  In this paper we outline the approach of solving special type of navigation
tasks for robotic systems, when a coalition of robots (agents) acts in the 2D
environment, which can be modified by the actions, and share the same goal
location. The latter is originally unreachable for some members of the
coalition, but the common task still can be accomplished as the agents can
assist each other (e.g. by modifying the environment). We call such tasks smart
relocation tasks (as the can not be solved by pure path planning methods) and
study spatial and behavior interaction of robots while solving them. We use
cognitive approach and introduce semiotic knowledge representation - sign world
model which underlines behavioral planning methodology. Planning is viewed as a
recursive search process in the hierarchical state-space induced by sings with
path planning signs reside on the lowest level. Reaching this level triggers
path planning which is accomplished by state of the art grid-based planners
focused on producing smooth paths (e.g. LIAN) and thus indirectly guarantying
feasibility of that paths against agent's dynamic constraints.
