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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Beyond Pick-and-Place: Tackling Robotic Stacking of Diverse Shapes · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/2110.06192/</link><description>Collected HN comments and submissions linking this paper.</description><language>en</language><lastBuildDate>Mon, 02 Nov 2026 11:16:22 GMT</lastBuildDate><atom:link href="https://hackerpaper.kaipfister.de/p/2110.06192/feed.xml" rel="self" type="application/rss+xml" /><item><title>Beyond Pick-and-Place: Tackling Robotic Stacking of Diverse Shapes — mentioned by jah242</title><link>https://news.ycombinator.com/item?id=31054753</link><guid isPermaLink="false">urn:hackerpapers:mention:2110.06192:31054753</guid><pubDate>Sat, 16 Apr 2022 18:26:26 GMT</pubDate><description>&lt;p&gt;This would be one example from Deepmind using raw pixel input to stack objects. This has a relatively detailed reward function (but is also a very complicated task) - https://arxiv.org/abs/2110.06192 There are other examples from OpenAI a while back using even just sparse rewards (i.e binary 1, 0 for success or failure over the whole task) - but these weren&amp;#x27;t pixel input if I remember correctly - https://openai.com/blog/ingredients-for-robotics-research/ I m afraid if you think providing any reward function is cheating then we have fundamentally different views of what AI/ML even…&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2110.06192/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.RO</category></item></channel></rss>
