• 제어로봇시스템학회:학술대회논문집
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• 1992.10a
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• pp.19-24
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• 1992

Real-time mobile robot controllers usually have been designed with an emphasis on control theory ignoring the importance of system integration. This paper demonstrates that useful mobile robots require a real time controller with a wide range of capabilities in addition to control theory. These capabilities include: path-planning, position estimation, path tracking control and wheel control. An architectural framework supporting these capabilities has been designed and implemented. Using this frame work, individual modules such as a path planner, a path tracking controller, position estimators, wheel controllers and other cruical elements have been successfully integrated into the control system for the LCAR robot which was developed as a proto-type mobile robot in our laboratory. The context of the research, the architecture, its implementation and performance results from experiments are discussed.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10b
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• pp.130-134
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• 1992

The ability of a robot system to comply to an environment via the control of tool-environment interaction force is of vital for the successful task accomplishment in many robot application. This paper presents the implementation of external force control for two dimensional contour following task using a commercial robot system. Force accommodation is used since a constraint imposed in our work is not to modify the commercial robot system. A linear, decoupled model of two dimensional contour following system in the discrete time domain is derived first. Then the experimental verification of linear control is obtained using a PUMA 560 manipulator with standard Unimation controller, Astek FS6-120A six axis wrist force sensor attached externally to the arm and LSI-11173 microcomputer. Experimentally obtained data shows that the RMS contact force error is 0.8246 N when following the straight edge and 2.3768 N when following 40 mm radius curved contour.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10b
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• pp.564-568
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• 1992

A neural optimization network is designed to solve the collsion-free inverse kinematics problem for redundant robot manipulators under the constraints of joint limits, maximum velocities and maximum accelerations. And the fuzzy rules are proposed to determine the weightings of neural optimization networks to avoid the collision between robot manipulator and obstacles. The inputs of fuzzy rules are the resultant distance, change of the distance and sum of the changes. And the output of fuzzy rules is defined as the capability of collision avoidance of joint differential motion. The weightings of neural optimization networks are adjusted according to the capability of collision avoidance of each joint. To show the validities of the proposed method computer simulation results are illustrated for the redundant robot with three degrees of freedom,

• 제어로봇시스템학회:학술대회논문집
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• 1992.10b
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• pp.468-472
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• 1992

In recent years, lots of researches on autonomous mobile robot have been accomplished. However they focused on environment recognition and its processing to make a decision on the motion, And cooperative multi-robot, which must be able to avoid crash and to make mutual communication, has not been studied much. This paper deals with cooperative motion of two robots, 'Meari 1" and "Meari 2 " made in our laboratory, based on communication between the two. Because there is an interference on communication occurring in cooperative motion of multi-robot, many restrictive conditions are required. Therefore, we have designed these robot system so that communication between them is available and mutual interference is precluded, and we used fuzzy interference to overcome unstability of sensor data.of sensor data.

• 제어로봇시스템학회:학술대회논문집
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• 1990.10b
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• pp.1087-1092
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• 1990

This paper describes the development and control of a quadruped walking robot, named as KAISER-II. The control system with multiprocessor based hierachical structure is developed. In order to navigate autonomously on a rough terrain, an identification algorithm for robot's position is proposed using 3-D vision and guide-mark pattern Also, a simple attitude control algorithm is included using force sensors. Through experimental results, it is shown that the robot can not only walk statically on even terrain but also cross over or go through the artificially made obstacles such as stairs, horizontal bar and tunnel-typed one.

• 제어로봇시스템학회:학술대회논문집
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• 1990.10b
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• pp.907-912
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• 1990

An approach to robot force control, which allows force manipulations to be realized without overshot and overdamping while in the presence of unknown environment, is given in this paper. The main idea is to use dynamic compensation for known robot parts and fuzzy compensation for unknown environment so as to improve system performance. The fuzzy compensation is implemented by using rule based fuzzy approach to identify unknown environment. The establishment of proposed control system consists of following two stages. First, similar to the resolved acceleration control method, dynamic compensation and PID control based on known robot dynamics, kinematics and estimated environment compliance is introduced. To avoid overshoot the whole control system is constructed overdamped. In the second stage, the unknown environment stiffness is estimated by using fuzzy reasoning, where the fuzzy estimation rules are obtained priori as the expression of the relationship between environment stiffness and system response. Based on simulation result, comparisons between cases with or without fuzzy identifications are given, which illustrate the improvement achieved.

• 제어로봇시스템학회:학술대회논문집
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• 1990.10b
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• pp.980-984
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• 1990

In order to find the optimal control law for the precise trajectory tracking of a robot manipulator, a perturbational control method is proposed based on a linearized manipulator dynamic model which can be obtained in a very compact and computationally efficient manner using the dual number algebra. Manipulator control can be decomposed into two parts: the nominal control and the corrective perturbational control. The nominal control is precomputed from the inverse dynamic model using the quantities of a desired trajectory. The perturbational control is obtained by applying the second-variational method on the linearized dynamic model. Simulation results for a PUMA-560 robot show that, by using this controller, the desired trajectory tracking performance of the robot can be achieved, even in the presence of large initial positional disturbances.

• 제어로봇시스템학회:학술대회논문집
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• 1990.10b
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• pp.985-989
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• 1990

This paper presents a fundamental study of a millimeter-sized master-slave robot driven by conduit-guided wires, which is expected to be applied to the delicate surgical operations, the assembling precise and small parts and so on. This system consists of a millimeter-sized slave robot and a master manipulator of which the size is adapted to a human finger. Displacement and torque of the master side can be reduced and transferred to the slave robot by controlling the motor torque against the master torque by feeding back tension signals. The master can feel the tensions by the motor torque. In this paper, the design method and making process of the master-slave system and the dynamical characteristic of displacement and torque control are proposed.

• 제어로봇시스템학회:학술대회논문집
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• 1990.10a
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• pp.269-274
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• 1990

Usually, robot manipulators in production lines are operated with reperting work trajectories. This paper presents the repeated adaptive learning algorithm for robot manipulates for the case of a trajectory. This algorithm uses the nonlinear dynamic model including the repeated friction compensating term, The advantage of the scheme is that It allows friction compensation which may be otherwise difficult for differently constructed models. A secondary advantage of the sheme is that it can also adapt to torque calculation in order to reduce the computational load of the control computer. To show the efficiency of the proposed controller, a computer simulation is performed for the planar robot manipulator with a 2 degree of freedom.

• IEMEK Journal of Embedded Systems and Applications
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• v.9 no.2
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• pp.101-107
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• 2014

Mobile robots use an environment map of its workspace to complete the surveillance task. However grid-based maps that are commonly used map format for mobile robot navigation use a large size of memory for accurate representation of environment. In this reason, grid-based maps are not suitable for path planning of mobile robots using embedded board. In this paper, we present the path planning algorithm that produce a secure path rapidly. The proposed approach utilizes a hybrid map that uses less memory than grid map and has same efficiency of a topological map. Experimental results show that the fast path planning uses only 1.5% of the time that a grid map based path planning requires. And the results show a secure path for mobile robot.