Strazdas Dominykas, Busch Matthias, Shaji Rijin, Siegert Ingo, Al-Hamadi Ayoub
Neuro-Information Technology Group, Faculty of Electrical Engineering and Information Technology, Otto-von-Guericke-University, Magdeburg, Germany.
Mobile Dialog Systems, Faculty of Electrical Engineering and Information Technology, Otto-von-Guericke-University, Magdeburg, Germany.
Front Robot AI. 2025 Jul 30;12:1561188. doi: 10.3389/frobt.2025.1561188. eCollection 2025.
Future work scenarios envision increased collaboration between humans and robots, emphasizing the need for versatile interaction modalities. Robotic systems can support various use cases, including on-site operations and telerobotics. This study investigates a hybrid interaction model in which a single user engages with the same robot both on-site and remotely. Specifically, the Robot System Assistant (RoSA) framework is evaluated to assess the effectiveness of touch and speech input modalities in these contexts. The participants interact with two robots, and , utilizing both input modalities. The results reveal that touch input excels in precision and task efficiency, while speech input is preferred for its intuitive and natural interaction flow. These findings contribute to understanding the complementary roles of touch and speech in hybrid systems and their potential for future telerobotic applications.
未来的工作场景设想人类与机器人之间的协作会增加，强调了通用交互方式的必要性。机器人系统可以支持各种用例，包括现场操作和远程机器人技术。本研究调查了一种混合交互模型，其中单个用户在现场和远程与同一机器人进行交互。具体而言，对机器人系统助手（RoSA）框架进行了评估，以评估在这些情况下触摸和语音输入方式的有效性。参与者使用这两种输入方式与两个机器人 和 进行交互。结果表明，触摸输入在精度和任务效率方面表现出色，而语音输入因其直观自然的交互流程而更受青睐。这些发现有助于理解触摸和语音在混合系统中的互补作用及其在未来远程机器人应用中的潜力。
