  We study the problem of multi-agent navigation in static environments when no
centralized controller is present. Each agent is controlled individually and
relies on three algorithmic components to achieve its goal while avoiding
collisions with the other agents and the obstacles: i) individual path planning
which is done by Theta* algorithm; ii) collision avoidance while path following
which is performed by ORCA* algorithm; iii) locally-confined multi-agent path
planning done by Push and Rotate algorithm. The latter component is crucial to
avoid deadlocks in confined areas, such as narrow passages or doors. We
describe how the suggested components interact and form a coherent navigation
pipeline. We carry out an extensive empirical evaluation of this pipeline in
simulation. The obtained results clearly demonstrate that the number of
occurring deadlocks significantly decreases enabling more agents to reach their
goals compared to techniques that rely on collision-avoidance only and do not
include multi-agent path planning component
