  A flexible operation of multiple robotic manipulators in a shared workspace
requires an online trajectory planning with static and dynamic collision
avoidance. In this work, we propose a real-time capable motion control
algorithm, based on non-linear model predictive control, which accounts for
static and dynamic collision avoidance. The proposed algorithm is formulated as
a non-cooperative game, where each robot is considered as an agent. Each agent
optimizes its own motion and accounts for the predicted movement of surrounding
agents. We propose a novel approach to formulate the dynamic collision
constraints. Additionally, we account for deadlocks that might occur in a setup
of multiple robotic manipulators. We validate our algorithm on a pick and place
scenario for four collaborative robots operating in a common workspace in the
simulation environment Gazebo. The robots are controlled by the Robot Operating
System (ROS). We demonstrate, that our approach is real-time capable and, due
to the distributed nature of the approach, easily scales to an arbitrary number
of robot manipulators in a shared workspace.
