ADAPT: An End-to-End Framework for Interactive, Text-Conditioned Humanoid Control

Summary

The Robotic Systems Lab presents ADAPT, an end-to-end framework for interactive, text-conditioned humanoid control, at the CoRL conference. Unlike dominant pipelines that generate kinematic motions for a separate RL tracker, ADAPT solves humanoid language control end-to-end in a closed-loop manner, allowing the robot to continuously respond to changing commands. The project page is available at https://wuyan01.github.io/ADAPT-project/.

Editorial context

The authors present ADAPT as an end-to-end framework for interactive, text-conditioned humanoid control at the CoRL conference, contrasting their closed-loop approach with dominant pipelines that generate kinematic motions for a separate RL tracker; claims regarding performance and deployment readiness are attributed to the RSS publication.

Source: ETH Robotic Systems Lab — X · Read original article ↗

Article text · Original source · English

In our latest work @corl_conf, we present ADAPT: an end-to-end framework for interactive, text-conditioned humanoid control, in contrast to dominant pipelines that generate kinematic motions for a separate RL tracker. 🤖

🌐 https://wuyan01.github.io/ADAPT-project/

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What the source reports

Publisher-reported claims, with original evidence. These results have not been independently verified by RoboSignal.

code: not_reported
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dataset: not_reported

Source excerpts and review record

Automatically extracted; no manual editorial approval recorded.

Instead, in our @corl_conf work ADAPT, we solve humanoid language control end-to-end closed-loop, where the robot must continuously respond to changing commands.
Open source S6

In our latest work @corl_conf, we present ADAPT: an end-to-end framework for interactive, text-conditioned humanoid control, in contrast ...
Open source S1

In our latest work @corl_conf, we present ADAPT: an end-to-end framework for interactive, text-conditioned humanoid control, in contrast to dominant pipelines that generate kinematic motions for a separate RL tracker. 🤖
Open source S2

Quoted postChenhao Li @ CoRL@breadli428

Dominant text-to-motion pipelines generate kinematic motions for a separate tracker. Instead, in our @corl_conf work ADAPT, we solve humanoid language control end-to-end closed-loop, where the robot must continuously respond to changing commands. 🌐Page: https://wuyan01.github.io/ADAPT-project/

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