• The Transactions of the Korean Institute of Electrical Engineers D
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• v.53 no.7
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• pp.509-516
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• 2004

This paper proposes an image processing algorithm for detecting obstacles on road using DLI(disparity of lane-related information) that is generated by stereo images acquired from dual cameras mounted on a moving vehicle. The DLI is a disparity that is acquired using a single lane information from road lane detection. For the purpose to reduce processing time, we use small block of edge-histogram based blocking logic. This algorithm detects moving objects such as preceding vehicles and obstacles. The proposed algorithm has been implemented in a personal computer with the road image data of a typical highway. We successfully performed experiments under a wide variety of road conditions without changing parameter values or adding human intervention. Experimental results also showed that the proposed DLI is quite successful.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2895-2897
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• 2000

This paper proposes a new fuzzy-neural algorithm for navigation of a mobile robot with stationary and moving obstacles environment. The proposed algorithm has two-layered hierarchical structure such as a lower layer for collision avoidance and goal approach. and upper layer for adaptive combination of these two algorithms. Some computer simulation results for a mobile robot equipped with ultrasonic range sensors show that the suggested navigation algorithm is very effective in stationary and moving obstacles environment.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.100-105
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• 1993

This paper discusses an approach to real-time path-planning of mobile robot navigating amidst multiple obstacles. Given an environment with the coordinates of known obstacles, the moving area of a mobile robot is divided into many patches of triangles with small edge length, in order to ensure a path better than those reported in the literature. After finding a minimum-distance to minimize the number of turns and total path-length by two-step path-revision and path-smmothing.

• 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.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.164-164
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• 2000

This paper proposes a moving window technique that extracts lanes and vehicles using the images captured by a CCD camera equipped inside an automobile in real time. For the purpose, first of all the optimal size of moving window is determined based upon speed of the vehicle, road curvature, and camera parameters. Within the moving windows that are dynamically changing, lanes and vehicles are extracted, and the vehicles within the driving lanes are classified as obstacles. Assuming highway driving, there are two sorts of image-objects within the driving lanes: one is ground mark to show the limit speed or some information for driving, and the other is the vehicle as an obstacle. Using characteristics of three-dimension objects, a neural network can be trained to distinguish the vehicle from ground mark. When it is recognized as an obstacle, the distance from the camera to the front vehicle can be calculated with the aids of database that keeps the models of automobiles on the highway. The correctness of this measurement is verified through the experiments comparing with the radar and laser sensor data.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.3
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• pp.377-383
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• 2021

Recently, in accordance with the 4th industrial revolution, The use of autonomous mobile robots for flexible logistics transfer is increasing in factories, the warehouses and the service areas, etc. In large factories, many manual work is required to use Simultaneous Localization and Mapping(SLAM), so the need for the improved mobile robot autonomous driving is emerging. Accordingly, in this paper, an algorithm for mapless navigation that travels in an optimal path avoiding fixed or moving obstacles is proposed. For mapless navigation, the robot is trained to avoid fixed or moving obstacles through Deep Q Network (DQN) and accuracy 90% and 93% are obtained for two types of obstacle avoidance, respectively. In addition, DQN requires a lot of learning time to meet the required performance before use. To shorten this, the target size change algorithm is proposed and confirmed the reduced learning time and performance of obstacle avoidance through simulation.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.21 no.10
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• pp.1551-1560
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• 1997

This study is devoted to the detection of the 3-dimensional point obstacles on the plane by using accumulated scan line images. The proposed accumulating only one scan line allow to process image at real time. And the change of motion of the feature in image is small because of the short time between image frames, so it does not take much time to track features. To obtain recursive optimal obstacles position and robot motion along to the motion of camera, Kalman filter algorithm is used. After using Kalman filter in case of the fixed environment, 3-dimensional obstacles point map is obtained. The position and motion of moving obstacles can also be obtained by pre-segmentation. Finally, to solve the stereo ambiguity problem from multiple matches, the camera motion is actively used to discard mis-matched features. To get relative distance of obstacles from camera, parallel stereo camera setup is used. In order to evaluate the proposed algorithm, experiments are carried out by a small test vehicle.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.43 no.3 s.309
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• pp.31-40
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• 2006

Many researches on path planning and obstacle avoidance for the fundamentals of mobile robot have been done. Informations from various sensors can find obstacles and make path. In spite of many solutions of finding optimal path, each can be applied to only a constrained condition. This means that it is difficult to find a universal algorithm. A optimal path with a complicated computation generates a time delay which cannot avoid moving obstacles. In this paper, we propose the algorithm of path planning and obstacle avoidance for mobile robot. We call the proposed method Random Access Sequence(RAS) method. In the proposed method, a small region is set first and numbers are assigned to its neighbors, then the path is selected using these numbers. It has an advantage of fast planning and simple operation. This means that new path selection may be possible within short time and that helps a robot to avoid obstacle in any direction. When a robot meets moving obstacles, it avoids obstacles in a random direction. RAS method using obstacle information from variable sensors is useful to get minimum path length to goal.

• Journal of the Korea Society for Simulation
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• v.16 no.1
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• pp.31-37
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• 2007

The importance of NPC's role in computer games is increasing. An NPC must perform its tasks by perceiving obstacles and other characters and by moving through them. It has been proposed to plan a natural-looking path against fixed obstacles by using a generalized visibility graph. In this paper we develop the execution module for an NPC to move efficiently along the path planned on the generalized visibility graph. The planned path consists of line segments and arc segments, so we define steering behaviors such as linear behaviors, circular behaviors, and an arriving behavior for NPC's movements to be realistic and utilize them during execution. The execution module also includes the collision detection capability to be able to detect dynamic obstacles and uses a decision tree to react differently according to the detected obstacles. The execution module is tested through the simulation based on the example scenario in which an NPC interferes the other moving NPC.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.54 no.5
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• pp.307-314
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• 2005

In this paper, we propose a predictive system for the avoidance of the moving obstacle. In the dynamic environment, robots should travel to the target point without collision with the moving obstacle. For this, we need the prediction of the position and velocity of the moving obstacle. So, we use the Kalman filer algorithm for the prediction. And for the application of the Kalman filter algorithm about the real time travel, we obtain the position of the obstacle which has the future time using Fuzzy system. Through the computer simulation studies, we show the effectiveness of the proposed navigational algorithm for autonomous mobile robots.