• Journal of Korea Multimedia Society
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• v.20 no.2
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• pp.344-351
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• 2017

In this paper, we propose the obstacle database management module for obstacle estimation and clustering. The proposed G-eye manager system can create customized walking route for blind people using the UI manager and verify the coordinates of the path. Especially, G-eye management system designed a regional information module. The regional information module can improve the loading speed of the obstacle data by classifying the local information by clustering the coordinates of the obstacle. In this paper, we evaluate the reliability of the walking route generated from the obstacle map. We obtain the coordinate value of the path avoiding the virtual obstacle from the proposed system and analyze the error rate of the path avoiding the obstacle according to the size of the obstacle. And we analyze the correlation between obstacle size and route by classifying virtual obstacles into sizes.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.8
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• pp.771-779
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• 2010

This paper presents a method that integrates the geometric path tracking and the obstacle avoidance for nonholonomic mobile robot. The mobile robot follows the path by moving through the turning radius given from the pure pursuit method which is the one of the geometric path tracking methods. And the obstacle generates the obstacle potential, from this potential, the virtual force is obtained. Therefore, the turning radius for avoiding the obstacle is calculated by proportional to the virtual force. By integrating the turning radius for avoiding the obstacle and the turning radius for following the path, the mobile robot follows the path and avoids the obstacle simultaneously. The effectiveness of the proposed method is verified through the real experiments for path tracking only, static obstacle avoidance, dynamic obstacle avoidance.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2010.05a
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• pp.325-326
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• 2010

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.2
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• pp.231-240
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• 2023

It remains a challenge for robots to learn avoiding obstacles automatically in path planning using deep reinforcement learning (DRL). More and more researchers use DRL to train a robot in a simulated environment and verify the possibility of DRL to achieve automatic obstacle avoidance. Due to the influence factors of different environments robots and sensors, it is rare to realize automatic obstacle avoidance of robots in real scenarios. In order to learn automatic path planning by avoiding obstacles in the actual scene we designed a simple Testbed with the wall and the obstacle and had a camera on the robot. The robot's goal is to get from the start point to the end point without hitting the wall as soon as possible. For the robot to learn to avoid the wall and obstacle we propose to use the double deep Q networks (DDQN) to verify the possibility of DRL in automatic obstacle avoidance. In the experiment the robot used is Jetbot, and it can be applied to some robot task scenarios that require obstacle avoidance in automated path planning.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.41 no.7
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• pp.809-822
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• 1992

A mathematical approach to solving the time-varying obstacle avoidance problem is pursued. The mathematical formulation of the problem is given in robot joint space(JS). View-time concept is used to deal with time-varying obstacles. The view-time is the period in which a time-varying obstacles. The view-time is the period in which a time-varying obstacle is viewed and approximated by an equivalent stationary obstacle. The equivalent stationary obstacle is the volume swept by the time-varying obstacle for the view-time. The swept volume is transformed into the JS obstacle that is the set of JS robot configurations causing the collision between the robot and the swept volume. In JS, the path avoiding the JS obstacle is planned, and a trajectory satisfying the constraints on robot motion planning is planned along the path. This method is applied to the collision-free motion planning of two SCARA robots, and the simulation results are given.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10b
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• pp.491-496
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• 1992

An analytic solution approach to the time-varying obstacle avoidance problem is pursued. We formulate the problem in robot joint space(JS), and introduce the view-time concept to deal with the time-varying obstacles. The view-time is a set of continuous times in which a time-varying obstacle is viewed and approximated by an equivalent stationary obstacle. The equivalent stationary obstacle is transformed into the JS obstacle. In JS, the path and trajectory avoiding the JS obstacle is planned.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.490-492
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• 2004

This paper presents an obstacle avoidance of a mobile robot by the subgoal generation using infrared sensors. When an obstacle appears on the path which the robot is moving forward the robot has to get information, such as distance between the robot and the obstacle and the shape of the obstacle for avoidance behavior. Our collision avoidance algorithm needs the only distance between the robot and the obstacles. The distances are used for subgoal generation. Simulation results show that a robot can go to the goal, carrying out subgoal generation and avoiding obstacles.

• Journal of Sensor Science and Technology
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• v.16 no.4
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• pp.286-293
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• 2007

For safe walking of the people who are blind, walking assistance robot which can detecting and avoiding the obstacle was investigated. The implemented prototype walking assistance robot consists of a obstacle detecting module, a user interface using acoustic signal and a driving module. The obstacle detecting module uses 6 ultrasonic sensors those located at the front part of the robot can perceive the obstacle which is in 3 meter distances and $180^{\circ}$ degrees. It calculates the distance and degree from the obstacle using TOF (time of flight) method and decides the 3-dimensional location of the obstacle. The obstacle information is delivered to the user using acoustic alarm and guide sound. The robot is designed to avoid by itself when the obstacle is detecting and the user only follows it to safe walking. After the designed robot was implemented, driving and obstacle detecting experiments were carried out. The result showed that the designed walking assistance robot will help the people who are blind to walk around safe.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.5
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• pp.471-478
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• 2011

This UGV (Unmanned Ground Vehicle) is not only widely used in various practical applications but is also currently being researched in many disciplines. In particular, obstacle avoidance is considered one of the most important technologies in the navigation of an unmanned vehicle. In this paper, we introduce a simple algorithm for path planning in order to reach a destination while avoiding a polygonal-shaped static obstacle. To effectively avoid such an obstacle, a path planned near the obstacle is much shorter than a path planned far from the obstacle, on the condition that both paths guarantee that the robot will not collide with the obstacle. So, to generate a path near the obstacle, we have developed an algorithm that combines an edge detection method and a limit-cycle navigation method. The edge detection method, based on Hough Transform and IR sensors, finds an obstacle's edge, and the limit-cycle navigation method generates a path that is smooth enough to reach a detected obstacle's edge. And we proposed novel algorithm to solve local minima using the virtual wall in the local vision. Finally, we verify performances of the proposed algorithm through simulations and experiments.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.5
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• pp.463-468
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• 2010

An obstacle avoidance method for a mobile robot is proposed in this paper. Our research was focused on the obstacles that can be found indoors since a robot is usually used within a building. It is necessary that the robot maintain the desired direction after successfully avoiding the obstacles to achieve a good autonomous navigation performance for the specified project mission. Sensors such as laser, ultrasound, and PSD (Position Sensitive Detector) can be used to detect and analyze the obstacles. A PSD sensor was used to detect and measure the height and width of the obstacles on the floor. The PSD sensor was carefully calibrated before measuring the obstacles to achieve better accuracy. Data obtained from the repeated experiments were used to plot an error graph which was fitted to a polynomial curve. The polynomial equation was used to navigate the robot. We also obtained a direction-error model of the robot after avoiding the obstacles. The prototypes for the obstacle and direction-error were modeled using a neural network whose inputs are the obstacle height, robot speed, direction of the wheels, and the error in direction. A mobile robot operated by a notebook computer was setup and the proposed algorithm was used to navigate the robot and avoid the obstacles. The results showed that our algorithm performed very well during the experiments.