Sebastian Rahn, Philipp Gehricke, Can-Leon Petermöller, Eric Neumann, Philipp Schlinge, Leon Rabius, Henning Termühlen, Christopher Sieh, M. Tassemeier, T. Wiemann, Mario Porrmann
{"title":"ReDroSe — Reconfigurable Drone Setup for Resource-Efficient SLAM","authors":"Sebastian Rahn, Philipp Gehricke, Can-Leon Petermöller, Eric Neumann, Philipp Schlinge, Leon Rabius, Henning Termühlen, Christopher Sieh, M. Tassemeier, T. Wiemann, Mario Porrmann","doi":"10.1145/3579170.3579266","DOIUrl":null,"url":null,"abstract":"In this paper we present ReDroSe, a heterogeneous compute system based on embedded CPUs, FPGAs and GPUs, which is integrated into an existing UAV platform to allow real time SLAM based on a Truncated Signed Distance Field (TSDF) directly on the drone. The system is fully integrated into the existing infrastructure to allow ground control to manage and monitor the data acquisition process. ReDroSe is evaluated in terms of power consumption and computing capabilities. The results show that the proposed architecture allows computations on the UAV that were previously only possible in post-processing while keeping the power consumption low enough to match the available flight time of the UAV.","PeriodicalId":153341,"journal":{"name":"Proceedings of the DroneSE and RAPIDO: System Engineering for constrained embedded systems","volume":"53 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the DroneSE and RAPIDO: System Engineering for constrained embedded systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3579170.3579266","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
In this paper we present ReDroSe, a heterogeneous compute system based on embedded CPUs, FPGAs and GPUs, which is integrated into an existing UAV platform to allow real time SLAM based on a Truncated Signed Distance Field (TSDF) directly on the drone. The system is fully integrated into the existing infrastructure to allow ground control to manage and monitor the data acquisition process. ReDroSe is evaluated in terms of power consumption and computing capabilities. The results show that the proposed architecture allows computations on the UAV that were previously only possible in post-processing while keeping the power consumption low enough to match the available flight time of the UAV.