• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.1
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• pp.115-122
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• 2014

Mobile robot has been studied for long time due to its simple structure and easy modeling. Regarding path planning of the mobile robot, we suggest real-time hybrid path planning algorithm which is the combination of optimal path planning and real-time path planning in this paper. Real-time hybrid path planning algorithm modifies, finds best route, and saves calculating time. It firstly plan the route with real-time path planning then robot starts to move according to the planned route. While robot is moving, update the route as the best outcome which found by optimal path planning algorithm. Verifying the performance of the proposed method through the comparing real-time hybrid path planning with optimal path planning will be done.

• Proceedings of the KIEE Conference
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• 2003.11b
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• pp.11-14
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• 2003

In this paper, we use Fuzzy Logic and Potential field method for optimal path planning of an autonomous mobile robot and apply to navigation for real-time mobile robot in 2D dynamic environment. For safe navigation of the robot, we use both Global and Local path planning. Global path planning is computed off-line using sell-decomposition and Dijkstra algorithm and Local path planning is computed on-line with sensor information using potential field method and Fuzzy Logic. We can get gravitation between two feature points and repulsive force between obstacle and robot through potential field. It is described as a summation of the result of repulsive force between obstacle and robot which is considered as an input through Fuzzy Logic and gravitation to a feature point. With this force, the robot fan get to desired target point safely and fast avoiding obstacles. We Implemented the proposed algorithm with Pioneer-DXE robot in this paper.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2007.04a
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• pp.78-83
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• 2007

The paper focuses on the establishment of optimized bucket path planning and trajectory control designated for force-reflecting backhoe reacting to excavation environment, such as potential obstacles and ground characteristics. The developed path planning method can be used for precise bucket control, and more importantly for obstacle avoidance which is directly related to safety issues. The platform of this research was based on conventional papers regarding the kinematic model of excavator. Jacobian matrix was constructed to find optimal joint angles and rotation angles of bucket from position and orientation data of excavator. By applying Newton-Raphson method optimal joint angles and bucket orientation were derived simultaneously in the way of minimizing positional errors of excavator. The model presented in this paper was intended to function as a cornerstone to build complete and advanced path planning of excavator by implementing soil mechanics and further study of excavator dynamics together.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2007.11a
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• pp.176-179
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• 2007

In this paper, we develop the path planning algorithm using the improved Dijkstra algorithm and the particle swarm optimization. To get the optimal path, at first we construct the MAKLINK on the world environment and then make a graph associated with the MAKLINK. From the graph, we obtain the Dijkstra path between the starting point and the destination point. From the optimal path, we search the improved Dijkstra path using the graph. Finally, applying the particle swarm optimization to the improved Dijkstra path, we obtain the optimal path for the mobile robot. It turns out that the proposed method has better performance than the result in [1].

• Journal of the Society of Naval Architects of Korea
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• v.50 no.5
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• pp.298-306
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• 2013

Nowadays, a transporter manager plans the schedule of the block transportation by considering the experience of the manager, the production process of the blocks and the priority of the block transportation in shipyard. The schedule planning of the block transportation should be rearranged for the reflection of the path blocking cases occurred by unexpected obstacles or delays in transportation. In this paper, the optimal block transportation path planning system is developed for rearranging the schedule of the block transportation by considering the damaged path. $A^*$ algorithm is applied to calculate the new shortest path between the departure and arrival of the blocks transported through the damaged path. In this algorithm, the first node of the damaged path is considered as the starting position of the new shortest path, and then the shortest path calculation is completed if the new shortest path is connected to the one of nodes in the original path. In addition, the data structure for the algorithm is designed. This optimal block transportation path planning system is applied to the Philippine Subic shipyard and the ability of the rapid path modification is verified.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.168-173
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• 2003

In this paper, we will present a deeper look on optimal design methods that are related to path-planning for a mobile robot. To control the motion of a mobile robot in a clustered environment, it's necessary to know a suitable trajectory assuming certain start and goal point. Up to now, there are many literatures that concern optimal path planning for an obstacle avoided mobile robot. Among those literatures, we have chosen 2 novel methods for our further analysis. The first approach [4] is based on HJB(Hamilton-Jacobi-Bellman) equation whose solution is the return-function that helps to generate a shortest path to the goal. The later [5] is called polynomial-path-planning approach, in this method, a shortest polynomial-shape path would become a solution if it was a collision-free path. The camera network plays the role as sensors to generate updated map which locates the static and dynamic objects in the space. Therefore, the exhibition of both path planning and dynamic obstacle avoidance by the updated map would be accomplished simultaneously. As we mentioned before, our research will include the motion control of a true mobile robot on those optimal planned paths which were generated by above algorithms. Base on the kinematic and dynamic simulation results, we can realize the affection of moving speed to the stable of motion on each generated path. Also, we can verify the time-optimal trajectory through velocity tuning. To simplify for our analysis, we assumed the obstacles are cylindrical circular objects with the same size.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.47 no.5
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• pp.379-387
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• 2019

The complexity of path planning for visiting multiple mission points is even larger than that of single pair path planning. Deciding a path for visiting n mission points requires conducting $n^2+n$ times of single pair path planning. We propose Multiple Mission $D^*$ Lite($MMD^*L$) which is an optimal path planning algorithm for visiting multiple mission points in dynamic environments. $MMD^*L$ reduces the complexity by reusing the computational data of preceding single pair path planning. Simulation results show that the complexity reduction is significant while its path optimality is not compromised.

• Journal of the Korean Institute of Telematics and Electronics
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• v.27 no.9
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• pp.1364-1371
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• 1990

We propose a time-optimal path planning scheme for the robot manipulator using Hopfield neural network. The time-optimal path planning, which can allow the robot system to perform the demanded tasks with a minimum execution time, may be of consequence to improve the productivity. But most of the methods proposed till now suffers from a significant computational burden and thus limits the on-line application. One way to avoid such a difficulty is to apply the neural networke technique, which can allow the parallel computation, to the minimum time problem. This paper proposes an approach for solving the time-optimal path planning by using Hopfield neural network. The effectiveness of the proposed method is demonstrarted using a PUMA 560 manipulator.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.49 no.10
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• pp.582-590
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• 2000

A fast optimal path planning algorithm using the analog Cellular Nonlinear Circuits(CNC) is proposed. The analog circuits based optimal path planning is very useful since most of the optimal path planning problems require real time computation. There has already been a previous study to implement the dynamic programming with analog circuits. However, it could not be applied for the practically large size of problems since the algorithm employs the mechanism of reducing its input current/voltage by the amount of cost, which causes outputs of distant cells to become zero. In this study, a subgoal-based dynamic programming algorithm to compute the optimal path is proposed. In the algorithm, the optimal paths are computed regardless of the distance between the starting and the goal points. It finds subgoals starting from the starting point when the output of the starting cell is raised from its initial value. The subgoal is set as the next initial position to find the next subgoal until the final goal is reached. The global optimality of the proposed algorithm is discussed and two different kinds of simulations have been done for the proposed algorithm.

• Proceedings of the IEEK Conference
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• 2000.06e
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• pp.31-34
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• 2000

In this paper, we design an optimal path for multiple mobile robots. For this purpose, we propose a new method of path planning for multiple mobile robots in dynamic environment. First, every mobile robot searches a global path using a distance transform algorithm. Then we put subgoals at crooked path points and optimize them. And finally to obtain an optimal on-line local path, ever)r mobile robot searches a new path with static and dynamic obstacle avoidance.