外观
论文arXiv 2610.0382826 天前
TACET：面向四足机器人的情境适宜声学-社交导航
原文链接：TACET: Context-Appropriate Acoustic-Social Navigation for Quadrupeds（arXiv 2610.03828 · 发布日期：2026-10-02）
TACET: Context-Appropriate Acoustic-Social Navigation for Quadrupeds
TACET针对四足机器人噪声社交导航，用视觉语言推理与反应控制协同，在真实四足机器人场景中验证。
核心要点
- 问题：医院、养老院和安静办公室中，足地撞击噪声本身也是社交变量。
- 方法：从自我视角推断社交情境，用紧凑行为token同时调节社交代价图与静音运动策略。
- 实验：真实四足机器人同速下噪声最高降低9.3 dBA，跨场景保持100%个人空间合规。
- 结果与开放：完整方法实现低声学侵扰（≤2.9 dBA），项目页面已公开。
验证范围与局限：验证范围为真实四足机器人上的所评估场景。
英文摘要 (Abstract)
Quadruped robots entering hospitals, care homes, and quiet offices must be context-appropriate not only in where they move but in how loudly they move: a legged robot's locomotion noise, dominated by foot-ground impacts, is itself a social variable. Prior social navigation respects human space but treats the robot as acoustically uniform, while quiet-locomotion methods reduce noise to an operator-specified, context-blind level. We present TACET, a context-appropriate acoustic-social navigation method that infers social context from the robot's egocentric view and decides both where it walks and how loudly, coupling a slow fine-tuned vision-language reasoner to a fast reactive controller through a single compact behavior token, . The same token conditions both a social costmap (where to go) and a quiet locomotion policy (how loudly to move), while a structured out-of-view memory keeps recently seen people in the reasoner's context after they leave the camera view. On a real quadruped, context-conditioned locomotion lowers locomotion noise by up to 9.3 dBA at matched speed, and across our scenarios the full method keeps personal-space compliance at 100% with low acoustic intrusion (<=2.9 dBA), jointly improving spatial and acoustic performance in the evaluated scenarios. The project page is available at https://rcilab.khu.ac.kr/tacet/.
作者：박성산, Young-Sik Shin, 김상현
来源
本页事实对应的公开页面，以原文为准。