• Welcome to Autonomous Vehicles and Embedded systems (AVE, [ ˈæv.ə.nuː ]) Lab!

  • Perception for Autonomous Driving

    We are developing a comprehensive perception system robust in all conditions by integrating various sensors
    including 4D Radar, which excels even in adverse weather conditions.

  • Large AI Model based End-to-End Autonomous Driving

    We are developing a robust Large AI Model based End-to-End Autonomous Driving System, adept at handling Unexpected Novel Situations (UNS). We are also studying Sim2Real techniques for real world applications

  • Localization for Autonomous Driving

    We're innovating a next-gen localization system to address multipath and interference challenges.
    Additionally, we're researching geo-localization techniques for GPS-denied environments.

  • Embedded AI for Autonomous Driving

    We aim to develop embedded techniques to enable on-device AI, making the commercialization of autonomous driving feasible.

  • Next-Generation Full-Stack Platform for Autonomous Driving

    Our goal is to attain a full-stack solution for autonomous driving.
    We are also planning to research on embedded systems, LLMs, and open-source platforms specialized for autonomous driving.

Publications

  • 2024
  • RTNH+: Enhanced 4D Radar Object Detection Network using Two-Level Preprocessing and Vertical Encodin…

  • Seung-Hyun Kong†, Dong-Hee Paek†, Sangyeong Lee IEEE Transactions on Intelligent Vehicles [SCIE, IF 14.0, JCR Top 2.3%], 2024

  • 2022
  • K-Radar: 4D Radar Object Detection for Urban Roads and Highways in Various Weather Conditions

  • Dong-Hee Paek, Seung-Hyun Kong, Kevin Tirta Wijaya Advances in Neural Information Processing Systems (NeurIPS) Datasets and Benchmarks, 2022

  • 2022
  • K-Lane: Lidar Lane Dataset and Benchmark for Urban Roads and Highways

  • Dong-Hee Paek, Seung-Hyun Kong, Kevin Tirta Wijaya IEEE/CVF Computer Vision and Pattern Recognition (CVPR) Workshop on Autonomous Driving, 2022

  • 2022
  • Segmented Encoding for Sim2Real of RL-based End-to-End Autonomous Driving

  • Seung-Hwan Chung, Seung-Hyun Kong, I Made Aswin Nahrendra, Sanjae Cho IEEE Intelligent Vehicles Symposium (IV), 2022

  • 2022
  • The Autonomous Vehicles and Electronics Lab [ITS Research Lab]

  • Yisheng Lv IEEE Intelligent Transportation Systems Magazine, 2022 July/August

  • 2022
  • GPS First Arrival Path Detection Network using MLP-Mixers

  • Seung-Hyun Kong†, Sangjae Cho†, Euiho Kim* IEEE Transaction on Wireless Communications [SCI, IF 7.016], vol. 21, no. 9, pp. 7764-7777, September 2022

  • 2021
  • Enhanced Off-Policy Reinforcement Learning with Focused Experience Replay

  • Seung-Hyun Kong, I Made Aswin Nahrendra, Dong-Hee Paek IEEE Access [SCIE, IF 3.476, Top 48.17%], vol. 9, pp. 93152-93164, May 2021

  • 2019
  • Automatic Recognition of General LPI Radar Waveform using SSD and Supplementary Classifier

  • Linh Manh Hoang; Minjun Kim; Seung-Hyun Kong IEEE Trans. on Signal Processing [SCI, IF 5.028, Top 13.53%], May 2019

  • 2018
  • Automatic LPI Radar Waveform Recognition using CNN

  • Seung-Hyun Kong; Minjun Kim; Linh Manh Hoang; Eunhui Kim IEEE Access [SCIE, IF 3.244, JCR Top 20.77%], January 2018

Gallery

  • 조상재 박사 디펜스, 졸업 기념 사진 촬영 및 회식
  •  
  • 2024-08-15

  • IEEE IV 2024 현장 운영

  •  …
  • 2024-06-14

Global and Industrial Leadership

The Cho Chun Shik Graduate School of Mobility, KAIST
Munji-ro, Yuseong-gu, Daejeon 193, South Korea
Tel : +82-42-350-1285 Email : avelab@kaist.ac.kr

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