{"title":"基于gpu的基于采样的运动规划碰撞检测","authors":"Jaeshik Yoon, Jae-Han Park, M. Baeg","doi":"10.1109/URAI.2013.6677345","DOIUrl":null,"url":null,"abstract":"This paper presents GPU-based collision detection method that accelerates collision queries for sampling-based motion planning. This approach uses many-core GPUs. To take advantage of a many-core GPU, kinematic and collision detection is calculated by the GPU. The experimental results indicate that this approach can result in a ten-fold faster performance than when using a CPU.","PeriodicalId":431699,"journal":{"name":"2013 10th International Conference on Ubiquitous Robots and Ambient Intelligence (URAI)","volume":"79 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"GPU-based collision detection for sampling-based motion planning\",\"authors\":\"Jaeshik Yoon, Jae-Han Park, M. Baeg\",\"doi\":\"10.1109/URAI.2013.6677345\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents GPU-based collision detection method that accelerates collision queries for sampling-based motion planning. This approach uses many-core GPUs. To take advantage of a many-core GPU, kinematic and collision detection is calculated by the GPU. The experimental results indicate that this approach can result in a ten-fold faster performance than when using a CPU.\",\"PeriodicalId\":431699,\"journal\":{\"name\":\"2013 10th International Conference on Ubiquitous Robots and Ambient Intelligence (URAI)\",\"volume\":\"79 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-12-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 10th International Conference on Ubiquitous Robots and Ambient Intelligence (URAI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/URAI.2013.6677345\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 10th International Conference on Ubiquitous Robots and Ambient Intelligence (URAI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/URAI.2013.6677345","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
GPU-based collision detection for sampling-based motion planning
This paper presents GPU-based collision detection method that accelerates collision queries for sampling-based motion planning. This approach uses many-core GPUs. To take advantage of a many-core GPU, kinematic and collision detection is calculated by the GPU. The experimental results indicate that this approach can result in a ten-fold faster performance than when using a CPU.
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