• Proceedings of the Korea Contents Association Conference
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• 2016.05a
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• pp.295-296
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• 2016

UAV를 이용하여 정사영상과 수치지도제작을 위해서는 촬영계획대로 촬영해야 한다. 그러나 풍속, 풍향 및 시스템의 결함으로 촬영정확도가 저하된다. 저가 UAV의 waypoint기능을 활용한다면 다소 실수를 줄일 수 있다. 본 연구에서는 waypoint기능을 이용하여 비행정확도를 평가하고 모의촬영을 통해 촬영정확도를 확인하고자 한다.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.7
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• pp.664-668
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• 2012

Hierarchical IPP (Integrated Path Planning) combining the GPP (Global Path Planner) and the LPP (Local Path Planner) is interesting the researches who study about the mobile vehicle in recent years. However, in this study, there is the path mismatch problem caused by the difference in the map information available to both path planners. If ever a part of the path that was found by the GPP is available to mobile vehicle, the part may be unavailable when the mobile vehicle generates the local path with its built-in sensors while the vehicle moves. This paper proposed the TWR (Temporal Waypoint Reviser) to solve the path mismatch problem of the hierarchical IPP. The results of simulation provide the performance of the IPP with the TWR by comparing with other path planners.

• International Journal of Aeronautical and Space Sciences
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• v.11 no.2
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• pp.136-144
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• 2010

This paper presents an algorithm for planning waypoints for the operation of a surveillance mission using cooperative unmanned aerial vehicles (UAVs) in a given map. This algorithm is rather simple and intuitive; therefore, this algorithm is easily applied to actual scenarios as well as easily handled by operators. It is assumed that UAVs do not possess complete information about targets; therefore, kinematics, intelligence, and so forth of the targets are not considered when the algorithm is in operation. This assumption is reasonable since the algorithm is solely focused on a surveillance mission. Various parameters are introduced to make the algorithm flexible and adjustable. They are related to various cost functions, which is the main idea of this algorithm. These cost functions consist of certainty of map, waypoints of co-worker UAVs, their own current positions, and a level of interest. Each cost function is formed by simple and intuitive equations, and features are handled using the aforementioned parameters.

• Journal of Biosystems Engineering
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• v.38 no.1
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• pp.1-8
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• 2013

Purpose: Path planning and tracking algorithms applicable to various agricultural operations, such as tillage, planting, and spraying, are needed to generate steering angles for auto-guidance tractors to track a point ahead on the path. An optimal coverage path algorithm can enable a vehicle to effectively travel across a field by following a sequence of parallel paths with fixed spacing. This study proposes a path generation and tracking algorithm for an auto-guided Korean tractor with a tillage implement that generates a path with C-type turns and follows the generated path in a paddy field. A mathematical model was developed to generate a waypoint path for a tractor in a field. This waypoint path generation model was based on minimum tractor turning radius, waypoint intervals and LBOs (Limit of Boundary Offsets). At each location, the steering angle was calculated by comparing the waypoint angle and heading angle of the tractor. A path following program was developed with Labview-CVI to automatically read the waypoints and generate steering angles for the tractor to proceed to the next waypoint. A feasibility test of the developed program for real-time path tracking was performed with a mobile platform traveling on flat ground. The test results showed that the developed algorithm generated the desired path and steering angles with acceptable accuracy.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.2
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• pp.211-217
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• 2014

This paper addresses an algorithm of path planning for autonomous driving of a ground vehicle in waypoint navigation. The proposed algorithm is flexible in utilization under a large GPS positioning error and generates collision-free multiple paths while pursuing minimum traveling time. An optimal path reduces inefficient steering by minimizing lateral changes in generated waypoints along a path. Simulation results compare the proposed algorithm with the A* algorithm by manipulation of the steering wheel and traveling time, and show that the proposed algorithm realizes real-time obstacle avoidance by quick processing of path generation, and minimum time traveling by producing paths with small lateral changes while overcoming the very irregular positioning error from the GPS.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.49 no.7
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• pp.557-564
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• 2021

This paper describes an automatic landing approach algorithm for fixed-wing UAVs using waypoint guidance. The proposed algorithm utilizes simple 2D Dubin's vehicle pre-simulations in planning the waypoints for landing approach. The remaining time to reach the runway is also estimated in the pre-simulation, and it is used for altitude control. The performance of the designed algorithm was verified by simulations and flight tests.

• Transactions of the Korean Society of Automotive Engineers
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• v.22 no.3
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• pp.241-249
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• 2014

This paper presents a path planning algorithm of an autonomous vehicle (ADAM III) for collision avoidance in the presence of multiple obstacles. Under the requirements that a low-cost GPS is used and its computation should be completed with a sampling time of sub-second, heading angle estimation is proposed to improve performance degradation of its measurement and a hierarchical structure for path planning is used. Once it is decided that obstacle avoidance is necessary, the path planning consists in three steps: waypoint generation, trajectory candidate generation, and trajectory selection. While the waypoints and the corresponding trajectory candidates are generated based on position of obstacles, the final desired trajectory is determined with considerations of kinematic constraints as well as an optimal condition in a term of lateral deviation. Finally the proposed algorithm was validated experimentally through field tests and its demonstration was performed in Autonomous Vehicle Competition (AVC) 2013.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.12
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• pp.1238-1243
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• 2008

This paper presents an HILS(Hardware in the Loop Simulations) based experimental study for the UAV's flight trajectory planning/generation algorithms and guidance/control laws. For the various mission that is loaded on each waypoint, proper trajectory planning and generation algorithms are applied to achieve best performances. Specially, the 'smoothing path' generation and the 'tangent orbit path' guidance laws are presented for the smooth path transitions and in-circle loitering mission, respectively. For the control laws that can minimize the effects of side wind, side slip angle($\beta$) feedback to the rudder scheme is implemented. Finally, being implemented on real hardwares, all the proposed algorithms are validated with integrations of hardware and software altogether via HILS.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.42 no.2
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• pp.127-133
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• 2014

This paper proposes a determination method of waypoints to maximize the survivability of a UAV. Voronoi diagram which is used for the initial selection of waypoint candidates is the most widely used path planning technique to avoid the threat as far as possible when the location and strength of the threat are given. But if threat strength is different each other and flight path is constrained along with straight lines, Voronoi diagram has limitations in real applications. In this study, the initial waypoints obtained from Voronoi diagram are optimized considering the shape of each threat. Here, a waypoint is optimized while adjacent waypoints are fixed. By repeating this localized optimization until whole waypoints are converged, computation time for finding the best waypoints is greatly reduced.

• Journal of Information Processing Systems
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• v.16 no.6
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• pp.1324-1342
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• 2020

Various modified algorithms of rapidly-exploring random tree (RRT) have been previously proposed. However, compared to the RRT algorithm for collision avoidance with global and static obstacles, it is not easy to find a collision avoidance and local path re-planning algorithm for dynamic obstacles based on the RRT algorithm. In this study, we propose boundary-RRT*, a novel-algorithm that can be applied to aerial vehicles for collision avoidance and path re-planning in a three-dimensional environment. The algorithm not only bounds the configuration space, but it also includes an implicit bias for the bounded configuration space. Therefore, it can create a path with a natural curvature without defining a bias function. Furthermore, the exploring space is reduced to a half-torus by combining it with simple right-of-way rules. When defining the distance as a cost, the proposed algorithm through numerical analysis shows that the standard deviation (σ) approaches 0 as the number of samples per unit time increases and the length of epsilon ε (maximum length of an edge in the tree) decreases. This means that a stable waypoint list can be generated using the proposed algorithm. Therefore, by increasing real-time performance through simple calculation and the boundary of the configuration space, the algorithm proved to be suitable for collision avoidance of aerial vehicles and replanning of local paths.