<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>International Conference | Takato Horii | Osaka University</title><link>https://www.takatohorii.jp/en/tags/international-conference/</link><atom:link href="https://www.takatohorii.jp/en/tags/international-conference/index.xml" rel="self" type="application/rss+xml"/><description>International Conference</description><generator>HugoBlox Kit (https://hugoblox.com)</generator><language>en-us</language><lastBuildDate>Thu, 28 May 2026 00:00:00 +0000</lastBuildDate><image><url>https://www.takatohorii.jp/media/icon_hu_da05098ef60dc2e7.png</url><title>International Conference</title><link>https://www.takatohorii.jp/en/tags/international-conference/</link></image><item><title>Presenting "TARAD" at ICRA 2026</title><link>https://www.takatohorii.jp/en/blog/icra2026-tarad/</link><pubDate>Thu, 28 May 2026 00:00:00 +0000</pubDate><guid>https://www.takatohorii.jp/en/blog/icra2026-tarad/</guid><description>&lt;p&gt;I will present our paper &amp;ldquo;TARAD: Task-Aware Robot Affordance-Centric Diffusion Policy Learned from LLM-Generated Demonstrations&amp;rdquo; at the &lt;strong&gt;IEEE International Conference on Robotics and Automation (ICRA 2026)&lt;/strong&gt;, held June 1–5, 2026 in Vienna, Austria.&lt;/p&gt;
&lt;p&gt;TARAD is a framework that uses large language models (LLMs) and vision-language models (VLMs) to perform high-level planning from natural language instructions and to extract affordance information, enabling the training of a multi-task 3D diffusion policy without relying on expert demonstrations or predefined motion primitives. Empirical evaluations in both the RLBench simulation environments and real-world experiments with a UR5e robot show that TARAD combines the precise control of imitation learning with the strong generalization of foundation models.&lt;/p&gt;
&lt;ul&gt;
&lt;li&gt;&lt;strong&gt;Session:&lt;/strong&gt; TuI1I Interactive Session 1 (Hall C)&lt;/li&gt;
&lt;li&gt;&lt;strong&gt;Date &amp;amp; Time:&lt;/strong&gt; Tuesday, June 2, 2026, 09:00–10:30&lt;/li&gt;
&lt;li&gt;&lt;strong&gt;Authors:&lt;/strong&gt; Site Hu, Takayuki Nagai, Takato Horii (The University of Osaka)&lt;/li&gt;
&lt;/ul&gt;
&lt;p&gt;The paper is published in &lt;em&gt;IEEE Robotics and Automation Letters&lt;/em&gt;. See the
for more details.&lt;/p&gt;</description></item></channel></rss>