UAV Path Planning in Mixed‐Obstacle Environment via Artificial Potential Field Method Improved by Additional Control Force

Luo, Guan-chen; Yu, Jianqiao; Mei, Yuesong; Zhang, Siyu

doi:10.1002/asjc.960

Cited by 38 publications

(27 citation statements)

References 27 publications

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“…The traditional path planning methods mainly include artificial potential field methods [31], Dijkstra algorithm [32], A * algorithm [33], and so on. Path planning is an NP-hard problem.…”

Section: Route Optimizationmentioning

confidence: 99%

Cold Chain Logistics Path Optimization via Improved Multi-Objective Ant Colony Algorithm

Zhao

Gui

et al. 2020

IEEE Access

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In order to improve the performance and change the current situation of the cost minimization model widely used in the cold chain logistics distribution process, a multi-objective optimization model based on cost, carbon emissions and customer satisfaction is proposed. Considering the characteristic of this proposed optimization model, we design an improved ant colony algorithm with a multi-objective heuristic function to solve it, termed as ACOMO. Experimental results show that the proposed ACOMO can effectively solve the vehicle routing problem of the multi-objective optimization model, and outperforms the classic ant colony algorithms, resulting in more Pareto optimal solutions. It offers an environmentally friendly distribution solution for the problem. Specifically, the distribution path obtained by the improved ant colony algorithm manages to achieve the above multiple goals, including reduction of distribution costs and carbon emissions, and improvement of customer satisfaction. In addition, compared with a single-target model that only provides one single distribution route to cost minimization, multi-objective optimization can provide a variety of distribution route options for logistics companies in practice. Finally, through the sensitivity analysis of temperature changes and cargo damage coefficients, the proposed system successfully provides reference for the optimization of the path of cold chain logistics enterprises, and promotes logistics enterprises to effectively arrange their work and to be more socially responsible. INDEX TERMS Cold chain logistics, path optimization, multi-objective optimization, carbon constraints, customer satisfaction.

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“…The traditional path planning methods mainly include artificial potential field methods [31], Dijkstra algorithm [32], A * algorithm [33], and so on. Path planning is an NP-hard problem.…”

Section: Route Optimizationmentioning

confidence: 99%

Cold Chain Logistics Path Optimization via Improved Multi-Objective Ant Colony Algorithm

Zhao

Gui

et al. 2020

IEEE Access

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“…When the actual distance between formation members meet the requirement of d ij < d e < θ d , The potential energy [25] between formations is mainly repulsive, and the perturbation matrix can be launched as…”

Section: ) Definition Of Potential Energy Field Between Uav and Obstmentioning

confidence: 99%

“…The search step varies dynamically according to the distance between the node and the threat, as shown in Fig.7, In the case threats, the adaptive step size can avoid re-selecting the sampling points, which saves the search space. The formula for changing the adaptive step size shown as (25) In (25), ρ max is the maximum search step. ρ min is the minimum search step, D is the distance between the node and the threat.…”

Section: A Ibi-rrt Algorithmmentioning

confidence: 99%

A Method of Trajectory Planning for Unmanned Aerial Vehicle Formation Based on Fluid Dynamic Model

2020

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This paper mainly studies the obstacle avoidance and rapid reconstruction of UAV formations. A hybrid trajectory planning algorithm based on potential field fluid dynamic model and bidirectional fast search random tree is proposed to improve the ability of UAV formation to adapt to complex dynamic environment. Firstly, a dynamic system mathematical model based on fluid potential energy field is proposed; and the obstacle potential energy function and potential energy function between the formations modify the disturbance flow field. Secondly, IBi-directional Rapidly Exploring Random Tree (IBi-RRT) algorithm with adaptive step size is scheduled to solve the dispersive and convergent streamlines of disturbed flow field and to plan the trajectory. This method can clarify the flow field streamlines by adaptive step size combined with rolling detection method, which greatly improves the formation's ability to avoid dynamic threats. The experimental results show that the proposed improved fluid potential energy field dynamic system and IBi-RRT hybrid trajectory planning algorithm with adaptive step size can effectively improve the adaptive ability of UAV formation to the dynamic environment, and can plan the ideal trajectory in response to unexpected situations. INDEX TERMS Complex environment, fluid potential energy field, obstacles avoidance, sudden threats.

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“…Although individual agents can be employed to accomplish various tasks, great benefits including low cost, robustness, scalability and easy maintenance can be achieved by multi‐agent coordination. Therefore, it owns broad applications, which include rendezvous, flocking, unmanned air vehicles, multi‐robot, complex networks and so on . Consensus, formation control, optimization, task assignment, and estimation are mainly studied in multi‐agent coordination, in which, the consensus problem has become a hot topic because of its wide applications.…”

Section: Introductionmentioning

confidence: 99%

Consensus Problem with a Reference State for Fractional‐Order Multi‐Agent Systems

Bai

Wen

Rahmani

et al. 2016

Asian Journal of Control

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In this paper, the consensus problem of fractional‐order multi‐agent systems with a reference state is studied under fixed directed communication graph. At the beginning, the convergence speeds of fractional‐order multi‐agent systems are investigated based on the Mittag‐Leffler function. Then, a common consensus control law and a consensus control law based on error predictor are proposed, and it is shown that the consensus tracking can be achieved using the above control laws when a communication graph has a directed spanning tree. Finally, the convergence speeds of fractional‐order systems are compared, and it is discovered that the convergence of systems is faster using the control law based on error predictor than using the common one.

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UAV Path Planning in Mixed‐Obstacle Environment via Artificial Potential Field Method Improved by Additional Control Force

Cited by 38 publications

References 27 publications

Cold Chain Logistics Path Optimization via Improved Multi-Objective Ant Colony Algorithm

Cold Chain Logistics Path Optimization via Improved Multi-Objective Ant Colony Algorithm

A Method of Trajectory Planning for Unmanned Aerial Vehicle Formation Based on Fluid Dynamic Model

Consensus Problem with a Reference State for Fractional‐Order Multi‐Agent Systems

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