Surveillance Planning With Bézier Curves

Faigl, Jan; Váňa, Petr

doi:10.1109/lra.2018.2789844

Cited by 46 publications

(20 citation statements)

References 22 publications

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“…Unsupervised learning is used for pattern detection and descriptive detection. Many types of algorithms such as k‐mean clustering, 105 and quality threshold clustering 106 are used. For example, for searching the focal points, a hurdle reducing strategy with the basis of QT clustering was presented in Tartaglione and Ariola 107 .…”

Section: Routing Techniquesmentioning

confidence: 99%

Routing and collision avoidance techniques for unmanned aerial vehicles: Analysis, optimal solutions, and future directions

Sharma

Obaidat

Sharma

et al. 2020

Int J Communication

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SummaryRouting remains the most important problem to be explored, for discovering an ideal pathway in unmanned aerial vehicles (UAVs). Several problems for identifying and targeting location continue giving the immense motility of UAVs. In routing planning, optimum decisions have to be taken for several vital operations for solving the issues in UAVs. Many types of routing techniques of UAVs, which have been used for many years, have been analyzed in this paper. Routing techniques aim to provide striking‐free surroundings to the UAVs and not only to find an optimum path but also the smallest path. Routing techniques play a vital part in the development of a secured way in a minimal time to reach the ultimate destination and hence much needed. There are various routing techniques, real‐time applications of UAVs which are elaborated in this paper, namely, representative, cooperative, and noncooperative techniques. In UAV, collision avoidance is very important for the obstacle‐free environment. Collision avoidance techniques are discussed for a safe environment of UAV. Further, the UAVs network communication coverage and connectivity by these techniques are discussed. Finally, we discuss the security and connectivity and future directions in UAV.

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Section: Routing Techniquesmentioning

confidence: 99%

Routing and collision avoidance techniques for unmanned aerial vehicles: Analysis, optimal solutions, and future directions

Sharma

Obaidat

Sharma

et al. 2020

Int J Communication

View full text Add to dashboard Cite

show abstract

“…Collision-free and minimum-time motion planning for multiple vehicles has been studied over several decades. Various solutions, most utilizing geometrical approaches, have been proposed, where significant results based on path analysis theories have been reported [1][2][3][4][5][6][7][8][9][10][11]. These approaches analyzed path planning as a means of connecting two configurations (position and orientation) using spline curve parameters.…”

Section: Introductionmentioning

confidence: 99%

“…These approaches analyzed path planning as a means of connecting two configurations (position and orientation) using spline curve parameters. Issues of path optimality have been investigated as well, for instance, geometric shape-based approach [7][8][9][10][11][12], sampling-based approach [12], and potential field approach [13][14][15]. The application of acceleration limits to the generation of tangential velocity along the spline curves as a planned path was considered in several studies [3,7,8].…”

Section: Introductionmentioning

confidence: 99%

“…Several works [3,[7][8][9] demonstrated a good performance using such type of curves [3,[7][8][9]. Some considerations of using such curves include easiness to determine the tangentiality at each point on the path [3], flexibility in reshaping using at least one control point [7]], and trajectory smoothness [8,9,11]. Mostly, the path-planning issue in robotics considers the advantage of smoothness [3,[7][8][9]11].…”

Section: Introductionmentioning

confidence: 99%

“…Some considerations of using such curves include easiness to determine the tangentiality at each point on the path [3], flexibility in reshaping using at least one control point [7]], and trajectory smoothness [8,9,11]. Mostly, the path-planning issue in robotics considers the advantage of smoothness [3,[7][8][9]11]. Various optimization studies have employed this search method [33,[35][36][37][38][39][40], which uses particles whose motions are influenced by the set of fittest particles.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

PSO-based Minimum-time Motion Planning for Multiple Vehicles Under Acceleration and Velocity Limitations

Pamosoaji

Piao

Hong

2019

Int. J. Control Autom. Syst.

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This paper discusses a particle swarm optimization (PSO)-based motion-planning algorithm in a multiple-vehicle system that minimizes the traveling time of the slowest vehicle by considering, as constraints, the radial and tangential accelerations and maximum linear velocities of all vehicles. A class of continuous-curvature three-degree Bezier curves are selected as the basic shape of the vehicle trajectories to minimize the number of parameters required to express them mathematically. In addition, velocity profile generation using the local minimum of the radial-accelerated linear velocity profile, which reduces the calculation effort, is introduced. A new PSO-based search algorithm, called "particle-group-based PSO," is introduced to find the best combination of trajectories that minimizes the traveling time of the slowest vehicle. A particle group is designed to wrap up a set of particles representing each vehicle. The first and last two control points characterizing a curve are used as the state vector of a particle. Simulation results demonstrating the performance of the proposed method are presented. The main advantage of the proposed method is its minimization of the velocity-profile-generation time, and thereby, its maximization of the search time.

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Information Gathering Planning with Hermite Spline Motion Primitives for Aerial Vehicles with Limited Time of Flight

Dubeň

Pěnička

Saska

2019

Modelling and Simulation for Autonomous Systems

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Surveillance Planning With Bézier Curves

Cited by 46 publications

References 22 publications

Routing and collision avoidance techniques for unmanned aerial vehicles: Analysis, optimal solutions, and future directions

Routing and collision avoidance techniques for unmanned aerial vehicles: Analysis, optimal solutions, and future directions

PSO-based Minimum-time Motion Planning for Multiple Vehicles Under Acceleration and Velocity Limitations

Information Gathering Planning with Hermite Spline Motion Primitives for Aerial Vehicles with Limited Time of Flight

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