Automated Extrinsic Calibration of Multi-Cameras and LiDAR

In intelligent driving systems, the multisensor fusion perception system comprising multiple cameras and LiDAR has become a crucial component. It is essential to have stable extrinsic parameters among devices in a multisensor fusion system to achieve all-weather sensing with no blind zones. However, prolonged vehicle usage can result in immeasurable sensor offsets that lead to perception deviations. To this end, we have studied multisensor unified calibration, rather than the calibration between a single pair of sensors as previously done. Benefiting from the mutually constrained pose between different sensor pairs, the method improves calibration accuracy by around 20% compared to calibration for a pair of sensors. The study can serve as a foundation for multisensor unified calibration, enabling the overall automatic optimization of all camera and LiDAR sensors onboard a vehicle within a single framework.

• Publication year

  2024

• Venue

  IEEE Transactions on Instrumentation and Measurement

• Publication date

  Unknown publication date

• Fields of study

  Computer Science, Engineering, Environmental Science

• Identifiers
  DOI 10.1109/TIM.2023.3341122
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

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