• ETRI Journal
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• v.43 no.6
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• pp.1013-1023
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• 2021

In this study, we propose a practical path planning method that combines the A^* search algorithm and minimum snap trajectory generation. The A^* search algorithm determines a set of waypoints to avoid collisions with surrounding obstacles from a starting to a destination point. Only essential waypoints (waypoints necessary to generate smooth trajectories) are extracted from the waypoints determined by the A^* search algorithm, and an appropriate time between two adjacent waypoints is allocated. The waypoints so determined are connected by a smooth minimum snap trajectory, a dynamically executable trajectory for the quadrotor. If the generated trajectory is invalid, we methodically determine when intermediate waypoints are needed and how to insert the points to modify the trajectory. We verified the performance of the proposed method by various simulation experiments and a real-world experiment in a forested outdoor environment.

• International Journal of Aeronautical and Space Sciences
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• v.8 no.2
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• pp.107-120
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• 2007

Coordination of multiple UAVs is an essential technology for various applications in robotics, automation, and artificial intelligence. In general, it includes 1) waypoints assignment and 2) trajectory generation. In this paper, we propose a new method for this problem. First, we modify the concept of the standard visibility graph to greatly improve the optimality of the generated trajectories and reduce the computational complexity. Second, we propose an efficient stochastic approach using simulated annealing that assigns waypoints to each UAV from the constructed visibility graph. Third, we describe a method to detect collision between two UAVs. FinallY, we suggest an efficient method of controlling the velocity of UAVs using A* algorithm in order to avoid inter-UAV collision. We present simulation results from various environments that verify the effectiveness of our approach.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.6
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• pp.526-530
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• 2011

This paper presents a new fuzzy model-based design approach for waypoints-tracking control of nonlinear underwater vehicles (UUVs) on a horizontal plane. The waypoints-tracking control problem is converted into the stabilization one for the error model between the given nonlinear UUV and the waypoints. By using the sector nonlinearity, the error model is modeled in Takagi-Sugeno's form. We then derive stabilization conditions for the error model in the format of linear matrix inequality. A numerical simulation is provided to illustrate the effectiveness of the proposed methodology.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.2
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• pp.402-408
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• 2017

This paper deals with a robust ${\mathfrak{H}}_{\infty}$ controller design problem for waypoints tracking of large displacement unmanned underwater vehicles (LDUUVs) in Takagi-Sugeno fuzzy form. The LDUUV model uses a rudder to control its horizontal motion. We determine the order of waypoints based on their priorities and consider only surge force. A fuzzy controller in state-feedback form is taken and its design condition of is represented in terms of linear matrix inequalities. A numerical simulation is included to show the effectiveness of the theoretical development.

• 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.14 no.6
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• pp.1457-1463
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• 2018

In recent times, Natural User Interface/Natural User Experience (NUI/NUX) technology has found widespread application across a diverse range of fields and is also utilized for controlling unmanned aerial vehicles (UAVs). Even if the user controls the UAV by utilizing the NUI/NUX technology, it is difficult for the user to easily control the UAV. The user needs an autopilot to easily control the UAV. The user needs a flight path to use the autopilot. The user sets the flight path based on the waypoints. UAVs normally fly straight from one waypoint to another. However, if flight between two waypoints is in a straight line, UAVs may collide with obstacles. In order to solve collision problems, flight records can be utilized to adjust the generated path taking the locations of the obstacles into consideration. This paper proposes a natural path generation method between waypoints based on flight records collected through UAVs flown by users. Bayesian probability is utilized to select paths most similar to the flight records to connect two waypoints. These paths are generated by selection of the center path corresponding to the highest Bayesian probability. While the K-means algorithm-based straight-line method generated paths that led to UAV collisions, the proposed method generates paths that allow UAVs to avoid obstacles.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.2
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• pp.97-103
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• 2016

In this paper, a smartphone-controlled personal mobility system (PMS) with semi-autonomous navigation is developed. The proposed PMS moves to waypoints and then reaches the destination where the waypoints and destination are selected by the user using Google maps in a smartphone. The hardware environment consists of a GPS (Global Positioning System) in the smartphone and a compass sensor. In addtion, while it is moving in autonomous mode, the user can intervene and change the direction and speed of the PMS in order to avoid obstacles that may be encountered accidentally in a dynamic environment. That is why it is called "semi-autonomous navigation". Experimental results showed that the proposed PMS is effectively able to migrate to the waypoints and destination in both autonomous and manual modes.

• Journal of the Korea Institute of Military Science and Technology
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• v.19 no.6
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• pp.779-788
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• 2016

In this paper, a global path replanning method is proposed in order to plan a global path minimizing the risk of the unmanned vehicle on the battlefield. We first introduce 4D environmental information consisting of mobility, visibility, kill, and hit attributes, and a unified threat map and a mobility map are defined by the four attributes. Using the mobility map, the unmanned vehicle can find the shortest path on the traversable area. And then taking into account the deterrent according to the type of the unmanned vehicle on the integrated threat map, the vehicle can generate a route to suppress or avoid the threat of enemy as well. Moreover, we present a waypoints bypassing method to exclude unnecessary waypoints rather than the mission point when planning paths for the multiple waypoints.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.31 no.8
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• pp.50-57
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• 2003

Controlling rotorcraft to fly precisely through multiple, irregularly, and closely spaced waypoints is a common and practical mission. However, finding an optimal trajectory for this kind of mission is quite challenging. Usability of traditional approaches such as inverse control or direct methods to this kind of problem is limited because of either limitation on the specification of the constraints or requirement of extensive computation time. This paper proposes a method that can easily compute the full trajectory and control history for rotorcraft to pass through waypoints while satisfying other general constraints of states such as velocities and attitudes on each waypoint. The proposed method is applied to rotorcraft guidance problems of slalom and linear trajectory in the middle of general curved trajectory. The algorithm is test for various situations and demonstrates its usability.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.37 no.11
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• pp.1104-1111
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• 2009

In the low altitude, mission of the aircraft is restricted by a variety of threats such as anti-air missiles and terrain obstacles. Especially, aircraft have always a risk of ground collision near terrain. In this study, to effectively solve this problem, we developed the flight path generation algorithm that is considered the terrain avoidance. In this flight path generation algorithm, waypoints that should be passed by the UAV are selected first. The waypoints are located in the middle of the terrain obstacles. Then, physically meaningful waypoints sets are classified by Dijkstra algorithm. The optimal waypoint guidance law based on the optimal control theory is applied to produce trajectory candidates. And finally the minimum control energy trajectory is determined.