| 摘 要: 自导航机器人(Automated Guided Vehicle，AGV)是现代产业不可或缺的重要组成部分。本文对AGV路径规划算法进行研究和设计。首先，采用栅格法对AGV运行环境建模，并制定约束规则以解决多AGV的冲突问题。其次，引入双非线性收敛因子和强制驱散机制对经典WOA进行改进。再次，定义适应度函数，并将改进的WOA应用于路径规划算法。仿真和实验结果表明，基于改进WOA的规划算法能够有效简化路径复杂度、降低机器人控制难度。 |
| 关键词: 群智能算法；鲸优化算法；自导航机器人；路径规划 |
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中图分类号: TP391
文献标识码: A
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| 基金项目: 天津市企业科技特派员项目(19JCTPJC52300)；教育部产学合作协同育人项目(201901198040)；天津市虚拟仿真实验教学建设项目资助. |
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| Research on Path Planning of Automatic Guided Vehicle based on Whale Optimization Algorithm |
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ZHU Cheng
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(School of Information Engineering, Tianjin University of Commerce, Tianjin 300134, China)
zhucheng@tjcu.edu.cn
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| Abstract: Automated Guided Vehicle (AGV) is an indispensable part of modern industry. This paper considers the AGV path planning algorithm. First, the grid method is used to model the AGV operating environment, and constraint rules are formulated to solve the conflict problem of multiple AGVs. Secondly, dual nonlinear convergence factors and forced dispersal mechanism are introduced to improve the classic Whale Optimization Algorithm (WOA). Third, we define the fitness function and apply the improved WOA to the path planning algorithm. Simulation and experimental results show that the planning algorithm based on improved WOA can effectively simplify the path complexity and reduce the difficulty of robot control. |
| Keywords: swarm intelligence algorithm; whale optimization algorithm; automatic guided vehicle; path planning |
