• Transactions of the Korean Society of Mechanical Engineers A
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• v.21 no.12
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• pp.1992-2007
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• 1997

A new algorithm for planning a collision-free path is developed based on linear prametric curve. In this paper robot is assumed to a point, and two linear parametric curve is used to construct a path connecting start and goal point, in which single intermediate connection point between start and goal point is considered. The intermediate connection point is set in polar coordinate(${\theta}{\delta}$) , and the interference between path and obstacle is mapped into CPS(connection point space), which is defined a CWS GM(circular work space geometry mapping). GM of all obstacles in workspace creates overlapping images of obstacle in CPS(Connection Point Space). The GM for all obstacles produces overlapping images of obstacle in CPS. The empty area of CPS that is not occupied by obstacle images represents collision-free paths in Euclidian Space. A GM based on connection point in elliptic coordinate(${\theta}{\delta}$) is also developed in that the total length of path is depend only on the variable .delta.. Hence in EWS GM(elliptic work space geometry mapping), increasing .delta. and finding the value of .delta. for collision-free path, the shortest path can be searched without carring out whole GM. The GM of obstacles expersses all possible collision-free path as empty spaces in CPS. If there is no empty space available in CPS, it indicates that path planning is not possible with given number of connection points, i.e. path planning is failed, and it is necessary to increase the number of connection point. A general case collision-free path planning is possible by appling GM to configuration space obstacles. Simulation of GM of obstacles in Euclidian space is carried out to measure performance of algorithm and the resulting obstacle images are reported.

• The Journal of Korea Robotics Society
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• v.16 no.2
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• pp.112-121
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• 2021

Unlike a typical small-sized robot navigating in a free space, an autonomous vehicle has to travel in a designated road which has lanes to follow and traffic rules to obey. High-Definition (HD) maps, which include road markings, traffic signs, and traffic lights with high location accuracy, can help an autonomous vehicle avoid the need to detect such challenging road surroundings. With space constraints and a pre-built HD map, a new type of path planning algorithm can be conceived as a substitute for conventional grid-based path planning algorithms, which require substantial planning time to cover large-scale free space. In this paper, we propose an obstacle-avoiding, cost-based planning algorithm in a continuous space that aims to pursue a globally-planned path with the help of HD map information. Experimentally, the proposed algorithm is shown to outperform other state-of-the-art path planning algorithms in terms of computation complexity in a typical urban road setting, thereby achieving real-time performance and safe avoidance of obstacles.

• 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.

• Proceedings of the KIEE Conference
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• 1997.11a
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• pp.576-580
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• 1997

This paper presents a path planning algorithm for biped walking robot in 3-D workspace. Since the biped walking robot can generate path on some 3-D obstacles that cannot generate path in case of mobile robot, we have to make a new path planning algorithms. A 3-D-to-2-D mapping algorithm is proposed and two kinds of path planning algorithms are also proposed. They make it easier to generate an efficient path for biped walking robot under given environment. Some simulation results are shown to prove the effectiveness of proposed algorithms.

• The Journal of Korea Robotics Society
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• v.2 no.2
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• pp.183-190
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• 2007

The most important thing for navigation of a mobile robot is to find the most suitable path and avoid the obstacles in the static and dynamic environment. This paper presents a method to search the optimal path in start space extended to time domain with considering a velocity and a direction of moving obstacles. A modified version of $A^*$ algorithm has been applied for path planning in this work and proposed a method of path search to avoid a collision with moving obstacle in space-tim domain with a velocity and an orientation of obstacles. The velocity and the direction for moving obstacle are assumed as linear form. The simulation result shows that a mobile robot navigates safely among moving obstacles of constant linear velocity. This work can be applied for not only a moving robot but also a legged humanoid robot and all fields where the path planning is required.

• Proceedings of the KIEE Conference
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• 1998.07b
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• pp.715-718
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• 1998

There are a lot of paths which connect between the mobile robot and the goat point. To make a mobile robot arrive at the goal point fastly, The optimal path is needed and a path palnning is necessary. In this paper, we propose a new method of path planning to find a path for mobile robot. It is based on Ginetic Algorithm for serching the optimal grobal path planning. Simulations show the efficiency for the grobal path planning.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.1208-1211
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• 1996

In this paper, an efficient and robust robot path planning technique is discussed. Concentric Ripple Edge Evaluation and Progression( CREEP ) algorithm[1] has been elaborated and expanded to carry out 3-D path planning. Like the 2-D case, robot can always find a path, if one exists, in a densely cluttered, unknown and unstructured 3-D obstacle environment. 3-D space in which the robot is expected to navigate is modeled by stacking cubic cells. The generated path is resolution optimal once the terrain is fully explored by the robot or all the information about the terrain is given. Path planning times are significantly reduced by local path update. Accuracy and efficiency of wave propagation in CREEP algorithm are achieved by virtual concentric sphere wave propagation. Simulations in 2-D and 3-D spaces are performed and excellent results are demonstrated.

• Journal of Computational Design and Engineering
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• v.3 no.2
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• pp.132-139
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• 2016

In this paper, a minimum time path planning strategy is proposed for multi points manufacturing problems in drilling/spot welding tasks. By optimizing the travelling schedule of the set points and the detailed transfer path between points, the minimum time manufacturing task is realized under fully utilizing the dynamic performance of robotic manipulator. According to the start-stop movement in drilling/spot welding task, the path planning problem can be converted into a traveling salesman problem (TSP) and a series of point to point minimum time transfer path planning problems. Cubic Hermite interpolation polynomial is used to parameterize the transfer path and then the path parameters are optimized to obtain minimum point to point transfer time. A new TSP with minimum time index is constructed by using point-point transfer time as the TSP parameter. The classical genetic algorithm (GA) is applied to obtain the optimal travelling schedule. Several minimum time drilling tasks of a 3-DOF robotic manipulator are used as examples to demonstrate the effectiveness of the proposed approach.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.4
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• pp.493-498
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• 2004

A novel approach for path planning of a polygonal robot is presented. Traditional path planners perform extensive geometric searching to find the optimal path or to prove that there is no solution. The computation required to prove that there is no solution is equivalent to exhaustive search of the motion space, which is typically very expensive. Humans seems to use a set of several different path planning strategies to analyse the situation of the obstacles in the environment, and quickly recognize whether the path-planning problem is easy to solve, hard to solve or has no solution. This human path-planning strategies have motivated the development of the presented algorithm that combines qualitative shape reasoning and exhaustive geometric searching to speed up the path planning process. It has three planning stages consisting of identification of no-solution cases based on an enclosure test, a qualitative reasoning stage, and finally a complete search algorithm in case the previous two stages cannot determine of the existence of a solution path.

• The Journal of Korea Robotics Society
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• v.18 no.1
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• pp.1-9
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• 2023

This paper presents an optimal path planning strategy for aerial searching and surveying of a user-designated area using multiple Unmanned Aerial Vehicles (UAVs). The method is designed to deal with a single unseparated polygonal area, regardless of polygonal convexity. By defining the search area into a set of grids, the algorithm enables UAVs to completely search without leaving unsearched space. The presented strategy consists of two main algorithmic steps: cellular decomposition and path planning stages. The cellular decomposition method divides the area to designate a conflict-free subsearch-space to an individual UAV, while accounting the assigned flight velocity, take-off and landing positions. Then, the path planning strategy forms paths based on every point located in end of each grid row. The first waypoint is chosen as the closest point from the vehicle-starting position, and it recursively updates the nearest endpoint set to generate the shortest path. The path planning policy produces four path candidates by alternating the starting point (left or right edge), and the travel direction (vertical or horizontal). The optimal-selection policy is enforced to maximize the search efficiency, which is time dependent; the policy imposes the total path-length and turning number criteria per candidate. The results demonstrate that the proposed cellular decomposition method improves the search-time efficiency. In addition, the candidate selection enhances the algorithmic efficacy toward further mission time-duration reduction. The method shows robustness against both convex and non-convex shaped search area.