{"title":"大型环境双导向移动机器人的快速ICP-SLAM","authors":"R. Tiar, M. Lakrouf, O. Azouaoui","doi":"10.1109/ICAR.2015.7251519","DOIUrl":null,"url":null,"abstract":"This paper describes the implementation of a local ICP-SLAM (Iterative Closest Point - Simultaneous Localization and Mapping) to improve the method presented in [1] to become faster. The ICP algorithm is known as a method that requires more computation time when the environment grows leading to poor results for both localization and mapping. Therefore, the ICP-SLAM is not recommended to use in real time for large environments. To overcome this problem, a local ICP-SLAM is introduced which is based on the partition of the environment on smaller parts. This method is implemented and tested on the car-like mobile robot “Robucar”. It allows the optimization of the computation time and localization accuracy. The experimental results show the effectiveness of the proposed local ICP-SLAM compared to the method in [1].","PeriodicalId":432004,"journal":{"name":"2015 International Conference on Advanced Robotics (ICAR)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2015-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":"{\"title\":\"Fast ICP-SLAM for a bi-steerable mobile robot in large environments\",\"authors\":\"R. Tiar, M. Lakrouf, O. Azouaoui\",\"doi\":\"10.1109/ICAR.2015.7251519\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper describes the implementation of a local ICP-SLAM (Iterative Closest Point - Simultaneous Localization and Mapping) to improve the method presented in [1] to become faster. The ICP algorithm is known as a method that requires more computation time when the environment grows leading to poor results for both localization and mapping. Therefore, the ICP-SLAM is not recommended to use in real time for large environments. To overcome this problem, a local ICP-SLAM is introduced which is based on the partition of the environment on smaller parts. This method is implemented and tested on the car-like mobile robot “Robucar”. It allows the optimization of the computation time and localization accuracy. The experimental results show the effectiveness of the proposed local ICP-SLAM compared to the method in [1].\",\"PeriodicalId\":432004,\"journal\":{\"name\":\"2015 International Conference on Advanced Robotics (ICAR)\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-07-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"10\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 International Conference on Advanced Robotics (ICAR)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICAR.2015.7251519\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 International Conference on Advanced Robotics (ICAR)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICAR.2015.7251519","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Fast ICP-SLAM for a bi-steerable mobile robot in large environments
This paper describes the implementation of a local ICP-SLAM (Iterative Closest Point - Simultaneous Localization and Mapping) to improve the method presented in [1] to become faster. The ICP algorithm is known as a method that requires more computation time when the environment grows leading to poor results for both localization and mapping. Therefore, the ICP-SLAM is not recommended to use in real time for large environments. To overcome this problem, a local ICP-SLAM is introduced which is based on the partition of the environment on smaller parts. This method is implemented and tested on the car-like mobile robot “Robucar”. It allows the optimization of the computation time and localization accuracy. The experimental results show the effectiveness of the proposed local ICP-SLAM compared to the method in [1].
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