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title

SayTap: Language to Quadrupedal Locomotion

description

Use foot contact pattern to bridge LLM and low-level controller.

site name

SayTap: Language to Quadrupedal Locomotion

author

updated

2025-12-22 06:30:40

raw text

This page requires Javascript. Please enable it for https://saytap.github.io/ Examples of A1 following human commands in natural language Unlike text generation where Large Language Models (LLMs) directly interpret the atomic elements—tokens—it often proves challenging for LLMs to comprehend low-level robotic commands such as joint angle targets or motor torques, especially for inherently unstable legged robots necessitating high-frequency control signals. In this work, we propose to use foot contact patterns as an interface that bridges human instructions in natural language and low-level commands. The proposed approach allows the robot to take both simple and direct instructions (e.g., “Trot forward slowly”) as well as vague human commands (e.g., “Good news, we are going to a picnic this weekend!”) in natural language and react accordingly.. SayTap: Language to Quadrupedal Locomotion Yujin Tang Google DeepMind The University of Tokyo Wenhao Yu Goo...

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