• 제어로봇시스템학회:학술대회논문집
• /
• 2002.10a
• /
• pp.106.5-106
• /
• 2002

1. Introduction 2. Artificial Immune Networks and Navigation Algorithm 3. Obstacle Avoidance and Goal Approach Behavior 4. Weights Adjustment Using Neural Network 5. Velocity Control and Local Minimum Avoidance 6. Simulation 7. Conclusion

• Journal of Ocean Engineering and Technology
• /
• v.33 no.6
• /
• pp.510-517
• /
• 2019

Efficient path planning is essential for unmanned surface vehicle (USV) navigation. The A^* algorithm is an effective algorithm for identifying a safe path with optimal distance cost. In this study, a modified version of the A^* algorithm is applied for planning the path of a USV in a static and dynamic obstacle environment. The current study adopts the A^* approach while maintaining a safe distance between the USV and obstacles. Two important parameters-path length and computational time-are considered at various start times. The results demonstrate that the modified approach is effective for obstacle avoidance by a USV that is compliant with the International Regulations for Preventing Collision at Sea (COLREGs).

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 2005.06a
• /
• pp.1468-1471
• /
• 2005

This Paper is to find out a solution for the full-coverage algorithm requiring the real-time processing such as mobile home service robots and vacuum cleaner robots. Previous methods are used by adopting based grid approach method. They used lots of sensors, a high speed CPU, expensive ranger sensors and huge memory. Besides, most full-coverage algorithms should have a map before obstacle avoidance. However, if a robot able to recognize the tangent vector of obstacles, it is able to bring the same result with less sensors and simplified hardware. Therefore, this study suggests a topological based approach and a local obstacle voidance method using a few of PSD sensors and ultra sonic sensors. The simulation results are presented to prove its applicability.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
• /
• 1998.03a
• /
• pp.88-93
• /
• 1998

This paper presents a new solution approach to moving obstacle avoidance problem for a mobile robot. A new concept avoidability measure(AVM) is defined to describe the state of a pair of a robot and an obstacle regarding the collision between them. As an AVM, virtual distance function(VDF) is derived as a function of the distance from the obstacle to the robot and outward speed of the obstacle relative to the robot. By keeping the virtual distance above some positive limit value, the robot avoids the obstacle. In terns of the VDF, an artificial potential field is constructed to repel the robot away from the obstacle and to attract the robot toward a goal location. At every sampling time, the artificial potential field is updated and the force driving the robot is derived form the gradient of the artificial potential field. The suggested algorithm drives the robot to avoid moving obstacles in real time. Since the algorithm considers the mobility of the obstacle as well as the distance, it is effective for moving obstacle avoidance. Some simulation studies show the effectiveness of the proposed approach.

• Journal of the Korean Society of Industry Convergence
• /
• v.21 no.2
• /
• pp.95-101
• /
• 2018

This paper presents a collision free mobile robot navigation based on the fuzzy inference fusion model in unkonown environments using multi-ultrasonic sensor. Six ultrasonic sensors are used for the collision avoidance approach where CCD camera sensors is used for the trajectory following approach. The fuzzy system is composed of three inputs which are the six distance sensors and the camera, two outputs which are the left and right velocities of the mobile robot's wheels, and three cost functions for the robot's movement, direction, obstacle avoidance, and rotation. For the evaluation of the proposed algorithm, we performed real experiments with mobile robot with ultrasonic sensors. The results show that the proposed algorithm is apt to identify obstacles in unknown environments to guide the robot to the goal location safely.

• Korean Journal of Child Studies
• /
• v.28 no.5
• /
• pp.209-220
• /
• 2007

This study explored the effects of self efficacy, classroom contextual characteristics and help-avoidance attitudes on academic help-seeking behavior. Participants were 210 4th grade students. Data were analyzed by Pearson's correlation coefficient and multiple regression analysis through the SPSSWIN 12.0. Results showed that students' self efficacy, perception of teacher behavior and goal orientations were positively related to help-seeking behaviors. Help-avoidance attitudes were negatively related to help-seeking behaviors. Cognitive efficacy and social-emotional efficacy facilitated help-seeking behaviors. Help-seeking behaviors were influenced by teacher's supportive help and expectation. Mastery goal orientations and performance-approach goal orientations promoted help-seeking behaviors but performance-avoidance goal orientations impeded help-seeking behaviors. Autonomous intention attitudes expedited help-seeking behaviors but intention based on ability diminished help-seeking behaviors.

• International Journal of Aeronautical and Space Sciences
• /
• v.14 no.3
• /
• pp.272-281
• /
• 2013

Traffic Collision Avoidance System (TCAS) is designed to enhance safety in aircraft operations, by reducing the incidences of mid-air collision between aircraft. The current version of TCAS provides only vertical resolution advisory to the pilots, if an aircraft's collision with another is predicted to be imminent, while efforts to include horizontal resolution advisory have been made, as well. This paper introduces a collision resolution algorithm, which includes both vertical and horizontal avoidance maneuvers of aircraft. Also, the paper compares between the performance of the proposed algorithm and that of algorithms with only vertical or horizontal avoidance maneuver of aircraft.

• Journal of Korean Society of Transportation
• /
• v.35 no.4
• /
• pp.292-306
• /
• 2017

Traffic noise cost can be assessed either by the damage cost approach or by the avoidance cost method. This paper provides an overview of pertinent studies of these two approaches and shows that the damage cost approach is more universal and reliable than the avoidance cost counterpart. This study then investigated three sub-components to address the damage cost framework. First of all, unit value per person exposed to noise per year was calculated. Secondly, the area exposed to noise was determined using noise prediction equation. Thirdly, the number of people affected by noise was computed by multiplying the number of people exposed to noise with the percentage of people affected by noise. This paper also suggested a simplified equation that represents the relationship between damage costs and noise levels. Finally, the benefits of noise reduction derived from the damage cost method and those from the avoidance cost approach were compared and discussed.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
• /
• 2004.08a
• /
• pp.146-154
• /
• 2004

Evaluating the risk of collision quantitatively plays a key role in developing the expert system of navigation and collision avoidance. This study suggested and developed a new approach to the evaluation by using the sech function as an alternative to the existing methods of appraising the collision risk. This study also investigated and built up theoretically how to determine the gradient coefficients in this approach and suggested the appropriate values as much as applicable. Finally this study analyzed thoroughly how to determine the threshold function of avoiding time and developed the appropriate equation.

• International Journal of Aeronautical and Space Sciences
• /
• v.14 no.1
• /
• pp.75-84
• /
• 2013

In this paper, the guidance law for formation flight and collision avoidance of multiple Unmanned Aerial Vehicle (UAV)s is proposed. To construct the physically comprehensible guidance law for formation flight, the virtual structure approach is used. To develop a guidance law for collision avoidance considering both other UAVs and unknown static obstacles, a geometric approach using information such as a relative position vector is utilized. Through the Lyapunov theorem, the stability of the proposed guidance law is proved. To combine guidance commands, the concept of the elastic weighting factor inspired by the elastic behavior of shape memory polymer, which tends to regain its original shape after deformation, is introduced. By using the concept of elastic weighting factor, multiple UAVs are able to cope actively with the situation of a collision between both UAVs and static obstacles during the formation flight. To verify the performance of the proposed method, numerical simulations are performed.