  We consider the configuration formation problem in modular robotic systems
where a set of singleton modules that are spatially distributed in an
environment are required to assume appropriate positions so that they can
configure into a new, user-specified target configuration, while simultaneously
maximizing the amount of information collected while navigating from their
initial to final positions. Each module has a limited energy budget to expend
while moving from its initial to goal location. To solve this problem, we
propose a budget-limited, heuristic search-based algorithm that finds a path
that maximizes the entropy of the expected information along the path. We have
analytically proved that our proposed approach converges within finite time.
Experimental results show that our planning approach has lower run-time than an
auction-based allocation algorithm for selecting modules' spots.
