  Human robot collaboration (HRC) is becoming increasingly important as the
paradigm of manufacturing is shifting from mass production to mass
customization. The introduction of HRC can significantly improve the
flexibility and intelligence of automation. However, due to the stochastic and
time-varying nature of human collaborators, it is challenging for the robot to
efficiently and accurately identify the plan of human and respond in a safe
manner. To address this challenge, we propose an integrated human robot
collaboration framework in this paper which includes both plan recognition and
trajectory prediction. Such a framework enables the robots to perceive, predict
and adapt their actions to the human's plan and intelligently avoid collisions
with the human based on the predicted human trajectory. Moreover, by explicitly
leveraging the hierarchical relationship between the plan and trajectories,
more robust plan recognition performance can be achieved. Experiments are
conducted on an industrial robot to verify the proposed framework, which shows
that our proposed framework can not only assure safe HRC, but also improve the
time efficiency of the HRC team, and the plan recognition module is not
sensitive to noises.
