Integrating Field of View in Human-Aware Collaborative Planning

TL;DR

This paper introduces a novel hierarchical planning approach that incorporates human field of view into human-robot collaboration, improving efficiency by reducing interruptions and redundant actions.

Contribution

It presents a new FOV-aware probabilistic planning framework and an efficient hierarchical online planner for better human-robot collaboration.

Findings

FOV-aware planner reduces human interruptions.

Improved collaboration efficiency in cooking domain.

Effective in virtual reality kitchen environment.

Abstract

In human-robot collaboration (HRC), it is crucial for robot agents to consider humans' knowledge of their surroundings. In reality, humans possess a narrow field of view (FOV), limiting their perception. However, research on HRC often overlooks this aspect and presumes an omniscient human collaborator. Our study addresses the challenge of adapting to the evolving subtask intent of humans while accounting for their limited FOV. We integrate FOV within the human-aware probabilistic planning framework. To account for large state spaces due to considering FOV, we propose a hierarchical online planner that efficiently finds approximate solutions while enabling the robot to explore low-level action trajectories that enter the human FOV, influencing their intended subtask. Through user study with our adapted cooking domain, we demonstrate our FOV-aware planner reduces human's interruptions and redundant actions during collaboration by adapting to human perception limitations. We extend these findings to a virtual reality kitchen environment, where we observe similar collaborative behaviors.