• Proceedings of the Korea Information Processing Society Conference
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• 2013.05a
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• pp.248-249
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• 2013

This study presents a potential field method for path planning to goal with a mobile robot in unknown environment. The proposed algorithm allows mobile robot to navigate through static obstacles, and find the path in order to reach the target without collision. This algorithm provides the robot with the possibility to move from the initial position to the final position (target). Stage and Player simulator is used to perform the robot motion and implement the potential field algorithm in C/C++ for performance evaluation. Two-dimensional terrain model is used to simulate the ability of robot in motion planning without any collision.

• ETRI Journal
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• v.45 no.5
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• pp.746-757
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• 2023

This study presents a novel safe landing algorithm for urban drone deliveries. The rapid advancement of drone technology has given rise to various delivery services for everyday necessities and emergency relief efforts. However, the reliability of drone delivery technology is still insufficient for application in urban environments. The proposed approach uses the "landing angle control" method to allow the drone to land vertically and a rapidly exploring random tree-based collision avoidance algorithm to generate safe and efficient vertical landing paths for drones while avoiding common urban obstacles like trees, street lights, utility poles, and wires; these methods allow for precise and reliable urban drone delivery. We verified the approach within a Gazebo simulation operated through ROS using a six-degree-of-freedom drone model and sensors with similar specifications to actual models. The performance of the algorithms was tested in various scenarios by comparing it with that of stateof-the-art 3D path planning algorithms.

• 제어로봇시스템학회:학술대회논문집
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• 1990.10b
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• pp.990-995
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• 1990

A minimum-time trajectory planning for two robot arms with designated paths and coordination is proposed. The problem considered in this paper is a subproblem of hierarchically decomposed trajectory planning approach for multiple robots : i) path planning, ii) coordination planning, iii) velocity planning. In coordination planning stage, coordination space, a specific form of configuration space, is constructed to determine collision region and collision-free region, and a collision-free coordination curve (CFCC) passing collision-free region is selected. In velocity planning stage, normal dynamic equations of the robots, described by joint angles, velocities and accelerations, are converted into simpler forms which are described by traveling distance along collision-free coordination curve. By utilizing maximum allowable torques and joint velocity limits, admissible range of velocity and acceleration along CFCC is derived, and a minimum-time velocity planning is calculated in phase plane. Also the planning algorithm itself is converted to simple numerical iterative calculation form based on the concept of neural optimization network, which gives a feasible approximate solution to this planning problem. To show the usefulness of proposed method, an example of trajectory planning for 2 SCARA type robots in common workspace is illustrated.

• Journal of the Korea Society of Computer and Information
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• v.18 no.1
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• pp.11-19
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• 2013

For an autonomous multi-mobile robot system, path planning and collision avoidance are important functions used to perform a given task collaboratively and cooperatively. This study considers these important and challenging problems. The proposed approach is based on a potential field method and fuzzy logic system. First, a global path planner selects the paths of the robots that minimize the cost function from each robot to its own target using a potential field. Then, a local path planner modifies the path and orientation from the global planner to avoid collisions with static and dynamic obstacles using a fuzzy logic system. In this paper, each robot independently selects its destination and considers other robots as dynamic obstacles, and there is no need to predict the motion of obstacles. This process continues until the corresponding target of each robot is found. To test this method, an autonomous multi-mobile robot simulator (AMMRS) is developed, and both simulation-based and experimental results are given. The results show that the path planning and collision avoidance strategies are effective and useful for multi-mobile robot systems.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1995.04a
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• pp.880-885
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• 1995

This paper deals with the efficient planning of robot motions in the Cartesian space while avoiding the collision with obstacles. The motion planning problem is to find a path from the specified starting robot configuration that avoids collision with a known set of stationary obstacles. A simple and efficient algorithm was developed using "Backward" approach to solve this problem. The computational result was satisfactory enough to real problems. problems.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1991.10a
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• pp.231-231
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• 1991

• Transactions of the Korean Society of Automotive Engineers
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• v.17 no.2
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• pp.1-9
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• 2009

A parking-assist system is defined that a driver adjusts vehicle velocity through brake pedal operation and parking-assist system controls the motion of the vehicle to follow a collision-free path. In this study, a motion control algorithm using Fuzzy inference is proposed to track a maneuvering clothoid parallel path. Simulations are performed under SIMULINK environments using MATLAB and CarSim for a vehicle model. As the vehicle model in MATLAB a bicycle model is used including lateral dynamics. The simulation results show that the path tracking performance is satisfactory under various driving and initial conditions.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.2
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• pp.291-297
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• 2012

In this paper, potential field algorithm was used for path planning in dynamic environment. This algorithm is used to plan a robot path because of its elegant mathematical analysis and simplicity. However, there are some problems. The problems are problem of collision risk, problem of avoidance path, problem of time consumption. In order to solve these problems, we fused potential field with fuzzy system. The input of the fuzzy system is set using relative velocity and location of robot and obstacle. The output of the fuzzy system is set using the weighting factor of repulsive potential function. The potential field algorithm is improved by using fuzzy potential field algorithm and, path planning in various environment has been done.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.131.4-131
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• 2001

A lot of path planning algorithms have been developed to find the collision-free path with minimum cost. But most of them require complicated computations. In this paper, a thinning method, which is one of the image processing schemes, was adopted to simplify the path planning procedure. In addition, critical points are used to find the shortest-distance path among all possible paths from the start to the goal point. Since the critical points contain the information on the neighboring paths, a new path can be quickly obtained on the map even when the start and goal points change. To investigate the validity of the proposed algorithm, various simulations have been performed for the environment where the obstacles with arbitrary shapes exist. It is shown that the optimal paths can be found with relative easiness.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.120.3-120
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• 2001

We propose a new method of path planning for cleaning robots. Path planning problem for cleaning robots is different from conventional path planning problems in which finding a collision-free trajectory from a start point to a goal point is focused. In the case of cleaning robots, however, a planned path should cover all area to be cleaned. To resolve this problem in a systematic way, we propose a method based on a graph model as follows: at first, partition a given map into proper regions, then transform a divided region to a vertex and a connectivity between regions to an edge of a graph. Finally, a region is divided into sub-regions so that the graph has a unary tree which is the simplest Hamilton path. The effectiveness of the proposed method is shown by computer simulation results.