Ioannis Karamouzas,
Stephen J. Guy
We introduce the problem of navigating a group
of robots having prioritized formations amidst static and
dynamic obstacles. Our formulation allows users to define a
number of template formations, each with a specified priority
value. At each planning cycle, we compute a new formation
which accounts for both these priority values and the safe
progress of the robots towards their goal. To this end, we
introduce a new velocity-based navigation approach which we
denote as Formation Velocity Obstacles (FVO). Like other
velocity-based approaches, FVO allows anticipatory collision
avoidance accounting for the likely future motion of nearby
obstacles. However, we extend these previous approaches and
allow anisotropic agents which rotate themselves to orient
along their direction of travel. We integrate these FVOs with
a Bayesian framework to infer priority values for arbitrary
formations from the user-given templates. The result is a
complete framework for prioritized formation planning
