is for general heavy objects, more than 30 kg, handling with high degree of freedom more than 7.

• Journal of Institute of Control, Robotics and Systems
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• v.5 no.8
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• pp.955-960
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• 1999

This paper describes the effect of impact configurations on a single robot manipulator. The effect of different configurations of kinematically redundant arms on impact forces at their end effectors during contact with the environment is investigated. Instead of the well-known impact ellipsoid, I propose an analytic method on the geometric configuration of the impact directly from the mathematical definition. By calculating the length along the specified motion direction and volume of the geometry, we can determine the characteristics of robot configurations in terms of both the impact along the specified direction and the ability of the robot withstanding the impact. Simulations of various impact configurations are discussed at the end of this paper.

• Journal of the Korean Society for Precision Engineering
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• v.10 no.4
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• pp.200-205
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• 1993

In many applications, the typical parallel-jaw end-effector of a robot arm has been remarkably satisfactory. But, it is not adequate for the applications such as complicated manipulation. In the study, a finger with 4 joints (so, having redundancy) was consturcted to investigate the characteristics of an articulated hand. Each joint was driven by one actuator, and the motor torque was transmited to each joint through a tendon-pulley system. In the context, major considerations for hardware design and the method to solve the inverse kinematics of a redundant manipulator were presented. Finally, the basic capabilities of an articulated hand were presented through experiments.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.15 no.4
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• pp.295-300
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• 1990

Inverse kinematic problem is a crucial point for robot manipulator control. In this paper, to implement the Jacobian control technique we used the Hopfield, Tank's neural network. The states of neurons represent joint velocities, and the connection weights are determined from the current value of the Jacobian matirx. The network energy function is constructed so that its minimum corresponds to the minimum least square error. At each sampling time, connection weights and neuron states are updated according to current joint positon. Inverse kinematic solution to the planar redundant manipulator is solved by computer simulation.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.3
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• pp.298-308
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• 2000

In this paper a new two-arm cooperative assembly(or insertion) algorithm is proposed. As a force-guided control method for the cooperative assembly the adaptive accommodation controller is adopted since it does not require any complicated contact state analysis nor depends of the geometrical complexity of the assembly parts. Also the RMRC(resolved motion rate control) method using a relative jacobian is used to solve inverse kinematics for two manipulators. By using the relative jacobian the two cooperative redundant manipulators can be formed as a new single redundant manipulator. Two arms can perform a variety of insertion tasks by using a relative motion between their end effectors. A force/torque sensing model using an approximated penetration depth calculation a, is developed and used to compute a contact force/torque in the graphic assembly simulation . By using the adaptive accommodation controller and the force/torque sensing model both planar and a spatial cooperative assembly tasks have been successfully executed in the graphic simulation. Finally through a cooperative assembly task experiment using a humanoid robot CENTAUR which inserts a spatially bent pin into a hole its feasibility and applicability of the proposed algorithm verified.

• Journal of the Ergonomics Society of Korea
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• v.12 no.1
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• pp.17-24
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• 1993

Today, rapid development and timeliness of introducing a new product be- comes a more influencing factor of determing its competitive power due to a shortened product cycle, while rapid improvement of manufacturing technology makes product design and manufacturing fuse together. This implies that prod- uct usability evaluation and improvement starts right from its design phase, resulting in less development time and cost. To make this possible, proper as- sessment of human reach is one of essential functions for ergonomic product us- ability evaluation, specifically in the platform of computer-aided ergonomic evaluation models or any CAD system with a built-in man model. In this study, an analytic reach prediction algorithm ensuring the posture that human naturally takes, is presented by employing the methods developed for robot kinematics. Among robot kinematic methods for solving the multi-link system, the resolved motion method was found to be effective to solve human reach as a redundant manipulator model. Also, the joint range availability was used as a performance fonction to guarantee human naturalness. The result is expected to be directly applicable to product usability evaluations.