<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Article-Journal on Chenhao Li</title><link>https://breadli428.github.io/publication_types/article-journal/</link><description>Recent content in Article-Journal on Chenhao Li</description><generator>Hugo</generator><language>en-us</language><lastBuildDate>Sun, 19 Apr 2026 00:00:00 +0000</lastBuildDate><atom:link href="https://breadli428.github.io/publication_types/article-journal/index.xml" rel="self" type="application/rss+xml"/><item><title>Learning Whole-Body Humanoid Locomotion via Motion Generation and Motion Tracking</title><link>https://breadli428.github.io/publication/ral2026-1/</link><pubDate>Sun, 01 Jan 2017 00:00:00 +0000</pubDate><guid>https://breadli428.github.io/publication/ral2026-1/</guid><description>Whole-body humanoid locomotion is challenging due to high-dimensional control, morphological instability, and the need for real-time adaptation to various terrains using onboard perception.</description></item><item><title>PAINT: Partner-Agnostic Intent-Aware Cooperative Transport with Legged Robots</title><link>https://breadli428.github.io/publication/ral2026-3/</link><pubDate>Sun, 01 Jan 2017 00:00:00 +0000</pubDate><guid>https://breadli428.github.io/publication/ral2026-3/</guid><description>Collaborative transport requires robots to infer partner intent through physical interaction while maintaining stable loco-manipulation.</description></item><item><title>Scaling Rough Terrain Locomotion with Automatic Curriculum Reinforcement Learning</title><link>https://breadli428.github.io/publication/ral2026-2/</link><pubDate>Sun, 01 Jan 2017 00:00:00 +0000</pubDate><guid>https://breadli428.github.io/publication/ral2026-2/</guid><description>Curriculum learning has demonstrated substantial effectiveness in robot learning.</description></item><item><title>Multi-Domain Motion Embedding: Expressive Real-Time Mimicry for Legged Robots</title><link>https://breadli428.github.io/publication/ijrr2026/</link><pubDate>Sun, 01 Jan 2017 00:00:00 +0000</pubDate><guid>https://breadli428.github.io/publication/ijrr2026/</guid><description>Effective motion representation is crucial for enabling robots to imitate expressive behaviors in real time, yet existing motion controllers often ignore inherent patterns in motion.</description></item></channel></rss>