• Korean Journal of Agricultural Science
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• v.42 no.1
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• pp.63-71
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• 2015

Path planning is an essential part for traveling and mowing of autonomous lawn mower tractors. Objectives of the paper were to analyze operation patterns by a skilled farmer, to extract and optimize waypoints, and to demonstrate generation of formatted planned path for autonomous lawn mower tractors. A 27-HP mower tractor was operated by a skilled farmer on grass fields. To measure tractor travel and operation characteristics, an RTK-GPS antenna with a 6-cm RMS error, an inertia motion sensing unit, a gyro compass, a wheel angle sensor, and a mower on/off sensor were mounted on the mower tractor, and all the data were collected at a 10-Hz rate. All the sensor data were transferred through a software program to show the status immediately on the notebook. Planned path was generated using the program parameter settings, mileage and time calculations, and the travel path was plotted using developed software. Based on the human operation patterns, path planning algorithm was suggested for autonomous mower tractor. Finally path generation was demonstrated in a formatted file and graphic display. After optimizing the path planning, a decrease in distance about 13% and saving of the working time about 30% was achieved. Field test data showed some overlap, especially in the turning areas. Results of the study would be useful to implement an autonomous mower tractor, but further research needs to improve the performance.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.05a
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• pp.462-465
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• 2002

This paper deals with the problem of synthesis of stable and optimal grasps with unknown objects by 3-finger hand. Previous robot grasp research has analyzed mainly with either unknown objects 2D by vision sensor or unknown objects, cylindrical or hexahedral objects, 3D. Extending the previous work, in this paper we propose an algorithm to analyze grasp of unknown objects 3D by vision sensor. This is archived by two steps. The first step is to make a 3D geometrical model of unknown objects by stereo matching which is a kind of 3D computer vision technique. The second step is to find the optimal grasping points. In this step, we choose the 3-finger hand because it has the characteristic of multi-finger hand and is easy to modeling. To find the optimal grasping points, genetic algorithm is used and objective function minimizing admissible farce of finger tip applied to the object is formulated. The algorithm is verified by computer simulation by which an optimal grasping points of known objects with different angles are checked.

• Journal of the Korean Society for Precision Engineering
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• v.19 no.11
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• pp.54-64
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• 2002

This paper deals with the problem of synthesis of stable and optimal grasps with unknown objects by 3-finger hand. Previous robot grasp research has mainly analyzed with either unknown objects 2-dimensionally by vision sensor or known objects, such as cylindrical objects, 3-dimensionally. As extending the previous work, in this study we propose an algorithm to analyze grasp of unknown objects 3-dimensionally by using vision sensor. This is archived by two steps. The first step is to make a 3-dimensional geometrical model for unknown objects by using stereo matching. The second step is to find the optimal grasping points. In this step, we choose the 3-finger hand which has the characteristic of multi-finger hand and is easy to model. To find the optimal grasping points, genetic algorithm is employed and objective function minimizes the admissible force of finger tip applied to the objects. The algorithm is verified by computer simulation by which optimal grasping points of known objects with different angle are checked.

• The Journal of Korea Robotics Society
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• v.1 no.2
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• pp.117-124
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• 2006

In this paper, we develope the navigation system for patrol robots in indoor environment. The proposed system consists of PDA map modelling, a localization algorithm based on a global position sensor and an automatic charging station. For the practical use in security system, the PDA is used to build object map on the given indoor map. And the builded map is downloaded to the mobile robot and used in path planning. The global path planning is performed with a localization sensor and the downloaded map. As a main controller, we use PXA270 based hardware platform in which embedded linux 2.6 is developed. Data handling for various sensors and the localization algorithm are performed in the linux platform. Also, we implemented a local path planning algorithm for object avoidance with ultra sonar sensors. Finally, for the automatic charging, we use an infrared ray system and develop a docking algorithm. The navigation system is experimented with the two-wheeled mobile robot using North-Star localization system.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.9
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• pp.2173-2193
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• 2013

In order to reduce the distribution cost of sensor nodes, a mobile sensor deployment has been proposed. The mobile sensor deployment can be solved by finding the optimal layout and planning the movement of sensor nodes with minimum energy consumption. However, previous studies have not sufficiently addressed these issues with an efficient way. Therefore, we propose a new deployment approach satisfying these features, namely a tree-based approach. In the tree-based approach, we propose three matching schemes. These matching schemes match each sensor node to a vertex in a rake tree, which can be trivially transformed to the target layout. In our experiments, the tree-based approach successfully deploys the sensor nodes in the optimal layout and consumes less energy than previous works.

• Design & Manufacturing
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• v.16 no.4
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• pp.52-59
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• 2022

Currently, Korea is an aging society and is expected to become a super-aged society in about four years. X-ray devices are widely used for early diagnosis in hospitals, and many X-ray technologies are being developed. The development of X-ray device technology is important, but it is also important to increase the reliability of the device through accurate data management. Sensor nodes such as temperature, voltage, and current of the diagnosis device may malfunction or transmit inaccurate data due to various causes such as failure or power outage. Therefore, in this study, the temperature, tube voltage, and tube current data related to each sensor and detection circuit of the diagnostic X-ray imaging device were measured and analyzed. Based on QC data, device failure prediction and diagnosis algorithms were designed and performed. The fault diagnosis algorithm can configure a simulator capable of setting user parameter values, displaying sensor output graphs, and displaying signs of sensor abnormalities, and can check the detection results when each sensor is operating normally and when the sensor is abnormal. It is judged that efficient device management and diagnosis is possible because it monitors abnormal data values (temperature, voltage, current) in real time and automatically diagnoses failures by feeding back the abnormal values detected at each stage. Although this algorithm cannot predict all failures related to temperature, voltage, and current of diagnostic X-ray imaging devices, it can detect temperature rise, bouncing values, device physical limits, input/output values, and radiation-related anomalies. exposure. If a value exceeding the maximum variation value of each data occurs, it is judged that it will be possible to check and respond in preparation for device failure. If a device's sensor fails, unexpected accidents may occur, increasing costs and risks, and regular maintenance cannot cope with all errors or failures. Therefore, since real-time maintenance through continuous data monitoring is possible, reliability improvement, maintenance cost reduction, and efficient management of equipment are expected to be possible.

• The Journal of the Korea institute of electronic communication sciences
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• v.6 no.1
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• pp.148-156
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• 2011

This paper presents an implementation of autonomous navigation of a mobile robot indoors. It explains methods for map building, localization, obstacle avoidance and path planning. Geometric map is used for localization and path planning. The localization method calculates sensor data based on the map for comparison with the real sensor data. Monte Carlo Localization(MCL) method is adopted for estimation of the robot position. For obstacle avoidance, an artificial potential field generates repulsive and attractive force to the robot. Dijkstra algorithm plans the shortest distance path from a start position to a goal point. The methods integrate into autonomous navigation method and implemented for indoor navigation. The experiments show that the proposed method works well for safe autonomous navigation.

• International Journal of Aeronautical and Space Sciences
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• v.11 no.4
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• pp.326-337
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• 2010

This work addresses problems regarding trajectory planning for unmanned aerial vehicle sensors. Such sensors are used for taking measurements of large nonlinear systems. The sensor investigations presented here entails methods for improving estimations and predictions of large nonlinear systems. Thoroughly understanding the global system state typically requires probabilistic state estimation. Thus, in order to meet this requirement, the goal is to find trajectories such that the measurements along each trajectory minimize the expected error of the predicted state of the system. The considerable nonlinearity of the dynamics governing these systems necessitates the use of computationally costly Monte-Carlo estimation techniques, which are needed to update the state distribution over time. This computational burden renders planning to be infeasible since the search process must calculate the covariance of the posterior state estimate for each candidate path. To resolve this challenge, this work proposes to replace the computationally intensive numerical prediction process with an approximate covariance dynamics model learned using a nonlinear time-series regression. The use of autoregressive time-series featuring a regularized least squares algorithm facilitates the learning of accurate and efficient parametric models. The learned covariance dynamics are demonstrated to outperform other approximation strategies, such as linearization and partial ensemble propagation, when used for trajectory optimization, in terms of accuracy and speed, with examples of simplified weather forecasting.

• Proceedings of the KIEE Conference
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• 2003.11b
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• pp.11-14
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• 2003

In this paper, we use Fuzzy Logic and Potential field method for optimal path planning of an autonomous mobile robot and apply to navigation for real-time mobile robot in 2D dynamic environment. For safe navigation of the robot, we use both Global and Local path planning. Global path planning is computed off-line using sell-decomposition and Dijkstra algorithm and Local path planning is computed on-line with sensor information using potential field method and Fuzzy Logic. We can get gravitation between two feature points and repulsive force between obstacle and robot through potential field. It is described as a summation of the result of repulsive force between obstacle and robot which is considered as an input through Fuzzy Logic and gravitation to a feature point. With this force, the robot fan get to desired target point safely and fast avoiding obstacles. We Implemented the proposed algorithm with Pioneer-DXE robot in this paper.

• Journal of the Institute of Convergence Signal Processing
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• v.8 no.1
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• pp.78-83
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• 2007

Robot collects surrounding information to recognize tile unknown environment by using various sensors such as visual, infrared ray and ultra sonic sensors. Although visual sensor is the most popular one, it has some difficulties in collecting data in dark or too bright environment due to sensitivity of the light. It also requests significant amount of calculation on collecting data from certain images with marked, straight and curved ones. As an alternative, ultra sonic sensor can simply overcome this visual sensing system's flaw and easily be used. It is easier than visual system, especially in case of collecting data on object and distance in dark environment. Ultra sonic sensor can replace the expensive visual sensing system not only in avoiding obstacles but also in reaching to the target area smoothly. The purpose of this paper is to develop the algorithm to optimize the environmental recognition, path planning and free-ranging by minimizing errors caused by inaccurate information and by considering characteristics of the ultra sonic rays such as refraction and diffusion. This paper also realizes the system that can recognize the environment and make the appropriate path planning by applying the algorithm on this moving robot.