Fail-Operational Shock Detection and Correction of MEMS-based Micro-Scanning LiDAR Systems

Philipp Stelzer; Andreas Strasser; Christian Steger; Norbert Druml

doi:10.1109/SAS48726.2020.9220034

Fail-Operational Shock Detection and Correction of MEMS-based Micro-Scanning LiDAR Systems

Philipp Stelzer, Andreas Strasser, Christian Steger, Norbert Druml

Institute of Technical Informatics (4480)

Research output: Chapter in Book/Report/Conference proceeding › Conference paper › peer-review

Abstract

Highly automated or autonomous vehicles will be dependent on systems that have to perceive the environment to make valid decisions during the driving cycle. One of the key enablers for autonomous and highly automated vehicles will be Light Detection And Ranging (LiDAR) technology. A MicroElectro-Mechanical System (MEMS) based Micro-Scanning LiDAR is able to detect obstacles in a predefined Field-of-View (FoV). The point cloud stability of the scanned FoV is mandatory to be able to make a valid point where the obstacle is located in the scenery. Due to the fact that massive shocks can occur arbitrarily to the system, it is necessary to be able to detect and correct them as fast as possible that point cloud stability can be recovered as fast as possible. In this paper, we introduce a novel system architecture that enables a fast shock detection and correction of phase and frequency for MEMS-based MicroScanning LiDAR Systems. Our novel introduced fail-operational detection and correction system architecture was implemented in a 1D MEMS-based Micro-Scanning LiDAR FPGA platform to prove its feasibility and for performance evaluation.

Original language	English
Title of host publication	2020 IEEE Sensors Applications Symposium, SAS 2020 - Proceedings
Number of pages	6
ISBN (Electronic)	978-1-7281-4842-7
DOIs	https://doi.org/10.1109/SAS48726.2020.9220034
Publication status	Published - Mar 2020
Event	15th IEEE Sensors Applications Symposium: SAS 2020 - Kuala Lumpur, Malaysia Duration: 9 Mar 2020 → 11 Mar 2020

Publication series

Name	2020 IEEE Sensors Applications Symposium, SAS 2020 - Proceedings

Conference

Conference	15th IEEE Sensors Applications Symposium
Abbreviated title	SAS 2020
Country/Territory	Malaysia
City	Kuala Lumpur
Period	9/03/20 → 11/03/20

Keywords

LiDAR
1D MEMS Mirror
automated driving
fast shock correction
failure recovery system

ASJC Scopus subject areas

Instrumentation
Computer Vision and Pattern Recognition
Computer Science Applications

Access to Document

10.1109/SAS48726.2020.9220034

Fail-Operational Shock Detection and Correction of MEMS-based Micro-Scanning LiDAR SystemsAccepted author manuscript, 3.03 MB

Cite this

Fail-Operational Shock Detection and Correction of MEMS-based Micro-Scanning LiDAR Systems. / Stelzer, Philipp; Strasser, Andreas; Steger, Christian et al.

2020 IEEE Sensors Applications Symposium, SAS 2020 - Proceedings. 2020. 9220034 (2020 IEEE Sensors Applications Symposium, SAS 2020 - Proceedings).

Research output: Chapter in Book/Report/Conference proceeding › Conference paper › peer-review

Stelzer, P, Strasser, A, Steger, C & Druml, N 2020, Fail-Operational Shock Detection and Correction of MEMS-based Micro-Scanning LiDAR Systems. in 2020 IEEE Sensors Applications Symposium, SAS 2020 - Proceedings., 9220034, 2020 IEEE Sensors Applications Symposium, SAS 2020 - Proceedings, 15th IEEE Sensors Applications Symposium, Kuala Lumpur, Malaysia, 9/03/20. https://doi.org/10.1109/SAS48726.2020.9220034

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N2 - Highly automated or autonomous vehicles will be dependent on systems that have to perceive the environment to make valid decisions during the driving cycle. One of the key enablers for autonomous and highly automated vehicles will be Light Detection And Ranging (LiDAR) technology. A MicroElectro-Mechanical System (MEMS) based Micro-Scanning LiDAR is able to detect obstacles in a predefined Field-of-View (FoV). The point cloud stability of the scanned FoV is mandatory to be able to make a valid point where the obstacle is located in the scenery. Due to the fact that massive shocks can occur arbitrarily to the system, it is necessary to be able to detect and correct them as fast as possible that point cloud stability can be recovered as fast as possible. In this paper, we introduce a novel system architecture that enables a fast shock detection and correction of phase and frequency for MEMS-based MicroScanning LiDAR Systems. Our novel introduced fail-operational detection and correction system architecture was implemented in a 1D MEMS-based Micro-Scanning LiDAR FPGA platform to prove its feasibility and for performance evaluation.

AB - Highly automated or autonomous vehicles will be dependent on systems that have to perceive the environment to make valid decisions during the driving cycle. One of the key enablers for autonomous and highly automated vehicles will be Light Detection And Ranging (LiDAR) technology. A MicroElectro-Mechanical System (MEMS) based Micro-Scanning LiDAR is able to detect obstacles in a predefined Field-of-View (FoV). The point cloud stability of the scanned FoV is mandatory to be able to make a valid point where the obstacle is located in the scenery. Due to the fact that massive shocks can occur arbitrarily to the system, it is necessary to be able to detect and correct them as fast as possible that point cloud stability can be recovered as fast as possible. In this paper, we introduce a novel system architecture that enables a fast shock detection and correction of phase and frequency for MEMS-based MicroScanning LiDAR Systems. Our novel introduced fail-operational detection and correction system architecture was implemented in a 1D MEMS-based Micro-Scanning LiDAR FPGA platform to prove its feasibility and for performance evaluation.

KW - LiDAR

KW - 1D MEMS Mirror

KW - automated driving

KW - fast shock correction

KW - failure recovery system

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M3 - Conference paper

T3 - 2020 IEEE Sensors Applications Symposium, SAS 2020 - Proceedings

BT - 2020 IEEE Sensors Applications Symposium, SAS 2020 - Proceedings

T2 - 15th IEEE Sensors Applications Symposium

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ER -

Fail-Operational Shock Detection and Correction of MEMS-based Micro-Scanning LiDAR Systems

Abstract

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Conference

Keywords

ASJC Scopus subject areas

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PRYSTINE - Programmable Systems for Intelligence in Automobiles