Abstract:<br>
This paper presents algorithmic solutions for the complete coverage path 
planning problem using a team of mobile robots. Multiple robots decrease 
the time to complete the coverage, but maximal efficiency is only achieved 
if the number of regions covered multiple times is minimized. A set of 
multi-robot coverage algorithms is presented that minimize repeat coverage. 
The algorithms use the same planar cellbased decomposition as the 
Boustrophedon single robot coverage algorithm, but provide extensions to 
handle how robots cover a single cell, and how robots are allocated among 
cells. Specifically, for the coverage task our choice of multi-robot policy 
strongly depends on the type of communication that exists between the robots.  
When the robots operate under the line-of-sight communication restriction, 
keeping them as a team helps to minimize repeat coverage. When communication 
between the robots is available without any restrictions, the robots are 
initially distributed through space, and each one is allocated a 
virtually-bounded area to cover. A greedy auction mechanism is used for 
task/cell allocation among the robots. Experimental results from different 
simulated and real environments that illustrate our approach for different 
communication conditions are presented.