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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Point Policy: Unifying Observations and Actions with Key Points for Robot Manipulation · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/2502.20391/</link><description>Collected HN comments and submissions linking this paper.</description><language>en</language><lastBuildDate>Mon, 02 Nov 2026 11:27:26 GMT</lastBuildDate><atom:link href="https://hackerpaper.kaipfister.de/p/2502.20391/feed.xml" rel="self" type="application/rss+xml" /><item><title>Point Policy: Unifying Observations and Actions with Key Points for Robot Manipulation — HN submission</title><link>https://news.ycombinator.com/item?id=43243820</link><guid isPermaLink="false">urn:hackerpapers:submission:2502.20391:43243820</guid><pubDate>Mon, 03 Mar 2025 16:57:32 GMT</pubDate><description>&lt;p&gt;Show HN: Why spend $$$ on data when robots can learn from us?&lt;/p&gt;&lt;p&gt;We just released Point Policy, a framework that allows robots to learn by directly copying humans. Point Policy does not need robot data, motion planning, simulators, or interactions. While the robotics community has been spending millions of $$$ on collecting huge robot datasets, we show that with just 30 videos of a human performing a task (less than 15 mins of human effort), we can teach robots to perform complex tasks in unseen scenarios with new objects. Here is a thread on X (prev Twitter) with visuals - https://x.com/haldar_siddhant/status/1895518805151138274 Would love to hear the…&lt;/p&gt;&lt;p&gt;4 points; 0 discussion replies on HN. &lt;a href="https://hackerpaper.kaipfister.de/p/2502.20391/"&gt;Paper and source history&lt;/a&gt;. A submission is not an endorsement.&lt;/p&gt;</description><category>cs.RO</category></item></channel></rss>
