Google Season Of Docs (GSoD) Guide

谷歌Season of Docs项目管理与进度报告指南
本文档详细介绍了谷歌Season of Docs项目的管理流程,包括每周工作、阶段工作和博客发布规范。所有技术作者需参与每周会议并完成周报、月报和终期报告,同时进行代码审查。志愿者和导师负责审核技术作者的PR。中、终期博客需包含项目进展、遇到的问题及解决方案。此外,项目完成后,技术作者需发表关于整个项目的心得博客。

Google Season of Docs is an annual program organized by Google.

Here is the related blog:

We have some guide for GSoD like what we did in OSPP - a Chinese clone of Google’s summer of code. All of the tech writers involved in the project are required to complete their weekly work and phased work :

Weekly Work

A volunteer will organize the weekly meeting and write meeting notes & publish blog posts with zoom meeting recording videos on YouTube embedded.

Here is the guideline for video-recording/downloading/uploading

  • Download the recording which has a shared screen along with the gallery view
  • Crop the video at the beginning and the end of the meeting, the video should start to form the beginning of the meeting
  • Add a beautiful thumbnail to the video
  • Highlight the most important agenda of the video by adding timestamps like kick-off meeting recording

Refer from: Google Season of Docs 2021 Team Proposal - Volunteering

PR Reviewing & Approving Workflow

For writers

Writers who are in the same team are REQUIRED to review each other’s PR, and give “Request changes” or “Approve” Writers are encouraged to give “Request changes”, “Approve”, or “Comment” to any PRs. (please contribute to the whole team by doing it!)

For volunteers

Volunteers are REQUIRED to review all PRs created by writers and give “Request changes” or “Approve”

Mentors are in charge of reviewing the PR after
  • Volunteers create an issue list about the high priority PR
  • PR passed all the CI tests (CLA & unit testings)
  • PR gets approved by all the project team members (if applicable, 0-1 approval)
  • PR gets approved by all volunteers (2 approvals)

Phased Work

The three blogs at the beginning, middle and the end should be committed to wechaty.js.org Repo. Before submitting the report, you can read the Wechaty community specifications and know wechaty better:

  1. Introduction of Wechaty
  2. Community communication channels
  3. Meeting specifications
  4. Blog publishing specifications
  5. Issue release specification
  6. PR release specification

It is important to note that the blog publishing specifications describe in detail how to submit a blog, how to embed a video in the blog, etc., which will be used in the mid-term and final reports. The specific requirements for the three reports are as follows.

Proposal Blog

All of the tech writers have already finished this part. Here is some specification, if you have time, you can modify the previous blog to make it more beautiful.

1. Personal Profile

Create your contributor profile (if you are a first-time contributor). You can commit to wechaty.js.org Repo’s jekyll/_contributors directory.

You can refer to the following developer introduction content writing page:

2. Proposal report

Mid-term Blog

There will be a GSoD Mid-term Demo Day, volunteers can organize this Mid-term Demo Day on a regular weekly zoom meeting.

Each writer in the same team should submit a mid-term blog together with the YouTube Midterm demo day video and a summary of the mid-term work. The video needs to be uploaded to youtube, and contact Huan to add it to the playlist of wechaty.

Report template as follows:

  • Title: GSoD 2021-Mid-Term-your_title
  • File name: 2021-XX-XX-gsod-mid-term-XX
  • Category: gsod
  • Tag(at least include): google,gsod-2021,gsod,docs,mid-term
  • Content at lease includes as follows:
    • Proposal
      • Team Member
      • Description/Abstract
      • Timeline
    • Proposal Mid-term Video Presentation
    • Progress
      • Work Done
      • Problems encountered and solutions
      • Follow-up work arrangement

Final Blog

Each writer in the same team should submit a final blog together with the YouTube final video and a summary of the whole work. The video needs to be uploaded to youtube, and contact Huan to add it to the playlist of wechaty.

The final Blog is to be written after most of PRs get merged, volunteers will announce the time to write a final blog when it is ready.

Report template as follows:

  • Title: GSoD 2021-Final-your_title
  • File name: 2021-XX-XX-gsod-final-XX
  • Category: gsod
  • Tag(at least include): google,gsod-2021,gsod,docs,final
  • Content at lease includes as follows:
    • Proposal
      • Team Member
      • Description/Abstract
      • Timeline
    • Outcome
      • Links to the added documentation
      • Proposal Final Video Presentation
      • Problems encountered and solutions
    • Voluteer Assessment

Submit Expense

As GSoD Payment Intro showed:

  • Organizations will receive 40% of the grant after hiring a technical writer. Organizations will receive invitations to submit their first expense starting June 10, 2021.
  • Organizations will receive the remaining 60% of the grant after successful completion of the Season of Docs program. Organizations will receive invitations to submit their final expense starting December 14, 2021.

So for all of the tech writers in Wechaty:

  • Get the first 40% of the base stipend after submitting the mid-term blog and reviewed by volunteers and mentors.
  • Get the remaining stipends after they submitting the final-term blog and reviewed by volunteers and mentors.

Tech writers can submit expenses on Wechaty-GSod-Opencollective, see more at Opencollective docs about expenses and getting paid

Performance

To Be Added in the future.

After GSod

After the GSoD’21, tech writers should publish a blog post talking about the whole project of GSoD’21 Wechaty from your perspective

内容概要:本文介绍了一个基于多传感器融合的定位系统设计方案,采用GPS、里程计和电子罗盘作为定位传感器,利用扩展卡尔曼滤波(EKF)算法对多源传感器数据进行融合处理,最终输出目标的滤波后位置信息,并提供了完整的Matlab代码实现。该方法有效提升了定位精度与稳定性,尤其适用于存在单一传感器误差或信号丢失的复杂环境,如自动驾驶、移动采用GPS、里程计和电子罗盘作为定位传感器,EKF作为多传感器的融合算法,最终输出目标的滤波位置(Matlab代码实现)机器人导航等领域。文中详细阐述了各传感器的数据建模方式、状态转移与观测方程构建,以及EKF算法的具体实现步骤,具有较强的工程实践价值。; 适合人群:具备一定Matlab编程基础,熟悉传感器原理和滤波算法的高校研究生、科研人员及从事自动驾驶、机器人导航等相关领域的工程技术人员。; 使用场景及目标:①学习和掌握多传感器融合的基本理论与实现方法;②应用于移动机器人、无人车、无人机等系统的高精度定位与导航开发;③作为EKF算法在实际工程中应用的教学案例或项目参考; 阅读建议:建议读者结合Matlab代码逐行理解算法实现过程,重点关注状态预测与观测更新模块的设计逻辑,可尝试引入真实传感器数据或仿真噪声环境以验证算法鲁棒性,并进一步拓展至UKF、PF等更高级滤波算法的研究与对比。
内容概要:文章围绕智能汽车新一代传感器的发展趋势,重点阐述了BEV(鸟瞰图视角)端到端感知融合架构如何成为智能驾驶感知系统的新范式。传统后融合与前融合方案因信息丢失或算力需求过高难以满足高阶智驾需求,而基于Transformer的BEV融合方案通过统一坐标系下的多源传感器特征融合,在保证感知精度的同时兼顾算力可行性,显著提升复杂场景下的鲁棒性与系统可靠性。此外,文章指出BEV模型落地面临大算力依赖与高数据成本的挑战,提出“数据采集-模型训练-算法迭代-数据反哺”的高效数据闭环体系,通过自动化标注与长尾数据反馈实现算法持续进化,降低对人工标注的依赖,提升数据利用效率。典型企业案例进一步验证了该路径的技术可行性与经济价值。; 适合人群:从事汽车电子、智能驾驶感知算法研发的工程师,以及关注自动驾驶技术趋势的产品经理和技术管理者;具备一定自动驾驶基础知识,希望深入了解BEV架构与数据闭环机制的专业人士。; 使用场景及目标:①理解BEV+Transformer为何成为当前感知融合的主流技术路线;②掌握数据闭环在BEV模型迭代中的关键作用及其工程实现逻辑;③为智能驾驶系统架构设计、传感器选型与算法优化提供决策参考; 阅读建议:本文侧重技术趋势分析与系统级思考,建议结合实际项目背景阅读,重点关注BEV融合逻辑与数据闭环构建方法,并可延伸研究相关企业在舱泊一体等场景的应用实践。
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