• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.44 no.7
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• pp.611-619
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• 2016

This paper proposes a collision prevention system for an agricultural unmanned helicopter. The collision prevention system consists of an obstacle detection system, a mapping algorithm, and a collision avoidance algorithm. The obstacle detection system based on a LiDAR sensor is implemented in the unmanned helicopter and acquires distance information of obstacles in real-time. Then, an obstacle mapping is carried out by combining the distance to the obstacles with attitude/location data of the unmanned helicopter. In order to prevent a collision, alert is activated to an operator based on the map when the vehicle approaches to the obstacles. Moreover, the developed collision prevention system is verified through flight test simulating a flight pattern aerial spraying.

• Journal of the Korea Institute of Military Science and Technology
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• v.16 no.2
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• pp.118-129
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• 2013

Since the obstacles and mines are of the risk factors for operating ships and submarines, the active sonar system is inevitably used to avoid the hazards in ocean environment. In this paper, modeling and simulation algorithm is used for active sonar systemto quantify the measure of mission achievability, which is known as Measure of Effectiveness(MOE), specifically for detection in this study. MOE for detection is directly formulated as a Cumulative Detection Probability(CDP) calculated from Probability of Detection(PD) in range and azimuth. The detection probability is calculated from Transmission Loss(TL) and the sonar parameters such asDirectivity Index (DI) calculated from the shape of transmitted and received array, steered beam patterns, and Reverberation Level (RL). The developed code is applied to demonstrating its applicability.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.6 no.1
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• pp.115-123
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• 2002

In this paper, we present two types of vision algorithm that mobile robot has CCD camera. for obstacle avoidance and path plan. One is simple algorithm that compare with grey level from input images. Also, The mobile robot depend on image processing and move command from PC host. we has been studied self controlled mobile robot system with CCD camera. This system consists of TMS320F240 digital signal processor, step motor, RF module and CCD camera. we used wireless RF module for movable command transmitting between robot and host PC. This robot go straight until 95 percent filled screen from input image. And the robot recognizes obstacle about 95 percent filled something, so it could avoid the obstacle and conclude new path plan. Another is complex algorithm that image preprocessing by edge detection, converting, thresholding and image processing by labeling, segmentation, pixel density calculation.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.588-591
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• 2004

In this paper, we propose a ground plane detection algorithm, using a new image processing method (IPD). To extract the ground plane from the color image acquired by monocular camera, we use a new identical pixel detection method (IPD) and an edge detection method. This IPD method decides whether the pixel is identical with the ground plane pixel or not. The IPD method needs the reference area and its performance depends on the reference area size. So we propose the reference area auto-expanding algorithm in accordance with situation. And we evaluated the proposed algorithm by the experiments in the various environments. From the experiments results, we know that the proposed algorithm is efficient in the real indoor environment.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.2337-2341
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• 2005

This paper presents the target detection method using Support Vector Machines(SVMs) and the navigation system using behavior-based fuzzy controller. SVM is a machine-learning method based on the principle of structural risk minimization, which performs well when applied to data outside the training set. We formulate detection of target objects as a supervised-learning problem and apply SVM to detect at each location in the image whether a target object is present or not. The behavior-based fuzzy controller is implemented as an individual priority behavior: the highest level behavior is target-seeking, the middle level behavior is obstacle-avoidance, the lowest level is an emergency behavior. We have implemented and tested the proposed method in our mobile robot "Pioneer2-AT". Comparing with a neural-network based detection method, a SVM illustrate the excellence of the proposed method.

• Proceedings of the IEEK Conference
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• 2009.05a
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• pp.372-374
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• 2009

In this research, an obstacle avoidance method is proposed. The common usage of a robot is indoor and the obstacles to the indoor robot is studied. The accurate detection of direction after overcoming the obstacles is necessary for performance of autonomous navigation and mission project. The sensors such as Laser, Ultrasound, PSD can be used to measure the obstacles. In this research, a PSD sensor is used to detect obstacles. It detects the height and width of obstacles located on the floor. Before measuring the obstacles, a calibration of the sensor was done and it produced a better accuracy. We have plotted an error graph using data obtained from the repeated experiments. The graph is fitted to a polynomial curve. The polynomial equation is used for the robot navigation. And in this research, a model of the error of the direction of the robot after overcoming obstacles was obtained also. The prototype of the obstacle and the error of the direction after overcoming the obstacles are modelled using a neural networks. The input of the neural network composed with the height of the obstacles, the speed of robot, the direction of wheels and the error of the direction. To implement the suggested algorithm, we set up a robot which is operated by a notebook computer. Experiment showed the suggested algorithm performed well.

• Proceedings of the KIEE Conference
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• 1998.07g
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• pp.2360-2362
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• 1998

This paper presents a new collison-free trajectory problem for SCARA robot manipulator. we use artificial potential field for collison detection and avoidance. The potential function is typically defined as the sum of attractive potential pulling the robot toward the goal configuration and a repulsive potential pushing the robot away from the obstacles. In here, end-effector of manipulator is represented as a particle in configuration space and moving obstacles is simply represented, too. we consider not fixed obstacle but moving obstacle in random. So, we propose new distance function of artificial potential field with moving obstacle for SCARA robot. At every sampling time, the artificial potential field is update and the force driving manipulator is derived from the gradient vector of artificial potential field. To real-time path planning, we apply very simple modeling to obstacle. Some simulation results show the effectiveness of the proposed approach.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.10a
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• pp.554-557
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• 2002

This paper describes power potential field method for the collision-free path planning of stereo-vision based mobile robot. Area based stereo matching is performed for obstacle detection in uncertain environment. The repulsive potential is constructed by distributing source points discretely and evenly on the boundaries of obstacles and superposing the power potential which is defined so that the source potential will have more influence on the robot than the sink potential when the robot is near to source point. The mobile robot approaches the goal point by moving the robot directly in negative gradient direction of the main potential. We have investigated the possibility of power potential method for the collision-free path planning of mobile robot through various experiments.

• Journal of Practical Engineering Education
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• v.9 no.1
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• pp.7-13
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• 2017

This study will provide a practical plan of engineering education through the study of major activities connected with the production of works to accomplish the graduation conditions by completing the comprehensive design subject and the result of the performance. The designed subject is to measure the minimum safety distance during driving using the obstacle detection function of the ultrasonic sensor and to perform the avoidance algorithm based on the measurement value of the acceleration gyro sensor. It is proposed an access surveillance system that minimizes the damage of drones, surrounding objects, and people, and improves air mobility. Experimental results show that the obstacles around the drone are detected by five ultrasonic sensors and the difference of output value is applied to each motor of the drone and obstacle avoidance is confirmed. In addition, the content and level of the data for measuring the achievement of learning achievement in the engineering education certification program were used and the results were confirmed to be consistent with the description of the engineering problem level required for the graduates of 4-year engineering college.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.9
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• pp.1987-1992
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• 2010

This paper deals with the method of using the three dimensional characteristic information to classify the front environment in travelling by using the images captured by a CCD camera equipped on a mobile robot. The images detected by the three dimensional characteristic information is divided into the part of obstacles, the part of corners, and th part of doorways in a corridor. In designing the travelling path of a mobile robot, these three situations are used as an important information in the obstacle avoidance and optimal path computing. So, this paper proposes the method of deciding the travelling direction of a mobile robot with using input images based upon the suggested algorithm by preprocessing, and verified the validity of the image information which are detected as obstacles by the analysis through neural network.