Multirobot Coverage of Linear Modular Environments

Mirko Salaris, Alessandro Riva, Francesco Amigoni

Abstract:

Multirobot systems for covering environments are increasingly used in
applications like cleaning, industrial inspection, patrolling, and precision
agriculture. The problem of covering a given environment using multiple robots
can be naturally formulated and studied as a multi-Traveling Salesperson
Problem (mTSP). In a mTSP, the environment is represented as a graph and the
goal is to find tours (starting and ending at the same depot) for the robots in
order to visit all the vertices with minimum global cost, namely the length of
the longest tour. The mTSP is an NP-hard problem for which several
approximation algorithms have been proposed. These algorithms usually assume
generic environments, but tighter approximation bounds can be reached focusing
on specific environments. In this paper, we address the case of environments
composed of sub-parts, called modules, that can be reached from each other only
through some linking structures. Examples are multi-floor buildings, in which
the modules are the floors and the linking structures are the staircases or the
elevators, and floors of large hotels or hospitals, in which the modules are
the rooms and the linking structures are the corridors. We focus on linear
modular environments, with the modules organized sequentially, presenting an
efficient (with polynomial worst-case time complexity) algorithm that finds a
solution for the mTSP whose cost is within a bounded distance from the cost of
the optimal solution. The main idea of our algorithm is to allocate disjoint
"blocks" of adjacent modules to the robots, in such a way that each module is
covered by only one robot. We experimentally compare our algorithm against some
state-of-the-art algorithms for solving mTSPs in generic environments and show
that it is able to provide solutions with lower makespan and spending a
computing time several orders of magnitude shorter.