  Robots sharing their space with humans need to be proactive in order to be
helpful. Proactive robots are able to act on their own initiative in an
anticipatory way to benefit humans. In this work, we investigate two ways to
make robots proactive. One way is to recognize humans' intentions and to act to
fulfill them, like opening the door that you are about to cross. The other way
is to reason about possible future threats or opportunities and to act to
prevent or to foster them, like recommending you to take an umbrella since rain
has been forecasted. In this paper, we present approaches to realize these two
types of proactive behavior. We then present an integrated system that can
generate proactive robot behavior by reasoning on both factors: intentions and
predictions. We illustrate our system on a sample use case including a domestic
robot and a human. We first run this use case with the two separate proactive
systems, intention-based and prediction-based, and then run it with our
integrated system. The results show that the integrated system is able to take
into account a broader variety of aspects that are needed for proactivity.
