Multi-robot forest coverage

Abstract

Abstract-One of the main applications of mobile robots is terrain coverage: visiting each location in known terrain. Terrain coverage is crucial for lawn mowing, cleaning, harvesting, search-and-rescue, intrusion detection and mine clearing. Naturally, coverage can be sped up with multiple robots. In this paper, we describe Multi-Robot Forest Coverage, a new multirobot coverage algorithm based on an algorithm by Even et al. for finding a tree cover with trees of balanced weights. The cover time of Multi-Robot Forest Coverage is at most eight times larger than optimal, and our experiments show it to perform significantly better than existing multi-robot coverage algorithms.

Multi-Agent Deep Reinforcement Learning for Multi-Robot Applications: A Survey

“…CPP is one of the most popular topics in robotics. For multi-robot coverage, several popular algorithms exist even with performance guarantees and worst-case time bounds [ 146 , 147 , 148 , 149 ]. In exploration, however, the objective might not be the same as the multi-robot CPP problem.…”

Chaotic Motion Planning for Mobile Robots: Progress, Challenges, and Opportunities

“…In terms of adaptability to unknown environments, CPP algorithms are classified into offline algorithms and online algorithms. Offline algo-rithms [91][92][93][94][95][96][97][98][99][100][101][102][103][104][105][106] need full knowledge of the map and any obstacles in the space must be stationary. The assumption of a priori known environments will usually lead to more efficient coverage, but this assumption is not applicable to many dynamic real-world situations.…”

I Have a Robot, and I'm Not Afraid to Use It!

“…Most multirobot research to date, within the robotics community, focuses on a single task at a time. Some examples of such canonical tasks include moving while maintaining formations (Balch and Arkin 1998; Fredslund and Mataric 2002; Desai, Ostrowski, and Kumar 2001; Carpin and Parker 2002; Inalhan, Busse, and How 2000; Kaminka, Schechter‐Glick, and Sadov 2008; Elmaliach and Kaminka 2008), multirobot coverage (Williams and Burdick 2006; Ferranti, Trigoni, and Levene 2007; Rekleitis et al 2004; Zheng et al 2005; Rekleitis, Dudek, and Milios 2001; Batalin and Sukhatme 2002; Wagner and Bruckstein 1997; Butler, Rizzi, and Hollis 2000; Hazon and Kaminka 2008; Agmon, Hazon, and Kaminka 2008), foraging (Goldberg and Mataríc 2001; Rybski et al 1998; Rosenfeld et al 2008; Zuluaga and Vaughan 2005; Schneider‐Fontan and Mataríc 1996; Jager and Nebel 2002; Ostergaard, Sukhatme, and Mataríc 2001; Kaminka, Erusalimchik, and Kraus 2010), and patrolling or surveillance (Elmaliach, Shiloni, and Kaminka 2008; Agmon, Kraus, and Kaminka 2008; Agmon et al 2008; Jensen et al 2011; Basilico, Gatti, and Amigoni 2009; Smith, Schwager, and Rus 2011; Agmon, Urieli, and Stone 2011; Marino et al 2009; Delle Fave et al 2009). Many of these are approached from the perspective of distributed control.…”