问HN：如今机器人团队是如何管理数据和调试的？
嗨，HN社区，
我正在进行一个与机器人技术相关的项目，希望能获得社区的意见。
我观察到的问题是：机器人团队会产生大量的数据（如ROS2、MCAP、OpenLABEL等），但调试和分析往往需要花费数小时翻阅日志、编写自定义脚本或处理碎片化格式。对于中小型机器人公司来说，这确实会减缓迭代速度。
我想了解：
• 你/你的团队目前是如何管理和分析机器人数据的？
• 你们面临的最大痛点是什么（例如，调试故障、比较测试运行、在日志中搜索）？
• 你们是否尝试过像Foxglove、Rerun等工具？哪些有效，哪些无效？
• 如果有一个解决方案能够真正简化这个过程，你希望它具备哪些功能才能让你们愿意采用？
我还准备了一个简短的（5分钟）调查问卷，链接在这里：https://forms.gle/x57UReg8Yj9Gx7qZ8
如果你愿意更详细地分享你的经验，这将对我们正在构建的内容非常有帮助。
我们会对回复进行匿名处理，并在收集到足够的数据后与社区分享汇总的见解。
提前感谢你们——我知道这是一个小众问题，但我认为HN社区中有一些最优秀的机器人工程师、创始人和爱好者。我非常期待听到你们今天是如何解决这个问题的。
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Hi HN,<p>I’m working on a project in the robotics space and would love to get the community’s perspective.<p>The problem I’ve seen: robotics teams generate a massive amount of data (ROS2, MCAP, OpenLABEL, etc.), but debugging and analysis often means hours of digging through logs, building custom scripts, or fighting fragmented formats. For small and medium robotics companies, this can really slow down iteration.<p>I’m trying to understand:<p>• How do you/your team currently manage and analyze robot data?<p>• What are the biggest pain points you face (e.g. debugging failures, comparing test runs, searching across logs)?<p>• Have you tried tools like Foxglove/Rerun/etc.? What works, what doesn’t?<p>• If there was a solution that actually made this easier, what would it have to do for you to adopt it?<p>I also put together a short (5 min) survey here: https://forms.gle/x57UReg8Yj9Gx7qZ8<p>If you’re willing to share your experiences in more detail, it would really help shape what we’re building.<p>We’ll anonymize responses and share the aggregated insights back with the community once we’ve collected enough.<p>Thanks in advance — I know this is a niche problem, but I figured HN has some of the sharpest robotics engineers, founders, and tinkerers out there. Really curious to hear how you’re solving this today.