Supporting task-oriented collaboration in human-robot teams using semantic-based path planning

摘要

Improvements in robot autonomy are changing the human-robot interaction from low-level manipulation to high-level task-based collaboration. For a task-oriented collaboration, a human assigns sub-tasks to robot team members. In this paper, we consider task-oriented collaboration of humans and robots in a cordon and search problem. We focus on a path-planning framework with natural language input. By the semantic elements in a shared mental model, a natural language command can be converted into optimization objectives. We import multi-objective optimization to facilitate modeling the “adverb” elements in natural language commands. Finally, human interactions are involved in the optimization search process in order to guarantee that the found solution correctly reflects the human’s intent.