research-article

ReDroSe — Reconfigurable Drone Setup for Resource-Efficient SLAM

Authors:

Sebastian Rahn,

Philipp Gehricke,

Can-Leon Petermöller,

Philipp Schlinge,

Henning Termühlen,

Christopher Sieh,

Marco Tassemeier,

Thomas Wiemann,

Mario PorrmannAuthors Info & Claims

RAPIDO '23: Proceedings of the DroneSE and RAPIDO: System Engineering for constrained embedded systems

Pages 20 - 30

https://doi.org/10.1145/3579170.3579266

Published: 13 April 2023 Publication History

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.

References

[1]

Daniel Ricao Canelhas, Todor Stoyanov, and Achim J. Lilienthal. 2013. SDF Tracker: A parallel algorithm for on-line pose estimation and scene reconstruction from depth images. In 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems. IEEE, Tokyo, Japan, 3671–3676.

[2]

NVIDIA Corporation. 2022. Jetson Xavier NX Series. https://www.nvidia.com/de-de/autonomous-machines/embedded-systems/jetson-xavier-nx/. Accessed: 2022-11-22.

[3]

Ouster Corporation. 2022. OS 1 Mid-range digital lidar sensor. https://ouster.com/products/scanning-lidar/os1-sensor/. Accessed: 2022-12-21.

[4]

Marc Eisoldt, Marcel Flottmann, Julian Gaal, Pascal Buschermöhle, Steffen Hinderink, Malte Hillmann, Adrian Nitschmann, Patrick Hoffmann, Thomas Wiemann, and Mario Porrmann. 2021. HATSDF SLAM–Hardware-accelerated TSDF SLAM for Reconfigurable SoCs. In 2021 European Conference on Mobile Robots (ECMR). IEEE, Bonn, Germany, 1–7.

[5]

Marc Eisoldt, Julian Gaal, Thomas Wiemann, Marcel Flottmann, Marc Rothmann, Marco Tassemeier, and Mario Porrmann. 2022. A fully integrated system for hardware-accelerated TSDF SLAM with LiDAR sensors (HATSDF SLAM). Robotics and Autonomous Systems 156 (2022).

[6]

Trenz Electronic. 2022. Trenz Electronic Wiki - TE0808 TRM. https://wiki.trenz-electronic.de/display/PD/TE0808+Resources. Accessed: 2022-11-22.

[7]

Trenz Electronic. 2022. Trenz Electronic Wiki - TEBF0808 TRM. https://wiki.trenz-electronic.de/display/PD/TEBF0808+TRM. Accessed: 2022-11-22.

[8]

Marcel Flottmann, Marc Eisoldt, Julian Gaal, Marc Rothmann, Marco Tassemeier, Thomas Wiemann, and Mario Porrmann. 2021. Energy-efficient FPGA-accelerated LiDAR-based SLAM for embedded robotics. In 2021 International Conference on Field-Programmable Technology (ICFPT). IEEE, Auckland, New Zealand, 1–6.

[9]

Felix Igelbrink, Thomas Wiemann, Sebastian Pütz, and Joachim Hertzberg. 2019. Markerless AD-HOC calibration of a hyperspectral camera and a 3D laser scanner, In Intelligent Autonomous Systems 15. Advances in Intelligent Systems and Computing 867, 748–759.

[10]

Shahram Izadi, David Kim, Otmar Hilliges, David Molyneaux, Richard Newcombe, Pushmeet Kohli, Jamie Shotton, Steve Hodges, Dustin Freeman, Andrew Davison, 2011. KinectFusion: real-time 3D reconstruction and interaction using a moving depth camera. In Proceedings of the 24th annual ACM symposium on User interface software and technology. 559–568.

Digital Library

[11]

MAVLink. 2022. MAVLink User Guide. https://mavlink.io/en/. Accessed: 2022-11-24.

[12]

NVIDIA. 2019. Accelerated GStreamer User Guide. https://developer.download.nvidia.com/embedded/L4T/r32_Release_v1.0/Docs/Accelerated_GStreamer_User_Guide.pdf. Accessed: 2022-11-25.

[13]

NVIDIA. 2022. Libargus Camera API. Retrieved 2022-11-25 from https://docs.nvidia.com/jetson/l4t-multimedia/group__LibargusAPI.html

[14]

Tixiao Shan and Brendan Englot. 2018. Lego-loam: Lightweight and ground-optimized lidar odometry and mapping on variable terrain. In 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). IEEE, 4758–4765.

Digital Library

[15]

Tixiao Shan, Brendan Englot, Drew Meyers, Wei Wang, Carlo Ratti, and Daniela Rus. 2020. Lio-sam: Tightly-coupled lidar inertial odometry via smoothing and mapping. In 2020 IEEE/RSJ international conference on intelligent robots and systems (IROS). IEEE, 5135–5142.

Digital Library

[16]

OpenCV team. 2022. OpenCV Camera Calibration. https://docs.opencv.org/4.x/dc/dbb/tutorial_py_calibration.html. Accessed: 2022-12-21.

[17]

Han Wang, Chen Wang, Chun-Lin Chen, and Lihua Xie. 2021. F-loam: Fast lidar odometry and mapping. In 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). IEEE, 4390–4396.

Digital Library

[18]

André Weißenberger and Bertil Schmidt. 2021. Accelerating JPEG Decompression on GPUs. In 2021 IEEE 28th International Conference on High Performance Computing, Data, and Analytics (HiPC). 121–130.

[19]

Thomas Whelan, Michael Kaess, Maurice Fallon, Hordur Johannsson, John Leonard, and John McDonald. 2012. Kintinuous: Spatially extended kinectfusion. (2012).

[20]

Xilinx. 2021. PetaLinux Tools Documentation: Reference Guide (ug1144 (v2021.2) ed.). Retrieved 2022-11-26 from https://docs.xilinx.com/r/2021.2-English/ug1144-petalinux-tools-reference-guide/Revision-History

[21]

Xilinx. 2021. Vitis High-Level Synthesis User Guide(ug1399 (v2021.2) ed.). https://docs.xilinx.com/r/2021.2-English/ug1399-vitis-hls/Getting-Started-with-Vitis-HLS

[22]

Xilinx. 2021. Vivado Design Suite User Guide: Design Flows Overview (ug892 (v2021.2) ed.). Retrieved 2022-11-26 from https://docs.xilinx.com/r/2021.2-English/ug892-vivado-design-flows-overview/Vivado-System-Level-Design-Flows

[23]

Ji Zhang and Sanjiv Singh. 2014. LOAM: Lidar odometry and mapping in real-time. In Robotics: Science and Systems, Vol. 2. Berkeley, CA, 1–9.

Cited By

Vogt CJost MMagno M(2024)SwiftEagle: An Advanced Open-Source, Miniaturized FPGA UAS Platform with Dual DVS/Frame Camera for Cutting-Edge Low-Latency Autonomous Algorithms2024 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)10.1109/IROS58592.2024.10802491(8134-8140)Online publication date: 14-Oct-2024
https://doi.org/10.1109/IROS58592.2024.10802491
Eisoldt MMock APorrmann MWiemann T(2023)Towards 6D MCL for LiDARs in 3D TSDF Maps on Embedded Systems with GPUs2023 Seventh IEEE International Conference on Robotic Computing (IRC)10.1109/IRC59093.2023.00035(158-165)Online publication date: 11-Dec-2023
https://doi.org/10.1109/IRC59093.2023.00035

Index Terms

ReDroSe — Reconfigurable Drone Setup for Resource-Efficient SLAM
1. Computer systems organization
  1. Architectures
    1. Other architectures
      1. Reconfigurable computing
  2. Embedded and cyber-physical systems
    1. Robotics
      1. Robotic autonomy

Recommendations

ReconfROS: Running ROS on Reconfigurable SoCs
DroneSE and RAPIDO '21: Proceedings of the 2021 Drone Systems Engineering and Rapid Simulation and Performance Evaluation: Methods and Tools Proceedings

In this paper, we present an approach to integrate reconfigurable SoCs into the well known Robot Operating System (ROS). Our method allows to implement hardware-accelerated algorithms on FPGA and integrate them directly into the ROS ecosystem. This ...
Demonstration of wireless synchronisation methods in autonomously controlled fleet of drones

This paper describes methods used in synchronising the behaviour of multiple autonomous flight vehicles utilising custom external hardware and firmware injected into current aviation flight systems. To prove the reliability and consistency of an ...
Efficient OpenCL system integration of non-blocking FPGA accelerators
Abstract
OpenCL functions as a portability layer for diverse heterogeneous hardware platforms including CPUs, GPUs, FPGAs, and hardware accelerators. However, OpenCL programs utilizing multiple of these devices in the same computing platform ...

Comments

Information & Contributors

Information

Published In

cover image ACM Other conferences

RAPIDO '23: Proceedings of the DroneSE and RAPIDO: System Engineering for constrained embedded systems

January 2023

94 pages

ISBN:9798400700453

DOI:10.1145/3579170

Copyright © 2023 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 13 April 2023

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Research-article
Research
Refereed limited

Conference

DroneSE and RAPIDO 2023

DroneSE and RAPIDO 2023: System Engineering for constrained embedded systems

January 17 - 18, 2023

Toulouse, France

Acceptance Rates

Overall Acceptance Rate 14 of 28 submissions, 50%

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

2
Total Citations
View Citations
101
Total Downloads

Downloads (Last 12 months)28
Downloads (Last 6 weeks)2

Reflects downloads up to 05 Mar 2025

Other Metrics

View Author Metrics

Citations

Cited By

Vogt CJost MMagno M(2024)SwiftEagle: An Advanced Open-Source, Miniaturized FPGA UAS Platform with Dual DVS/Frame Camera for Cutting-Edge Low-Latency Autonomous Algorithms2024 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)10.1109/IROS58592.2024.10802491(8134-8140)Online publication date: 14-Oct-2024
https://doi.org/10.1109/IROS58592.2024.10802491
Eisoldt MMock APorrmann MWiemann T(2023)Towards 6D MCL for LiDARs in 3D TSDF Maps on Embedded Systems with GPUs2023 Seventh IEEE International Conference on Robotic Computing (IRC)10.1109/IRC59093.2023.00035(158-165)Online publication date: 11-Dec-2023
https://doi.org/10.1109/IRC59093.2023.00035

View Options

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

HTML Format

View this article in HTML Format.

Figures

Tables

Media

View Table of Conten