CHENGCHENG GUO

CHENGCHENG GUO

I received the B.E. and M.E. degrees from Tongji University, Shanghai, China. My research interests include visual simultaneous localization and mapping

Sitemap

A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.

Pages

Posts

awesome resource list

less than 1 minute read

Published:

Awesome algorithm list

  • object slam(https://github.com/520xyxyzq/awesome-object-SLAM)

Blog Post 21

less than 1 minute read

Published:

阅读过的书籍:

error handle collection

less than 1 minute read

Published:

  • apt command error
    ps -A | grep apt
kill -9
rm -f /var/lib/dpkg/lock
rm -f /var/cache/apt/archives/lock
rm -f /var/lib/apt/lists/lock

Read Paper Collection Detail

1 minute read

Published:

LVI-SAM: Tightly-coupled Lidar-Visual-Inertial Odometry via Smoothing and Mapping (ICRA 2021)

Read Paper Collection

4 minute read

Published:

Vision Localization

  1. Monocular Localization in HD Maps by Combining Semantic Segmentation and Distance Transform (IROS 2020, KIT)
  2. Road Mapping and Localization using Sparse Semantic Visual Features (ICRA 2021, Alibaba)
  3. Compact 3D Map-Based Monocular Localization Using Semantic Edge Alignment (IROS 2021, Alibaba)
  4. Monocular Localization with Vector HD Map (MLVHM): A Low-Cost Method for Commercial IVs (Sensors, 2020)
  5. Long-Term Urban Vehicle Localization Using Pole Landmarks Extracted from 3-D Lidar Scans (2019)
  6. DA4AD: End-to-End Deep Attention-based Visual Localization for Autonomous Driving (ECCV 2020)
  7. Exploiting Sparse Semantic HD Maps for Self-Driving Vehicle Localization (IROS 2019, Uber.ATG)
  8. Lane Endpoint Detection and Position Accuracy Evaluation for Sensor Fusion-Based Vehicle Localization on Highways (Korean, 2018, sensors)
  9. Visual Semantic Localization based on HD Map for Autonomous Vehicles in Urban Scenarios (ICRA 2021, Huawei)
  10. HDMI-Loc:Exploiting high definition map image for precise localization vis bitwise particle filter (IROS 2020)
  11. DT-Loc: Monocular Visual Localization on HD Vector Map Using Distance Transforms of 2D Semantic Detections (IROS 2021)

PYTHON脚本集合

less than 1 minute read

Published:

PYTHON SCRIPT COLLECTION

stereo match

3 minute read

Published:

立体匹配

portfolio

publications

一种基于语义边缘对齐的由粗到精的多传感器融合定位方法 [patent]

Published in , 1900

本发明涉及无人驾驶、视觉定位技术领域，具体来说是一种基于语义边缘对齐的由粗到精的多传感器融合定位方法，包括获取高精地图、原始图像、消费级的车载GPS以及轮子里程计的步骤，本发明是一种低成本的以视觉传感器为主的高精定位方法，通过融合里程计和车载GPS信息获得鲁棒的定位结果，通过提取图像中稳定的语义特征，进行语义边缘对齐来得到车辆位姿的估计，对齐的方式不需要显式的进行三维地图特征和二维图像特征的数据关联，而是隐式的通过最小化投影点的光度残差来进行位姿的估计。

talks

teaching

Teaching experience 1

Undergraduate course, University 1, Department, 2014

This is a description of a teaching experience. You can use markdown like any other post.

Teaching experience 2

Workshop, University 1, Department, 2015

This is a description of a teaching experience. You can use markdown like any other post.