• Korean Journal of Agricultural Science
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• v.42 no.1
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• pp.63-71
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• 2015

Path planning is an essential part for traveling and mowing of autonomous lawn mower tractors. Objectives of the paper were to analyze operation patterns by a skilled farmer, to extract and optimize waypoints, and to demonstrate generation of formatted planned path for autonomous lawn mower tractors. A 27-HP mower tractor was operated by a skilled farmer on grass fields. To measure tractor travel and operation characteristics, an RTK-GPS antenna with a 6-cm RMS error, an inertia motion sensing unit, a gyro compass, a wheel angle sensor, and a mower on/off sensor were mounted on the mower tractor, and all the data were collected at a 10-Hz rate. All the sensor data were transferred through a software program to show the status immediately on the notebook. Planned path was generated using the program parameter settings, mileage and time calculations, and the travel path was plotted using developed software. Based on the human operation patterns, path planning algorithm was suggested for autonomous mower tractor. Finally path generation was demonstrated in a formatted file and graphic display. After optimizing the path planning, a decrease in distance about 13% and saving of the working time about 30% was achieved. Field test data showed some overlap, especially in the turning areas. Results of the study would be useful to implement an autonomous mower tractor, but further research needs to improve the performance.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2022.11a
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• pp.351-356
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• 2022

Among the path planning methods used to generate the ship's path, the graph search-based method is widely used because it has the advantage of its completeness, optimality. In order to apply the graph-based search method to the berthing path plan, the deviation from the path must be minimized. Path following suitability should be considered essential, since path deviation during berthing can lead to collisions with berthing facilities. However, existing studies of graph search-based berthing path planning are dangerous for application to real-world navigation environments because they produce results with a course change just before berthing. Therefore, in this paper, we develop a cost function suitable for path following, and propose a 3D A* algorithm that applies it. In addition, in order to evaluate the suitability for the actual operating environment, the results of the path generation of the algorithm are compared with the trajectory of the data collected by manned operations.

• 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.

• 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].

• Transactions of the Korean Society of Mechanical Engineers A
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• v.36 no.6
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• pp.623-628
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• 2012

Conventional path planning methods have focused on the generation of an optimal shortest path to the goal. However, this optimal path cannot guarantee safe navigation, because it can often lead to a narrow area. Therefore, we propose a Coulomb's law-based safe path planning method that uses an information grid map. The information grid map includes four types of information: occupied, empty, guide, and dangerous areas. A safe path can be generated away from the dangerous area and close to the guide area by repulsive and attractive forces, respectively. Experiments and simulations show that the proposed method can generate paths inside the safe region and is useful for safe navigation.

• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.939-940
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• 2006

Many researches on path planning and obstacle avoidance for the fundamentals of mobile robot have been done. In this paper, we propose the algorithm of path planning and obstacle avoidance for mobile robot. We call the proposed method Random Access Sequence(RAS) method. RAS method using obstacle information from variable sensors is useful to get minimum path length to goal.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.7
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• pp.651-658
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• 2011

An efficient modified $D^*$ lite algorithm is suggested, which can perform online path planning for mobile robots in dynamic indoor environment. Online path planning should plan and execute alternately in a short time, and hence it enables the robot avoid unknown dynamic obstacles which suddenly appear on robot's path. Based on $D^*$ Lite algorithm, we improved representation of edge cost, heuristic function, and priority queue management, to build a modified $D^*$ Lite algorithm. Performance of the proposed algorithm is revealed via extensive simulation study.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.3
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• pp.267-274
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• 2012

We proposed the KPP (Korea university Path Planner) in our previous works. The KPP is the path planning scheme of a car-like mobile robot in parking environment. The objective of this paper is to investigate the advantage of the KPP through the quantitative and qualitative analysis compared with conventional RRT. For comparison, we proposed travel time for performance index. This paper shows that the KPP shows outstanding performances from the viewpoint of travel time and computational efficiency compared with RRT.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2000.11a
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• pp.274-277
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• 2000

In this paper we propose new algorithms of path planning and obstacle avoidance for an autonomous mobile robot with vision system. Distance variation is included in path planning to approach the target point and avoid obstacles well. The fuzzy rules are also applied to both trajectory planning and obstacle avoidance to improve the autonomy of mobile robot. It is shown by computer simulation that the proposed algorithm is working well.

• Journal of Aerospace System Engineering
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• v.14 no.5
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• pp.9-17
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• 2020

Mobile robots, including UAVs perform missions with limited fuel. Therefore, the energy-aware path planning is required to maximize efficiency when the robot is operated for a long time. In this study, we estimated the power consumption for each maneuver of a quadcopter UAV in the 3D environment and applied to the cost functions of D^⁎ Lite. The simulations were performed in a 3D environment that is similar to the industrial sites. The efficiency of path generation was high when the energy-aware path planning with simplified heuristic was applied. In addition, the energy-aware path was generated 19.3 times faster than the shortest path with a difference within 3.2%.