Interacting physically with robots and sharing environment with them leads to situations where humans and robots have to cross each other in narrow corridors. In these cases, the robot has to make space for the human to pass. From observation of human-human crossing behaviours, we isolated two main factors in this avoiding behaviour: body rotation and sliding motion. We implemented a robot controller able to vary these factors and explored how this variation impacted on people's perception. Results from a within-participants study involving 23 participants show that people prefer a robot rotating its body when crossing them. Additionally, a sliding motion is rated as being warmer. These results show the importance of social avoidance when interacting with humans.
MindEye-OmniAssist: A Gaze-Driven LLM-Enhanced Assistive Robot System for Implicit Intention Recognition and Task Execution
Hubei Key Laboratory of Brain-Inspired Intelligent Systems, Huazhong University of Science and Technology(脑启发智能系统湖北省重点实验室,华中科技大学);Key Laboratory of the Ministry of Education for Image Processing and Intelligent Control, School of Artificial Intelligence and Automation, Huazhong University of Science and Technology(图像处理与智能控制教育部重点实验室,人工智能与自动化学院,华中科技大学);state key laboratory of intelligent vehicle safety technology, chongqing changan automobile co ltd(智能车辆安全技术 state key laboratory,重庆长安汽车有限公司);Science and technology innovation center, China ship development and design centre(科技创新中心,中国船舶工业设计研究中心)
Perspective-Shifted Neuro-Symbolic World Models: A Framework for Socially-Aware Robot Navigation
Institute for Systems and Robotics, Instituto Superior Técnico, Universidade de Lisboa(系统机器人研究所,理工学院,里斯本大学);LAAS-CNRS, Artificial and Natural Intelligence Toulouse Institute (ANITI)(LAAS-CNRS,图卢兹人工智能研究所(ANITI))