{"title":"基于单向观测的协作机器人映射","authors":"Heoncheol Lee","doi":"10.1109/CASE48305.2020.9216996","DOIUrl":null,"url":null,"abstract":"This paper addresses the problem of cooperative mapping in multi-robot SLAM (simultaneous localization and mapping) with unknown initial relative poses among robots. If mutual observation measurements between robots are available when the robots encounter each other, the map transformation between robots for cooperative mapping can be easily obtained. However, the mutual observation measurements require too strict assumptions such as a rendezvous and encounters, which is not practical in real multi-robot systems. Moreover, the mutual observation measurements may contain inevitable errors due to the errors in sensors. To relax the assumption and correct the errors, this paper proposes a one-way observation-based technique for cooperative mapping. The proposed technique was tested with datasets obtained by real experiments with two mobile robots. Each robot was equipped with a sensor fusion system to observe other robots. The test results showed that the proposed technique worked well and improved the accuracy of the cooperatively produced map.","PeriodicalId":212181,"journal":{"name":"2020 IEEE 16th International Conference on Automation Science and Engineering (CASE)","volume":"65 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"One-Way Observation-based Cooperative Robot Mapping\",\"authors\":\"Heoncheol Lee\",\"doi\":\"10.1109/CASE48305.2020.9216996\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper addresses the problem of cooperative mapping in multi-robot SLAM (simultaneous localization and mapping) with unknown initial relative poses among robots. If mutual observation measurements between robots are available when the robots encounter each other, the map transformation between robots for cooperative mapping can be easily obtained. However, the mutual observation measurements require too strict assumptions such as a rendezvous and encounters, which is not practical in real multi-robot systems. Moreover, the mutual observation measurements may contain inevitable errors due to the errors in sensors. To relax the assumption and correct the errors, this paper proposes a one-way observation-based technique for cooperative mapping. The proposed technique was tested with datasets obtained by real experiments with two mobile robots. Each robot was equipped with a sensor fusion system to observe other robots. The test results showed that the proposed technique worked well and improved the accuracy of the cooperatively produced map.\",\"PeriodicalId\":212181,\"journal\":{\"name\":\"2020 IEEE 16th International Conference on Automation Science and Engineering (CASE)\",\"volume\":\"65 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 IEEE 16th International Conference on Automation Science and Engineering (CASE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CASE48305.2020.9216996\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE 16th International Conference on Automation Science and Engineering (CASE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CASE48305.2020.9216996","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
摘要
研究了在初始相对姿态未知的情况下,多机器人SLAM (simultaneous localization and mapping)中的协同映射问题。如果机器人之间有相互观测的测量结果,那么机器人之间的地图转换就可以很容易地进行协作测绘。然而,相互观察测量需要过于严格的假设,如交会和相遇,这在实际的多机器人系统中是不现实的。此外,由于传感器的误差,相互观测的测量结果可能存在不可避免的误差。为了放宽假设并修正误差,本文提出了一种基于单向观测的协同映射技术。用两台移动机器人的真实实验数据集对该方法进行了验证。每个机器人都配备了传感器融合系统,以观察其他机器人。实验结果表明,该方法效果良好,提高了协同制作地图的精度。
This paper addresses the problem of cooperative mapping in multi-robot SLAM (simultaneous localization and mapping) with unknown initial relative poses among robots. If mutual observation measurements between robots are available when the robots encounter each other, the map transformation between robots for cooperative mapping can be easily obtained. However, the mutual observation measurements require too strict assumptions such as a rendezvous and encounters, which is not practical in real multi-robot systems. Moreover, the mutual observation measurements may contain inevitable errors due to the errors in sensors. To relax the assumption and correct the errors, this paper proposes a one-way observation-based technique for cooperative mapping. The proposed technique was tested with datasets obtained by real experiments with two mobile robots. Each robot was equipped with a sensor fusion system to observe other robots. The test results showed that the proposed technique worked well and improved the accuracy of the cooperatively produced map.