• Journal of Drive and Control
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• v.17 no.3
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• pp.33-46
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• 2020

We introduce a piece of special-purpose equipment for responding to disasters that has a dual-arm manipulator consisting of six-axis multi joints, and a master-slave operating system controlled by a wearable joystick for intuitive and convenient operation. However, due to the complexity and diversity of a disaster environment, training and suitable training means are needed to improve the interaction between the driver and equipment. Therefore, in this paper, a system that can improve the operator's immersion in the training simulation is proposes, this system is implemented in a virtual environment. The implemented system consists of a cabin installed with the master-slave operation system, a motion platform, visual and sound systems, as well as a real-time simulation device. This whole system was completed by applying various techniques such as a statistical mapping method, inverse kinematics, and a real-time physical model. Then, the implemented system was evaluated from a point of view of the appropriateness of the mapping method, inverse kinematics, the feasibility for real-time simulations of the physical environment through some task mode.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.21 no.8
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• pp.1024-1033
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• 1997

The past several years have witnessed an ever-increasing acceptance and adoption of parallel processing, both for high performance scientific computing as well as for more general purpose applications. Furthermore with increasing needs to perform the complex flow calculations in an efficient manner, the use of the message passing model on distributed networks has emerged as an important alternative to the expensive supercomputers. This work attempts to provide a generic framework to enable the parallelization of all CFD-related works using the master-slave model. This framework consists of (1) input geometry, (2) domain decomposition, (3) grid generation, (4) flow computations, (5) flow visualization, and (6) output display as the sequential components, but performs computations for (2) to (5) in parallel on the workstation clustering. The flow computations are parallized by having multiple copies of the flow-code to solve a PDE on different spatial regions on different processors, while their flow data are exchanged across the region boundaries, and the solution is time-stepped. The Parallel Virtual Machine (PVM) is used for distributed communication in this work.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.5
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• pp.602-608
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• 2011

In this study, a method of designing a neurointerface using neural network (NN) is proposed for controlling nonholonomic mobile robots. According to the concept of virtual master-slave robots, in particular, a partially stable inverse dynamic model of the master robot is acquired online through the NN by applying a feedback-error learning method, in which the feedback controller is assumed to be based on a PD compensator for such a nonholonomic robot. The NN for the online feedback-error learning can composed that the input layer consists of six units for the inputs $x_i$, i=1~6, the hidden layer consists of two hidden units for hidden outputs $o_j$, j=1~2, and the output layer consists of two units for the outputs ${\tau}_k$, k=1~2. A tracking control problem is demonstrated by some simulations for a nonholonomic mobile robot with two-independent driving wheels. The initial q value was set to [0, 5, ${\pi}$].