  For large-scale tasks, coverage path planning (CPP) can benefit greatly from
multiple robots. In this paper, we present an efficient algorithm MSTC* for
multi-robot coverage path planning (mCPP) based on spiral spanning tree
coverage (Spiral-STC). Our algorithm incorporates strict physical constraints
like terrain traversability and material load capacity. We compare our
algorithm against the state-of-the-art in mCPP for regular grid maps and real
field terrains in simulation environments. The experimental results show that
our method significantly outperforms existing spiral-STC based mCPP methods.
Our algorithm can find a set of well-balanced workload distributions for all
robots and therefore, achieve the overall minimum time to complete the
coverage.
