Modified central force optimization (MCFO) algorithm for 3D UAV path planning

Chen, Yongbo; Yu, Jianqiao; Mei, Yuesong; Wang, Yafei; Su, Xiaolong

doi:10.1016/j.neucom.2015.07.044

Cited by 107 publications

(46 citation statements)

References 26 publications

(36 reference statements)

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“…Dubins defines the path as a combination of circle's arcs and lines tangent to them [28] [8]. In the waypoint-based case the sequence of points is commonly connected by straightlines [21] [60] or splines [84] [27]. The most generic approach is a continuous function parametrized by the virtual arc length [15] [4] [42].…”

Section: Path Following Problemmentioning

confidence: 99%

“…The resulting optimal path, which commonly seeks a compromise between a minim path length and a minimum control effort, will vary based on the problem requirements. Occasionally, between the path following and the path planning controllers the path smoothing block can be found [40] [21]. The task of this block is to smooth the path generated by the path planning algorithm considering the kinematic constrains of the vehicle.…”

Section: Introductionmentioning

confidence: 99%

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A Survey of Path Following Control Strategies for UAVs Focused on Quadrotors

Rubí

Pérez

Morcego

2019

J Intell Robot Syst

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The trajectory control problem, defined as making a vehicle follow a pre-established path in space, can be solved by means of trajectory tracking or path following. In the trajectory tracking problem a timed reference position is tracked. The path following approach removes any time dependence of the problem, resulting in many advantages on the control performance and design. An exhaustive review of path following algorithms applied to quadrotor vehicles has been carried out, the most relevant are studied in this paper. Then, four of these algorithms have been implemented and compared in a quadrotor simulation platform: Backstepping and Feedback Linearisation control-oriented algorithms and NLGL and Carrot-Chasing geometric algorithms.

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Section: Path Following Problemmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Survey of Path Following Control Strategies for UAVs Focused on Quadrotors

Rubí

Pérez

Morcego

2019

J Intell Robot Syst

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“…The path following problem is defined as making the quadrotor follow a pre-stablished path in space. The reference path can be given using different approaches such as with waypoints [13] [8], dubins paths [14] [15] or splines [16] [17]. In this paper, a parametrized function of the three position coordinates is used to define the desired path:…”

Section: B Path Following Problemmentioning

confidence: 99%

Adaptive Nonlinear Guidance Law Using Neural Networks Applied to a Quadrotor

Rubí

Morcegol

Pérez

2019

2019 IEEE 15th International Conference on Control and Automation (ICCA)

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The NonLinear Guidance Law (NLGL) is a geometric algorithm commonly employed to solve the path following problem on different unmanned vehicles. NLGL is simple (does no depend on the model of the vehicle), effective and has only one tunning parameter. Its control parameter (L) depends on various factors, such as the velocity of the vehicle, the shape of the reference path and the dynamics of the vehicle. This paper analyses the effect of parameter L on the performance of NLGL when it is applied to a quadrotor vehicle. An Adaptive NLGL, which includes a velocity reduction term, is proposed. Stability proofs are given. Simulation results show that the proposed algorithm enhances the performance of the standard NLGL. Furthermore, it has no parameters to tune.

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“…Several global path planning algorithms have been proposed for enhancing UAV autonomy in an airspace for various missions [14][15][16][17][18][19][20][21][22][23][24][25][26][27]. The pathfinding process is mainly comprised of three key-elements; setting up a suitable environment (e.g., a graph representation of an environment), a search algorithm that explores the graph, and a heuristic function (e.g., distance and energy, etc.)…”

Section: Introductionmentioning

confidence: 99%

A Fast Global Flight Path Planning Algorithm Based on Space Circumscription and Sparse Visibility Graph for Unmanned Aerial Vehicle

Majeed

Lee

2018

Electronics

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This paper proposes a new flight path planning algorithm that finds collision-free, optimal/near-optimal and flyable paths for unmanned aerial vehicles (UAVs) in three-dimensional (3D) environments with fixed obstacles. The proposed algorithm significantly reduces pathfinding computing time without significantly degrading path lengths by using space circumscription and a sparse visibility graph in the pathfinding process. We devise a novel method by exploiting the information about obstacle geometry to circumscribe the search space in the form of a half cylinder from which a working path for UAV can be computed without sacrificing the guarantees on near-optimality and speed. Furthermore, we generate a sparse visibility graph from the circumscribed space and find the initial path, which is subsequently optimized. The proposed algorithm effectively resolves the efficiency and optimality trade-off by searching the path only from the high priority circumscribed space of a map. The simulation results obtained from various maps, and comparison with the existing methods show the effectiveness of the proposed algorithm and verify the aforementioned claims.

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Modified central force optimization (MCFO) algorithm for 3D UAV path planning

Cited by 107 publications

References 26 publications

A Survey of Path Following Control Strategies for UAVs Focused on Quadrotors

A Survey of Path Following Control Strategies for UAVs Focused on Quadrotors

Adaptive Nonlinear Guidance Law Using Neural Networks Applied to a Quadrotor

A Fast Global Flight Path Planning Algorithm Based on Space Circumscription and Sparse Visibility Graph for Unmanned Aerial Vehicle

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