ReDroSe - Reconfigurable Drone Setup for Resource-Efficient SLAM

被引：1

作者：

Rahn, Sebastian ^{[1
]}

Gehricke, Philipp ^{[1
]}

Petermoeller, Can-Leon ^{[1
]}

Neumann, Eric ^{[1
]}

Schlinge, Philipp ^{[1
]}

Rabius, Leon ^{[1
]}

Termuehlen, Henning ^{[1
]}

Sieh, Christopher ^{[1
]}

Tassemeier, Marco ^{[1
]}

Wiemann, Thomas ^{[1
]}

Porrmann, Mario ^{[1
]}

机构：

[1] Osnabruck Univ, Osnabruck, Germany

来源：

PROCEEDINGS OF SYSTEM ENGINEERING FOR CONSTRAINED EMBEDDED SYSTEMS, DRONESE AND RAPIDO 2023 | 2023年

关键词：

ROS; Field Programmable Gate Array; GPU; Heterogeneous Computing; Hardware Acceleration; UAV; Drone;

D O I：

10.1145/3579170.3579266

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

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.

引用

页码：20 / 30

页数：11

共 50 条

[31] A resource-efficient adaptive Fourier analyzer
Hajdu, C. F.
Zamantzas, C.
Daboczi, T.
JOURNAL OF INSTRUMENTATION, 2016, 11
[32] Sustainable and Resource-Efficient Homes and Communities
Friedman, Avi
SUSTAINABILITY, 2017, 9 (12)
[33] Protean: Resource-efficient Instruction Prefetching
Hassan, Muhammad
Park, Chang Hyun
Black-Schaffer, David
PROCEEDINGS OF THE INTERNATIONAL SYMPOSIUM ON MEMORY SYSTEMS, MEMSYS 2023, 2023,
[34] Resource-efficient workflow scheduling in clouds
Lee, Young Choon
Han, Hyuck
Zomaya, Albert Y.
Yousif, Mazin
KNOWLEDGE-BASED SYSTEMS, 2015, 80 : 153 - 162
[35] Resource-Efficient Computing in Wearable Systems
Pedram, Mahdi
Rofouei, Mahsan
Fraternali, Francesco
Ashari, Zhila Esna
Ghasemzadeh, Hassan
2019 IEEE INTERNATIONAL CONFERENCE ON SMART COMPUTING (SMARTCOMP 2019), 2019, : 150 - 155
[36] Biogas as a resource-efficient vehicle fuel
Borjesson, Pal
Mattiasson, Bo
TRENDS IN BIOTECHNOLOGY, 2008, 26 (01) : 7 - 13
[37] A RESOURCE-EFFICIENT PROBABILISTIC FAULT SIMULATOR
May, David
Stechele, Walter
2013 23RD INTERNATIONAL CONFERENCE ON FIELD PROGRAMMABLE LOGIC AND APPLICATIONS (FPL 2013) PROCEEDINGS, 2013,
[38] Resource-efficient anonymous group identification
Handley, B
FINANCIAL CRYPTOGRAPHY, PROCEEDINGS, 2001, 1962 : 295 - 312
[39] Are solid recovered fuels resource-efficient?
Velis, Costas A.
Cooper, Jeff
WASTE MANAGEMENT & RESEARCH, 2013, 31 (02) : 113 - 114
[40] Resource-Efficient Wearable Computing for Real-Time Reconfigurable Machine Learning: A Cascading Binary Classification
Pedram, Mahdi
Rokni, Seyed Ali
Nourollahi, Marjan
Homayoun, Houman
Ghasemzadeh, Hassan
2019 IEEE 16TH INTERNATIONAL CONFERENCE ON WEARABLE AND IMPLANTABLE BODY SENSOR NETWORKS (BSN), 2019,

← 1 2 3 4 5 →