Cross-modality Force and Language Embeddings for Natural Human-Robot Communication
Ravi Tejwani, Karl Velazquez, John Payne, Paolo Bonato, Harry Asada
- 发表年份
- 2025
- 访问权限
- 开放获取
摘要
A method for cross-modality embedding of force profile and words is presented for synergistic coordination of verbal and haptic communication. When two people carry a large, heavy object together, they coordinate through verbal communication about the intended movements and physical forces applied to the object. This natural integration of verbal and physical cues enables effective coordination. Similarly, human-robot interaction could achieve this level of coordination by integrating verbal and haptic communication modalities. This paper presents a framework for embedding words and force profiles in a unified manner, so that the two communication modalities can be integrated and coordinated in a way that is effective and synergistic. Here, it will be shown that, although language and physical force profiles are deemed completely different, the two can be embedded in a unified latent space and proximity between the two can be quantified. In this latent space, a force profile and words can a) supplement each other, b) integrate the individual effects, and c) substitute in an exchangeable manner. First, the need for cross-modality embedding is addressed, and the basic architecture and key building block technologies are presented. Methods for data collection and implementation challenges will be addressed, followed by experimental results and discussions.
关键词
相关论文
工业5.0中人机协作的多模态感知、互认知与具身执行综述与展望
Kai Ding, Qingyuan Mao, Yaqian Zhang 等 6 位作者
Robotics and Computer-Integrated Manufacturing · 2026
迈向以人为中心的制造:人机协作装配中不确定性下的任务规划
Yingchao You, Ze Ji, Changyun Wei
Robotics and Computer-Integrated Manufacturing · 2026
代理式人机协作:通过记忆实现上下文对齐
Jiahui Si, Wenchao Li, Xi Chen 等 7 位作者
Robotics and Computer-Integrated Manufacturing · 2026
自适应物理信息Transformer结合高斯过程残差补偿用于人机协作中的逆动力学建模
Rui Qian, Xi Zhang, Dongpeng Li 等 5 位作者
Robotics and Computer-Integrated Manufacturing · 2026