Information collection is an important application of multirobot systems especially in environments that are difficult to operate for humans. The objective of the robots is to maximize information collection from the environment while remaining in their path-length budgets. In this paper, we propose a novel multi-robot information collection algorithm that uses a continuous region partitioning approach to efficiently divide an unknown environment among the robots based on the discovered obstacles in the area, for better loadbalancing. Our algorithm gracefully handles situations when some of the robots cannot communicate with other robots due to limited communication ranges.