A cellular automata model for indoor evacuation based on artificial potential field and ant colony algorithm

Ye, Zhiwei; Yin, Yujie; Zong, Xinlu; Wang, Mingwei; Jiang, Yingli

doi:10.1201/b19880-173

Cited by 4 publications

(1 citation statement)

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“…Wen et al [11] combined CACO algorithm with multi-objective optimization theory to solve the multiobjective path planning problem with multiple constraints. Ye et al [12] constructed comprehensive heuristic information to guide CACO algorithm search based on node potential feld direction and distance between node and target, which efectively improved algorithm's convergence performance and solution accuracy. Akbarimajd and Hassanzadeh [13] proposed a new CACO algorithm with hierarchical architecture, which realized path planning in an environment with convex and concave obstacles.…”

Section: Introductionmentioning

confidence: 99%

UAV Path Planning in Dynamical Environment: A Novel ICACO-IDWA Algorithm

Guo

Zhang

et al. 2022

Mathematical Problems in Engineering

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In this paper, a novel UAV path planning algorithm based on improved cellular ant colony algorithm and dynamic window algorithm (ICACO-IDWA) is proposed to solve the problem of dynamically changing threat during actual flight. The main innovations of this paper are as follows. (a) The hexagon grid method is proposed to model the UAV flight space, which solves the problem of inconsistent simulation time step. (b) A novel ICACO-IDWA algorithm is proposed. In the first stage, the optimal path is obtained by the improved cellular ant colony algorithm (ICACO). In the second stage, the improved dynamic window algorithm (IDWA) is used to optimize the optimal path considering dynamic threat. Through the algorithm, the UAV path planning with dynamic threat change is realized. Finally, simulation results verify the effectiveness of the proposed model and algorithm.

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Section: Introductionmentioning

confidence: 99%