• Industrial Engineering and Management Systems
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• v.3 no.1
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• pp.78-84
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• 2004

To optimize movement of a multi-joint robot arm is known to be a difficult problem, because it is a kind of redundant system. Although the end-effector is set its position by each angle of the joints, the angle of each joint cannot be uniquely determined by the position of the end-effector. There exist the infinite number of different sets of joint angles which represent the same position of the end-effector. This paper describes how to manage the angle of each joint to move its end-effector preferably on an X-Y plane with obstacles in the end-effector’s reachable area, and how to optimize the movement of a multi-joint robot arm, evading obstacles. The definition of “preferable” movement depends upon a purpose of robot operation. First, we divide viewpoints of preference into two, 1) the standpoint of the end-effector, and 2) the standpoint of joints. Then, we define multiple objective functions, and formulate it into a multi-objective programming problem. Finally, we solve it using multi-purpose genetic algorithm, and obtain reasonable results. The method described here is possible to add appropriate objective function if necessary for the purpose.

• The Journal of Korea Robotics Society
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• v.16 no.1
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• pp.49-55
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• 2021

Recently, a smart farm technology is drawing attention as an alternative to the decline of farm labor population problems due to the aging society. Especially, there is an increasing demand for automatic harvesting system that can be commercialized in the market. Pre-harvest crop detection is the most important issue for the harvesting robot system in a real-world environment. In this paper, we proposed a real-time tomato instance tracking algorithm by using deep learning and probability models. In general, It is hard to keep track of the same tomato instance between successive frames, because the tomato growing environment is disturbed by the change of lighting condition and a background clutter without a stochastic approach. Therefore, this work suggests that individual tomato object detection for each frame is conducted by YOLOv3 model, and the continuous instance tracking between frames is performed by Kalman filter and probability model. We have verified the performance of the proposed method, an experiment was shown a good result in real-world test data.

• Proceedings of the IEEK Conference
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• 1998.10a
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• pp.417-420
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• 1998

A heuristic sweeping algorithm for an autonomous smearing robot which executes the area filling task is proposed. This algorithm searches tracking points with the obstacle andenvironment wall while the robot tracking whole workspace, and finds sequential tracking line by sequentally connecting the tracking points in such a way that (1) the line should be never crossed, (2) the total tracking points should be is linked as short as possible, and (3) the tracking link should be cross over the obstacle in the work-space. If the line pass through the obstacle, hierarchical collision free algorithm proposed is implied. The proposed algorithm consists of (1) collision detection procedure, (2) obstacle map making procedures, (3) tracking points generation procedures for subgosls, (4) tracking points scanning procedures, and (5) obstacle avoidance procedure.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2004.04a
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• pp.241-246
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• 2004

This paper proposed trajectory tracking control of mobile robot. Trajectory tracking control scheme are real coding genetic-algorithm and back-propergation algorithm. Control scheme ability experience proposed simulation. Stable tracking control problem of mobile robots have been studied in recent years. These studios have guaranteed stability of controller, but the performance of transient state has not been guaranteed. In some situations, constant gain controller shows overshoots and oscillations. So we introduce better control scheme using Real coding Genetic Algorithm(RCGA) and neural network. Using RCGA, we can find proper gains in several situations and these gains are generalized by neural network. The generalization power of neural network will give proper gain in untrained situation. Performance of proposed controller will verify numerical simulations and the results show better performance than constant gain controller.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.1185-1188
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• 1996

In this paper we present a genetic approach for trajectory control algorithm of balancing weight for IWR biped walking robot. The biped walking robot, IWR that was made by Automatic Control Lab. of Inha University has a trunk which stabilizes its walking by generating compensation moment. Trunk is composed of a revolute and a prismatic joint which roles balancing weight. The motion of balancing weight is determined by the gait of legs and represented by two linear second order ordinary differential equations. The solution of this equation must satisfy some constraints simultaneously to have a physical meaning. Genetic algorithm search for this feasible motion of balancing weight under some constraints. Simulation results show that feasible motion of balancing weight can be obtained by genetic algorithm.

• Proceedings of the KIEE Conference
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• 2003.07d
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• pp.2504-2506
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• 2003

In this paper, we propose an algorithm for driving line-tracer robot, considered as a kind of AGV. At first, we introduce the architecture of the line-tracer robot implemented for the experiment, and explain the driving algorithm using path information from infrared sensors. The proposed algorithm can overcome the difference between each sensor's characteristics. Finally, we make some experiments and show the performance of the algorithm in case of straight path.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.12
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• pp.1233-1240
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• 2004

Recently the need for cooperative control among robots is increasing in a variety of industrial robot applications. Such a control framework enhances the efficiency of the real robotic assembly environment along with extending the robot application. In this paper, an ethernet-based cooperative control framework was proposed. The cooperative control of robots can multiply the handling capacity of robot system, and make it possible to implement jigless cooperation, due to realization of trajectory-synchronized movement between a master robot and slave robots. Coordinate transformation was used to relate among robots in a common coordinate. An optimized ethernet protocol of HiNet was developed to maximize the speed of communication and to minimize the error of synchronous movement. The proposed algorithm and optimization of network protocol was tested in several class of robots.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1601-1604
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• 1997

The most important topic in research of mobile robot is path planning in order to avoid with obstacle. In this study the path planning algorithm using a neural network model is proposed. The inputs of neural network are range data which are acquired form laser range finderm and weights are based on difference with goal direction. The thresholds are made by consdiering the marginal distance between mobile robot and obstacle. Consequently the outputs are obtained by multiplying input and weight. The obtained heading directiion enables the mobile robot to approach the goal, without any collision with obstacles around. The effectiveness of the this method of real-time navigation of a mobile robot is estimated by computer simulation in complex environment.

• Proceedings of the IEEK Conference
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• 2003.07c
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• pp.2577-2580
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• 2003

In this paper we present a teleoperation system of an internet-based mobile robot based on H.263 image compression algorithm. We control remotely the networked mobile robot with vision over the internet under unknown environments in the real time. The main feature of this system is that local operators need to download and install a client program and so they can command the robot in a remote location. Image information of remote location is compressed by H.263 video codec algorithm and then transmitted to a local operator. We constructed and tested a networked autonomous mobile robot in the real field. The experimental results show the usefulness of the robot under test.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.447-449
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• 2004

We proposed the method of the production of the humanoid biped robot and apply the A* path finding algorithm, for that robot mainly used in game and mobile robot, to avoid obstacles at real time. Actually we made the robot which has 20 DOF, 12 DOF in the two legs, 6 DOF in the two arms and each 1 DOF in the neck and waist, to realize human motions with minimal DOF, And we use the CATIA V5 for 3D modeling design and simulate.