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Object Guided Beam Steering Algorithm for Optical Phased Array (OPA) LIDAR

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Intelligence Science and Big Data Engineering. Visual Data Engineering (IScIDE 2019)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 11935))

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Abstract

As a fundamental sensor for autonomous driving, light detection and ranging (LIDAR) has gained increasing attentions in recent years. Optical phased array (OPA) LIDAR as a solid-state solution with the advantages of durability and low cost has been actively researched in both the academic and industry fields. Beam steering is a critical problem in OPA LIDAR where the beam can be controlled by software instantaneously. In this paper, we propose an object guided beam steering algorithm where the beams are allocated according to the detected objects in current frame of image. A series of rules are designed to assign different weights to different regions in the scene. We evaluated the algorithm in a simulated environment and the experimental results demonstrated the effectiveness of the proposed algorithm.

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Authors and Affiliations

  1. College of Information Science and Electronic Engineering, Zhejiang University, Hangzhou, China

    Zhiqing Wang, Zhiyu Xiang & Eryun Liu

Authors
  1. Zhiqing Wang
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  2. Zhiyu Xiang
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  3. Eryun Liu
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Corresponding author

Correspondence to Zhiqing Wang .

Editor information

Editors and Affiliations

  1. Nanjing University of Science and Technology, Nanjing, China

    Zhen Cui

  2. Nanjing University of Science and Technology, Nanjing, China

    Jinshan Pan

  3. Nanjing University of Science and Technology, Nanjing, China

    Shanshan Zhang

  4. Nanjing University of Science and Technology, Nanjing, China

    Liang Xiao

  5. Nanjing University of Science and Technology, Nanjing, China

    Jian Yang

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Cite this paper

Wang, Z., Xiang, Z., Liu, E. (2019). Object Guided Beam Steering Algorithm for Optical Phased Array (OPA) LIDAR. In: Cui, Z., Pan, J., Zhang, S., Xiao, L., Yang, J. (eds) Intelligence Science and Big Data Engineering. Visual Data Engineering. IScIDE 2019. Lecture Notes in Computer Science(), vol 11935. Springer, Cham. https://doi.org/10.1007/978-3-030-36189-1_22

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  • DOI: https://doi.org/10.1007/978-3-030-36189-1_22

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-36188-4

  • Online ISBN: 978-3-030-36189-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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