로봇학회논문지 (The Journal of Korea Robotics Society)

  • 제17권3호
  • /
  • Pages.245-254
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  • 2022
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  • 1975-6291(pISSN)
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  • 2287-3961(eISSN)
한국로봇학회 (Korea Robotics Society)
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열악한 환경에서의 자율주행을 위한 다중센서 데이터셋 구축

Build a Multi-Sensor Dataset for Autonomous Driving in Adverse Weather Conditions

  • 투고 : 2022.05.17
  • 심사 : 2022.06.20
  • 발행 : 2022.08.31
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초록

Sensor dataset for autonomous driving is one of the essential components as the deep learning approaches are widely used. However, most driving datasets are focused on typical environments such as sunny or cloudy. In addition, most datasets deal with color images and lidar. In this paper, we propose a driving dataset with multi-spectral images and lidar in adverse weather conditions such as snowy, rainy, smoky, and dusty. The proposed data acquisition system has 4 types of cameras (color, near-infrared, shortwave, thermal), 1 lidar, 2 radars, and a navigation sensor. Our dataset is the first dataset that handles multi-spectral cameras in adverse weather conditions. The Proposed dataset is annotated as 2D semantic labels, 3D semantic labels, and 2D/3D bounding boxes. Many tasks are available on our dataset, for example, object detection and driveable region detection. We also present some experimental results on the adverse weather dataset.

키워드

과제정보

This project was funded by Defense Aquisition Prorgram Administration (DAPA)

참고문헌

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