  Intentional or unintentional contacts are bound to occur increasingly more
often due to the deployment of autonomous systems in human environments. In
this paper, we devise methods to computationally predict imminent collisions
between objects, robots and people, and use an upper-body humanoid robot to
block them if they are likely to happen. We employ statistical methods for
effective collision prediction followed by sensor-based trajectory generation
and real-time control to attempt to stop the likely collisions using the most
favorable part of the blocking robot. We thoroughly investigate collisions in
various types of experimental setups involving objects, robots, and people.
Overall, the main contribution of this paper is to devise sensor-based
prediction, trajectory generation and control processes for highly articulated
robots to prevent collisions against people, and conduct numerous experiments
to validate this approach.
