Coordinated multi-robot exploration

By Wolfram Burgard, Mark Moors, Cyrill Stachniss, Frank E. Schneider. IEEE Transactions on robotics, 2005

1,291 citations recorded by the source corpus.

In this paper, we consider the problem of exploring an unknown environment with a team of robots. As in single-robot exploration the goal is to minimize the overall exploration time. The key problem to be solved in the context of multiple robots is to choose appropriate target points for the individual robots so that they simultaneously explore different regions of the environment. We present an approach for the coordination of multiple robots, which simultaneously takes into account the cost of reaching a target point and its utility. Whenever a target point is assigned to a specific robot, the utility of the unexplored area visible from this target position is reduced. In this way, different target locations are assigned to the individual robots. We furthermore describe how our algorithm can be extended to situations in which the communication range of the robots is limited. Our technique has been implemented and tested extensively in real-world experiments and simulation runs. The results demonstrate that our technique effectively distributes the robots over the environment and allows them to quickly accomplish their mission.

Subfields: Computer Networks and Communications, Mechanical Engineering

View Paper: https://www.semanticscholar.org/paper/ce81a0b905dcfc206d5122dd93785be3d1f40bc7

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In Computer Networks and Communications

In Mechanical Engineering

Citations in the corpus

Past, Present, and Future of Simultaneous Localization and Mapping: Toward the Robust-Perception Age (2016, neutral): “of the evaluation grows exponentially with the search space which proves to be computationally intractable in real applications [33, 185].”
Multiple‐Robot Simultaneous Localization and Mapping: A Review (2016, background): “Multiple-robot exploration (Rekleitis et al., 2001; Zlot et al., 2002; Burgard and Schneider, 2002; Sheng et al., 2006; Burgard et al., 2005; Wurm et al., 2008) is also another interesting topic which is tightly coupled with multiple-robot SLAM.”
Distributed Multirobot Exploration and Mapping (2005, methodology): “If the robots know their relative locations and share a map of the area they explored so far, then effective coordination can be achieved by guiding the robots into different, non-overlapping areas of the environment [1], [29], [37], [2].”
Coordinated multi-robot exploration using a segmentation of the environment (2008, background): “Furthermore, there has been research on how to deal with limited communication in the context of multi-robot exploration [3], [19].”
A Survey on Active Simultaneous Localization and Mapping: State of the Art and New Frontiers (2022, methodology): “Early works such as [105], [223] present an approach for choosing appropriate frontiers, while simultaneously taking into account their utility and the cost of reaching them.”
DAvinCi: A cloud computing framework for service robots (2010, background): “The papers [8], [9], [10] describe algorithms, techniques and approaches for a network of robots for coordinated exploration and map building.”
Trajectory tracking for non-holonomic cars: A linear approach to controlled leader-follower formation (2010, background): “Areas of interest include: space exploration, in the context of robot assisted construction of space stations [2], security surveillance [8], hazardous cleaning labors [23] and exploration of unknown, or dangerous, environments [3], [13].”
Voronoi-Based Multi-Robot Autonomous Exploration in Unknown Environments via Deep Reinforcement Learning (2020, background): “Frontier-based techniques have been widely used in the multirobot exploration missions, motivated by [16], [17], [34], the proposed cooperative exploration strategy in the first layer is introduced in this section.”
Simultaneous Localization and Mapping: A Survey of Current Trends in Autonomous Driving (2017, neutral): “Some approaches have chosen to consider that the initial distance between the vehicles is known beforehand [232][220].”
Distributed Control of Robotic Networks: A Mathematical Approach to Motion Coordination Algorithms (2009, background): “Recent works on multi-robot exploration of unknown environments include [Batalin and Sukhatme, 2004, Burgard et al., 2005, Howard et al., 2006].”
Coordinated Multi-Robot Exploration Under Communication Constraints Using Decentralized Markov Decision Processes (2012, methodology): “Burgard et al. (2005) apply their multi-robot strategy to each sub-team of robots which are able to communicate with each other.”
On the use of simulation in robotics: Opportunities, challenges, and suggestions for moving forward (2020, background): “Simulation can play an important role in providing insights into multirobot, collaborative scenarios (12, 13).”