A New Paradigm of Human-robot Dialogue Facilitating Human and Robot Teaming in Sample Exploration - Fu, Yan; Wang, Hao; Xue, Shuqi; Zhang, Bojun; Cheng, Jianmei; Gao, Zhengke (2023 IEEE International Conference on Real-time Computing and Robotics (RCAR), 2023)
When human-robot collaboration is used as an optimal for conducting sample collection for lunar missions, the heterogeneity between human and robot spatial information processing modes pose a challenge to the human-robot collaboration. To address the communication obstacles, a conceptual framework, named Co-SRP is constructed, integrating perception of current scenarios, comprehension of elements observed in complete task context, and the prediction of the system and task's status in the near term to achieve spatial co-awareness. The proposed framework's effectiveness was validated on a simulation platform for lunar surface sampling missions. The results indicate that the framework improved the lunar surface sampling robot's ability to understand astronaut guidance commands and increased efficiency in human-robot collaboration.