• Proceedings of the KIEE Conference
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• 1994.11a
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• pp.345-348
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• 1994

A real-time collision avoidance algorithm for an AMR (Autonomous Mobile Robot) using the Distance Transform and Vector Field Histogram is studied. This approach enables AMR to find a collision-free path with the unknown obstacles. All system parameters including positions of the obstacles can be accepted using a mouse icon and all the obtained trajectories can be displayed on a computer monitor in graphics.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.2
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• pp.211-217
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• 2014

This paper addresses an algorithm of path planning for autonomous driving of a ground vehicle in waypoint navigation. The proposed algorithm is flexible in utilization under a large GPS positioning error and generates collision-free multiple paths while pursuing minimum traveling time. An optimal path reduces inefficient steering by minimizing lateral changes in generated waypoints along a path. Simulation results compare the proposed algorithm with the A* algorithm by manipulation of the steering wheel and traveling time, and show that the proposed algorithm realizes real-time obstacle avoidance by quick processing of path generation, and minimum time traveling by producing paths with small lateral changes while overcoming the very irregular positioning error from the GPS.

• Proceedings of the KSME Conference
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• 2000.11a
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• pp.570-575
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• 2000

This paper presents a delayed time path planning method of the Autonomous Mobile Robot using fuzzy logic controller for avoidance of obstacles in unknown environment. It is the objective of this paper to develop fuzzy control algorithms using delayed time techniques to deal with moving obstacles randomly. This control method gives the benefit of the collision free movement in real time and optimal path to the pre-settled goal. The computer simulations are demonstrated the effective of the suggested control method in obstacle avoidance.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.4
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• pp.686-691
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• 2008

This paper proposes the concept of "virtual sensor data" and its application for real time obstacle avoidance. The virtual sensor data is virtual distance which takes care of the movement of the obstacle as well as that of the robot. In practical application, the virtual sensor data is calculated from the odometry data and the range sensor data. The virtual sensor data can be used in all the methods which use distance data for collision avoidance. Since the virtual sensor data considers the movement of the robot and the obstacle, the methods utilizing the virtual sensor data results in more smooth and safer collision-free motion.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.690-693
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• 2004

This paper proposes a multi-resolution electrostatic potential field (MREPF) based solution to the mobile robot path planning and collision avoidance problem in 2D dynamic environment. The MREPF is an environment method in calculation time and updating field map. The large scale resolution map is added to EPF and this resolution map interacts with the small scale resolution map to find an optimal solution in real time. This approach can be interpreted with Atlantis model. The simulation studies show the efficiency of the proposed algorithm.

• Journal of the Korean Society for Precision Engineering
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• v.15 no.6
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• pp.107-115
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• 1998

A path planning using potential field method is very useful for the real-time navigation of mobile robots. However, the method needs high modeling cost to calculate the potential field because of complex preprocessing, and mobile robots may get stuck into local minima. In this paper, An efficient path planning algorithm for multiple mobile robots, based on the potential field method, was proposed. In the algorithm. the concepts of subgoals and obstacle priority were introduced. The subgoals can be used to escape local minima, or to design and change the paths of mobile robots in the work space. In obstacle priority, all the objects (obstacles and mobile robots) in the work space have their own priorities, and the object having lower priority should avoid the objects having higher priority than it has. In this paper, first, potential based path planning method was introduced, next an efficient collision-avoidance algorithm for multiple mobile robots, moving in the obstacle environment, was proposed by using subgoals and obstacle priority. Finally, the developed algorithm was demonstrated graphically to show the usefulness of the algorithm.

• Journal of the Korean Society for Precision Engineering
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• v.17 no.7
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• pp.113-123
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• 2000

In the navigation for a mobile robot, the collision avoidance with unexpected obstacles is essential for the safe navigation and it is independent of the technique used to control the mobile robot. This paper presents a new collision avoidance algorithm using neural network for the safe navigation of the autonomous mobile robot equipped with CAN and ultrasonic sensors. A tracked wheeled mobile robot has a stability and an efficiency to move on a rough ground. And its mechanism is simple. However it has difficulties to recognize its surroundings. Because the shape of the tracked wheeled mobile robot is a square type, sensor modules are generally located on the each plane surface of 4 sides only. In this paper, the algorithm using neural network is proposed in order to avoid unexpected obstacles. The important character of the proposed algorithm is to be able to detect the distance and the angle of inclination of obstacles. Only using datum of the distance and the angle, informations about the location and shape of obstacles are obtained, and then the driving direction is changed. Consequently, this algorithm is capable of real time processing and available for a mobile robot which has few sensor modules or the limited sensing range such as a tracked wheeled mobile robot. Effectiveness of the proposed algorithm is illustrated through a computer simulation and an experiment using a real robot.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.7 no.1
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• pp.9-21
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• 1998

This paper a new solution approach to moving obstacle avoidance problem of 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 terms 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 from 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.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.10a
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• pp.327-330
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• 1995

If a mobile robot is used in a real situation, robot must face a moving obstacles. In that case, the collision avoidance algorithm for moving obstacle is a indispensible element in mobile robot control. We csrried out a research to find and evaluate the advanced algorithm for mobile robot. At first we generate the continous path for mobi;e robot. Then by creating a curved path for avoidance, the mobile robot can change its path smoothly. Smoothed path made the robot adapt more effectively to the changing of path. Under time-varying condition, computer simulation was performed to show the validation of proposed algorithm.

• Journal of Navigation and Port Research
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• v.34 no.6
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• pp.405-415
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• 2010

To assess the possible collision risk between Mokpo Harbour Bridge, which is under construction, and passing vessels, we proposed Real-Time Bridge-Vessel Collision Model (RT-BVCM) in this paper. The mathematical model of RT-BVCM consists of the causation probability by the vessel aberrancy due to navigation environments, the geometric probability by the structural feature of a bridge relative to a ship size and, the failure probability by the ship collision track and the stopping distance which is not to come to a stop before hitting the obstacles. Then, the probabilistic mathematical model represented as risk index with the risk level from 1 to 5. The merit of the proposed model to the collision model proposed by AASHTO (American Association of State Highway and Transportation Officials) is that it can provide enough time to take adequate collision avoiding action. Through the simulation tests to the two kinds of test ships, 3,000 GT and 10,000 GT, it is cleary found that the proposed model can be used as a collision evaluation model to the passing vessel and Mokpo Harbour Bridge.