Abstract
When robots work with humans for a collaborative task, they need to plan their actions while taking humans’ actions into account. The state-of-the-art optimization-based human-aware task planner plans robot actions by prioritizing the actions that are parallel to the human's actions. However, the limitation of this approach is that the robot execution time for each action, which is an important parameter for the optimization problem, is fixed. In this paper, we investigate how online robot execution time estimation can increase the time efficiency of such a human-aware task planner. We propose a direct time estimation method and an analytical time estimation method. An integrated task and trajectory planning framework is also presented. Experiments show that online robot execution time estimation increases the time efficiency of the collaborative task. Moreover, the results of the direct time estimation method are more accurate than those of the analytical method.
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