• Journal of the Korea Institute of Military Science and Technology
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• v.12 no.6
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• pp.689-696
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• 2009

In this paper, a new user interface for unmanned combat vehicle(UCV) is developed based on the mission planning and global path planning. In order to complete a tactical mission given to an UCV, it is essential to design an effective interface scheme between human and UCV considering changing combat environment and characteristics of the mission. The user interface is mainly composed of two parts, mission planning and global path planning, since they are important factors to accomplish combat missions. First of all, mission types of UCV are identified. Based on mission types, the concept of mission planning for UCVs is presented. Then a new method for global path planning is devised. It is capable of dealing with multiple grid maps to consider various combat factors so that paths suitable for the mission be generated. By combining these two, a user interface method is suggested. It is partially implemented in the Dog-horse Robot of ADD and its effectiveness is verified.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2002.04a
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• pp.184-189
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• 2002

Collision free task planning for dual-arm robot which perform many subtasks in a common work space can be achieved in two steps : path planning and trajectory planning. Path planning finds the order of tasks for each robot to minimize path lengths as well as to avoid collision with static obstacles. A trajectory planning strategy is to let each robot move along its path as fast as possible and delay one robot at its initial position or reduce speed at the middle of its path to avoid collision with the other robot.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2001.04a
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• pp.244-249
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• 2001

Collision free task planning for dual-arm robot which perform many subtasks in a common work space can be achieved in two steps : path planning and trajectory planning. Path planning finds the order of tasks for each robot to minimize path lengths as well as to avoid collision with static obstacles. A trajectory planning strategy is to let each robot move along its path as fast as possible and delay one robot at its initial position or reduce speed at the middle of its path to avoid collision with the other robot.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2000.10a
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• pp.113-118
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• 2000

Collision free task planning for dual-arm robot which perform many subtasks in a common work space can be achieved in two steps : path planning and trajectory planning. Path planning finds the order of tasks for each robot to minimize path lengths as well as to avoid collision with static obstacles. A trajectory planning strategy is to let each robot move along its path as fast as possible and delay one robot at its initial position or reduce speed at the middle of its path to avoid collision with the other robot.

• The Journal of Korea Robotics Society
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• v.18 no.3
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• pp.316-322
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• 2023

The increasing popularity of autonomous unmanned aerial vehicles (UAVs) can be attributed to their wide range of applications. 3D path planning is one of the crucial components enabling autonomous flight. In this paper, we present a novel 3D path planning algorithm that generates and utilizes curvature-based trajectories. Our approach leverages circular properties, offering notable advantages. First, circular trajectories make collision detection easier. Second, the planning procedure is streamlined by eliminating the need for the spline process to generate dynamically feasible trajectories. To validate our proposed algorithm, we conducted simulations in Gazebo Simulator. Within the simulation, we placed various obstacles such as pillars, nets, trees, and walls. The results demonstrate the efficacy and potential of our proposed algorithm in facilitating efficient and reliable 3D path planning for UAVs.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.8
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• pp.1483-1490
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• 2009

This parer is presented multiple path-planning of unmanned autonomous forklift using modified genetic algorithm and fuzzy inference system. There are a task-level feedback method and a method that path is dynamically replaned in realtime while the autonomous vehicles are moving by means of an optimal algorithm for existing multiple path-planning. However, such methods cause malfunctions and inefficiency in the sense of time and energy, and path-planning should be dynamically replanned in realtime. To solve these problems, we propose multiple path-planning using modified genetic algorithm and fuzzy inference system and show the performance with autonomous vehicles. For experiment, we designed and built two autonomous mobile vehicles that equipped with the same driving control part used in actual autonomous forklift, and test the proposed multiple path-planning algorithm. Experimental result that actual autonomous mobile vehicle, we verified that fast optimized path-planning and efficient collision avoidance are possible.

• 제어로봇시스템학회:학술대회논문집
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• 1990.10a
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• pp.722-725
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• 1990

This paper proposes a new path planning method for obstacle avoidance of mobile robot. In order to achieve easy planning of the path, a simple representation of the empty space is achieved based on thinning algorithm. The proposed Planning technique facilitates the direct use of information obtained by camera. Comparing to the V-graph method, the task of determining the shortest path from the resulting skeleton of empty space is optimized in terms of number of computation steps. The usefulness of the proposed method is ascertained by simulation.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.9 no.4
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• pp.782-791
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• 2005

In this paper, path planning and tracking problems are mentioned to guarantee efficient and safe navigation of autonomous mobile robots. We focus on the path planning and also deal with the path tracking and obstacle avoidance. We improved the conventional distance transform (DT) algorithm for the path planning. Using the improved DT algorithm, we obtain paths with shorter distances compared to the conventional DT algorithm. In the stage of the Path tracking, we employ the fuzzy logic controller to conduct the path tracking behavior and obstacle avoidance behavior. Through computer simulation studies, we show the effectiveness of the Nosed navigational algorithm for autonomous mobile robots.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• v.9 no.1
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• pp.295-299
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• 2005

In this paper, path planning and tracking problems are mentioned to guarantee efficient and safe navigation of autonomous mobile robots. We focus on the path planning and also deal with the path tracking and obstacle avoidance. We improved the conventional distance transform (DT) algorithm for the path planning. Using the improved DT algorithm, we obtain paths with shorter distances compared to the conventional DT algorithm. In the stage of the path tracking, we employ the fuzzy logic controller to conduct the path tracking behavior and obstacle avoidance behavior. Through computer simulation studies, we show the effectiveness of the proposed navigational algorithm for autonomous mobile robots.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.10
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• pp.1479-1485
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• 2015

Robot's technology was very simple and repetitive in the past. Nowadays, robots are required to perform intelligent operation. So, path planning has been studied extensively to create a path from start position to the goal position. In this paper, potential field algorithm was used for path planning in dynamic environments. It is used for a path plan of mobile robot because it is elegant mathematical analysis and simplicity. However, there are some problems. The problems are collision risk, avoidance path, time attrition. In order to resolve path problems, we amalgamated potential field algorithm with the artificial neural network system. The input of the neural network system is set using relative velocity and location between the robot and the obstacle. The output of the neural network system is used for the weighting factor of the repulsive potential function. The potential field algorithm problem of mobile robot's path planning can be improved by using artificial neural network system. The suggested algorithm was verified by simulations in various dynamic environments.