Multi-Robot Weighted Coverage Path Planning: a Solution based on the DARP Algorithm

Abstract

Covering a given area with a team of mobile robots in a minimum time is a well-studied problem with many real-world applications. A rarely studied subject, however, is the case of a weighted plane: due to the necessity of taking time-consuming measurements or having to traverse different kinds of terrains, the coverage time may vary over the environment and the path planning needs to be adapted accordingly. In this paper, we present an adapted version of a state-of-the-art mCPP (multi-robot coverage path planning) approach, the DARP algorithm, to make it suitable to deal with weighted environments.In particular, we propose several modifications to DARP that allow overcoming some of its limitations and, as a result, obtain an increased convergence rate and decreased convergence time with respect to the original version. Furthermore, as proved by extensive simulations, these improvements are also noticed in the unweighted version of the problem.

UGV Coverage Path Planning: An Energy-Efficient Approach through Turn Reduction

“…Over the past few decades, CPP has emerged as a critical field of study in robotics, prompting a surge in research exploring various aspects of this multifaceted problem [6][7][8][9][10][11][12][13][14][15][16][17][18][19]. The literature reveals a wide array of approaches to CPP, ranging from grid-based methods to graph-based ones, each exhibiting its strengths and shortcomings.…”

“…The authors of [17] present a modified version of the DARP algorithm, a widely recognized approach in the field of multi-robot coverage path planning. They extend the original algorithm to better accommodate environments with varying coverage time, owing to factors such as diverse terrains or the necessity for detailed measurements.…”

“…The scientific community has devoted considerable effort to addressing the offline multi-UGV CPP problem, with several intriguing strategies and methodologies emerging over the years [8][9][10][11][12][13][17][18][19][20][21][22]. A fundamental insight that underpins many of these methodologies is that the multi-UGV CPP problem can, under certain circumstances, be reduced to multiple single-robot CPP problems.…”

Area Division Using Affinity Propagation for Multi-Robot Coverage Path Planning

“…An interesting approach was proposed by Idir et al [19], who suggested a multi-robot CPP algorithm based on the DARP algorithm. The authors sought to tackle the problem of weight allocation for multi-robot coverage using a weighted approach.…”

“…The complexity of CPP intensifies when we move from single-robot systems to multirobot systems. Multi-robot CPP involves devising paths for multiple robots to ensure comprehensive and efficient coverage of a larger or more complex area [17][18][19][20][21][22][23][24][25][26]. A pressing issue in multi-robot CPP is the division of the operational area among the robots, a problem known as the 'area division problem'.…”