| 基于神经网络和遗传算法的机器人动态避障路径规划 |
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| 引用本文： | 陈华华,杜歆,顾伟康. 基于神经网络和遗传算法的机器人动态避障路径规划[J]. 传感技术学报, 2004, 17(4): 551-555 |
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| 作者姓名： | 陈华华 杜歆 顾伟康 |
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| 作者单位： | 浙江大学信息与电子工程系,杭州,310027;浙江大学信息与电子工程系,杭州,310027;浙江大学信息与电子工程系,杭州,310027 |
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| 基金项目： | 国家自然科学基金，浙江省自然科学基金 |
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| 摘 要： | 文中提出了基于神经网络和遗传算法的动态环境下机器人动态避障路径规划方法,机器人工作空间动态环境信息的神经网络模型,并利用该模型建立机器人动态避障与神经网络输出的关系,然后将需规划路径的二维编码简化成一维编码,并把动态避障要求和最短路径要求融合成一个适应度函数.通过对算法进行实验仿真,结果表明提出的动态路径规划方法是正确和有效的.
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| 关 键 词： | 神经网络 遗传算法 路径规划 动态避障 适应度函数 |
| 文章编号： | 1004-1699(2004)04-0551-05 |
| 修稿时间： | 2004-05-12 |
Neural Network and Genetic Algorithm Based Dynamic ObstacleAvoidance and Path Planning for A Robo |
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| CHEN Huahu,DU Xin,GU Weik. Neural Network and Genetic Algorithm Based Dynamic ObstacleAvoidance and Path Planning for A Robo[J]. Journal of Transduction Technology, 2004, 17(4): 551-555 |
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| Authors: | CHEN Huahu DU Xin GU Weik |
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| Affiliation: | Department of Information Science and Electronics Engineering , Zhejiang University , Hangzhou 310027 , C |
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| Abstract: | A method of dynamic obstacle avoidance and path planning based on neural network and genetic algorithm is proposed. The neural network model of dynamic environmental information in the workspace for a robot is constructed. Using this model, the relationship between dynamic obstacle avoidance and the output of the model is established. Then the two dimensional coding for the via points of the path is converted to one dimensional one and the fitness of both dynamic obstacle avoidance and the shortest distance are fused to a fitness function. The simulation result shows that the proposed method is correct and efficient. |
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| Keywords: | neural network genetic algorithm dynamic obstacle avoidance path planning fitness function |
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