Hierarchical Intention Tracking for Robust Human-Robot Collaboration in Industrial Assembly Tasks

Collaborative robots require effective human intention estimation to safely and smoothly work with humans in less structured tasks such as industrial assembly, where human intention continuously changes. We propose the concept of intention tracking and introduce a collaborative robot system that concurrently tracks intentions at hierarchical levels. The high-level intention is tracked to estimate human's interaction pattern and enable robot to either (1) avoid collision with human to minimize interruption or (2) assist human to correct failure. The low-level intention estimate provides robot with task-specific information for concurrent task execution. We implement the system on a UR5e robot and demonstrate robust, seamless and ergonomic human-robot collaboration in an assembly use case through an ablative pilot study.