Qingchun Meng, Sng Honglian, Changjiu Zhou, Hongbo Ji, Dong Hao
{"title":"基于遗传算法的智能控制——以移动机器人为例","authors":"Qingchun Meng, Sng Honglian, Changjiu Zhou, Hongbo Ji, Dong Hao","doi":"10.1109/IJSIS.1998.685455","DOIUrl":null,"url":null,"abstract":"The application of genetic algorithms to mobile robot dynamic control and path planning is described. A new genetic strategy, GASC (genetic algorithm with symmetric code), is used in this application. Robot dynamic control based on dynamic model and its path planning are converted into an optimization problem with some constraints, then GASC is employed to solve this problem. In GASC, some new genetic techniques have been put forward. A genetic strategy is employed in the robot system's intelligent control. The simulation results obtained show that these techniques are indispensable to enhance the performance of our genetic strategy. GASC out performs the traditional genetic algorithms greatly in control find path planning of a mobile robot. The population of GAs based on symmetric codes theory in our generic strategy can automatically satisfy the velocities constraints at the final point in a robot path.","PeriodicalId":289764,"journal":{"name":"Proceedings. IEEE International Joint Symposia on Intelligence and Systems (Cat. No.98EX174)","volume":"57 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1998-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Intelligent control based on genetic algorithms-case study on mobile robot\",\"authors\":\"Qingchun Meng, Sng Honglian, Changjiu Zhou, Hongbo Ji, Dong Hao\",\"doi\":\"10.1109/IJSIS.1998.685455\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The application of genetic algorithms to mobile robot dynamic control and path planning is described. A new genetic strategy, GASC (genetic algorithm with symmetric code), is used in this application. Robot dynamic control based on dynamic model and its path planning are converted into an optimization problem with some constraints, then GASC is employed to solve this problem. In GASC, some new genetic techniques have been put forward. A genetic strategy is employed in the robot system's intelligent control. The simulation results obtained show that these techniques are indispensable to enhance the performance of our genetic strategy. GASC out performs the traditional genetic algorithms greatly in control find path planning of a mobile robot. The population of GAs based on symmetric codes theory in our generic strategy can automatically satisfy the velocities constraints at the final point in a robot path.\",\"PeriodicalId\":289764,\"journal\":{\"name\":\"Proceedings. IEEE International Joint Symposia on Intelligence and Systems (Cat. No.98EX174)\",\"volume\":\"57 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1998-03-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings. IEEE International Joint Symposia on Intelligence and Systems (Cat. No.98EX174)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IJSIS.1998.685455\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings. IEEE International Joint Symposia on Intelligence and Systems (Cat. No.98EX174)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IJSIS.1998.685455","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Intelligent control based on genetic algorithms-case study on mobile robot
The application of genetic algorithms to mobile robot dynamic control and path planning is described. A new genetic strategy, GASC (genetic algorithm with symmetric code), is used in this application. Robot dynamic control based on dynamic model and its path planning are converted into an optimization problem with some constraints, then GASC is employed to solve this problem. In GASC, some new genetic techniques have been put forward. A genetic strategy is employed in the robot system's intelligent control. The simulation results obtained show that these techniques are indispensable to enhance the performance of our genetic strategy. GASC out performs the traditional genetic algorithms greatly in control find path planning of a mobile robot. The population of GAs based on symmetric codes theory in our generic strategy can automatically satisfy the velocities constraints at the final point in a robot path.