• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.12
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• pp.2296-2302
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• 2006

In this paper, we propose a development technique of high precision laser finder ranger within instrument distance 1km, instrument error less than 1 m by using pulse time of flight method in the 5m unit instrument and heterodyne method in the within Am unit. These propose methods can be more advanced to measurement velocity and more highly precision distance instrument not affected the strength of light. We also validate this usefulness.

• International Journal of Highway Engineering
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• v.18 no.3
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• pp.127-134
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• 2016

PURPOSES : Low visibility caused by dark surroundings at nighttime affects the likelihood of accidents, and various efforts, such as installing road safety facilities, have been made to reduce accidents at night. Despite these efforts, the nighttime severity index (SI) in Korea was higher than the daytime SI during 2011-2014. This study determined the factors affecting daytime and nighttime accident severity through a discriminant analysis. METHODS : Discriminant analysis. RESULTS : First, drowsiness, lack of attention, and lighting facilities affected both daytime and nighttime accident severity. Accidents were found to be caused by a low ability to recognize the driving conditions and a low obstacle avoidance capability. Second, road conditions and speeding affected only the daytime accident severity. Third, failure to maintain a safe distance significantly affected daytime accident severity and nonsignificantly affected nighttime accident severity. The majority of such accidents were caused by rear-end collisions of vehicles driving in the same direction; given the low relative speed difference in such cases, the shock imparted by the accidents was minimal. CONCLUSIONS : Accidents caused by a failure to maintain a safe distance has lower severity than do accidents caused by other factors.

• International Journal of Aeronautical and Space Sciences
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• v.18 no.4
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• pp.719-728
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• 2017

This paper proposes a synthesis of new guidance law to generate an evasive maneuver against enemy's missile interception while considering its impact angle, acceleration, and field-of-view constraints. The first component of the synthesis is a new function of repulsive Artificial Potential Field to generate the evasive maneuver as a real-time dynamic obstacle avoidance. The terminal impact angle and terminal acceleration constraints compliance are based on Time-to-Go Polynomial Guidance as the second component. The last component is the Logarithmic Barrier Function to satisfy the field-of-view limitation constraint by compensating the excessive total acceleration command. These three components are synthesized into a new guidance law, which involves three design parameter gains. Parameter study and numerical simulations are delivered to demonstrate the performance of the proposed repulsive function and guidance law. Finally, the guidance law simulations effectively achieve the zero terminal miss distance, while satisfying an evasive maneuver against intercept missile, considering impact angle, acceleration, and field-of-view limitation constraints simultaneously.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.2024-2029
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• 2005

In this paper, it is shown how a mobile robot can navigate with high speed in dynamic real environment. In order to achieve high speed and safe navigation, a robot collects environmental information. A robot empirically memorizes locations of high risk due to the abrupt appearance of dynamic obstacles. After collecting sufficient data, a robot navigates in high speed in safe regions. This fact implies that the robot accumulates location dependent environmental information and the robot exploits its experiences in order to improve its navigation performance. This paper proposes a computational scheme how a robot can distinguish regions of high risk. Then, we focus on velocity control in order to achieve high speed navigation. The proposed scheme is experimentally tested in real office building. The experimental results clearly show that the proposed scheme is useful for improving a performance of autonomous navigation. Although the scope of this paper is limited to the velocity control in order to deal with unexpected obstacles, this paper points out a new direction towards the intelligent behavior control of autonomous robots based on the robot's experience.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.2237-2242
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• 2005

The original RRT is iteratively expanded by applying control inputs that drive the system slightly toward randomly-selected states, as opposed to requiring point-to-point convergence, as in the probabilistic roadmap approach. It is generally known that the performance of RRTs can be improved depending on the selection of the metrics in choosing the nearest vertex and bias techniques in choosing random states. We designed a path planning algorithm based on the RRT method for a remote-controlled mobile robot. First, we considered a bias technique that is goal-biased Gaussian random distribution along the command directions. Secondly, we selected the metric based on a weighted Euclidean distance of random states and a weighted distance from the goal region. It can save the effort to explore the unnecessary regions and help the mobile robot to find a feasible trajectory as fast as possible. Finally, the constraints of the actuator should be considered to apply the algorithm to physical mobile robots, so we select control inputs distributed with commanded inputs and constrained by the maximum rate of input change instead of random inputs. Simulation results demonstrate that the proposed algorithm is significantly more efficient for planning than a basic RRT planner. It reduces the computational time needed to find a feasible trajectory and can be practically implemented in a remote-controlled mobile robot.

• IEMEK Journal of Embedded Systems and Applications
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• v.7 no.5
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• pp.227-239
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• 2012

Recent advances in electronics have enabled various conventional products to incorporate with numerous powerful microcontroller. Generally, an embedded system is a computer system designed for specific control functions within a larger system, often with real-time computing constraints. The growing performance and reliability of hardware components and the possibilities brought by various design method enabled implementing complex functions that improve the comport of the system's occupant as well as their safety. A cyber physical system (CPS) is a system featuring a tight combination of, and coordination between, the system's computational and physical elements. The concept of cyber physical system, including physical elements, cyber elements, and shared networks, has been introduced due to two general reasons: design flexibility and reliability. This paper presents a cyber physical system where system components are connected to a shared network, and control functions are divided into small tasks that are distributed over a number of embedded controllers with limited computing capacity. In order to demonstrate the effectiveness of cyber physical system, an unmanned forklift with autonomous obstacle avoidance ability is implemented and its performance is experimentally evaluated.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.4
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• pp.457-467
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• 2004

In this paper, a robot is considered as an agent, a structure of robot is presented which consisted by multi-subagents and they have diverse capacity such as perception, intelligence, action etc., required for robot. Also, subagents are consisted by micro-agent($\mu$agent) charged for elementary action required. The structure of robot control have two sub-agents, the one is behavior based reactive controller and action selection sub agent, and action selection sub-agent select a action based on the high label action and high performance, and which have a learning mechanism based on the reinforcement learning. For presented robot structure, it is easy to give intelligence to each element of action and a new approach of multi robot control. Presented robot is simulated for two goals: chaotic exploration and obstacle avoidance, and fabricated by using 8bit microcontroller, and experimented.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.9
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• pp.818-826
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• 2015

This paper presents a novel methodology for estimating vehicle ego-motion, i.e. tri-axis linear velocities and angular velocities by using stereo vision sensor and 2G1Y sensor (longitudinal acceleration, lateral acceleration, and yaw rate). The estimated ego-motion information can be utilized to predict future ego-path and improve the accuracy of 3D coordinate of obstacle by compensating for disturbance from vehicle movement representatively for collision avoidance system. For the purpose of incorporating vehicle dynamic characteristics into ego-motion estimation, the state evolution model of Kalman filter has been augmented with lateral vehicle dynamics and the vanishing point estimation has been also taken into account because the optical flow radiates from a vanishing point which might be varied due to vehicle pitch motion. Experimental results based on real-world data have shown the effectiveness of the proposed methodology in view of accuracy.

• Journal of Korea Game Society
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• v.6 no.3
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• pp.3-12
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• 2006

Path-finding, one of the traditional Game A.I. problems, becomes an important issue to make games more realistic. Due to the limited resources in the computer system, path-finding systems sometimes produce a simplified and unrealistic path. The most relent researches have been focused on the path-finding avoiding only static obstacles. Various moving obstacles are however deployed in real games, a method avoiding those obstacles and producing a smooth path is necessary. In this paper, navigation mesh is used to represent 3D space and its topological characteristics are used for path-finding. Intellectual repulser and attractor are also used to avoid moving obstacles and to find an optimal path. We have evaluated the path produced by the method proposed in this paper and verified its usability in real game.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.24 no.11
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• pp.2875-2882
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• 2000

Typically, the ultrasonic sensors can be used in navigation systems for modeling of the enviornment, obstacle avoidance, and map building. In this paper, we tried to approach an object classification method using the range data of the ultrasonic sensors. A characterization of the sonar scan is described that allows the differentiation of planes, corners, edges, cylindrical and rectangular pillars by processing the scanned data from three sonars. To use the data from the ultrasonic sensors as input to the neural networks, we have introduced a clustering, threshold, and bit operation algorithm for the obtained raw data, After repeated training of the neural network, the performance of the proposed method was obtained through experiments. Also, the recognition ranges of the proposed method were investigated. As a result of experiments, we found that the proposed method successfully recognized the objects within the accuracy of 78%.