Multi-robot Cooperative Systems for Exploration: Advances in Dealing with Constrained Communication Environments

Benavides, Facundo; Monzón, Pablo; Chanel, Caroline Ponzoni Carvalho; Grampín, Eduardo

doi:10.1109/lars-sbr.2016.37

Cited by 5 publications

(2 citation statements)

References 32 publications

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“…In multi-robot exploration, it is crucial for the robots to cover various search areas to explore the environment and create a useful map effectively. This requirement applies to diverse fields, including industrial applications, like automated lawnmowers or vacuum cleaners, military operations, such as mine clearance, and humanitarian efforts like search and rescue operations [5]. This section summarizes relevant works related to multi-target search and compares them with our proposal.…”

Section: Related Workmentioning

confidence: 99%

Inverse Firefly-Based Search Algorithms for Multi-Target Search Problem

Zedadra,

Guerrieri,

Seridi

et al. 2024

BDCC

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Efficiently searching for multiple targets in complex environments with limited perception and computational capabilities is challenging for multiple robots, which can coordinate their actions indirectly through their environment. In this context, swarm intelligence has been a source of inspiration for addressing multi-target search problems in the literature. So far, several algorithms have been proposed for solving such a problem, and in this study, we propose two novel multi-target search algorithms inspired by the Firefly algorithm. Unlike the conventional Firefly algorithm, where light is an attractor, light represents a negative effect in our proposed algorithms. Upon discovering targets, robots emit light to repel other robots from that region. This repulsive behavior is intended to achieve several objectives: (1) partitioning the search space among different robots, (2) expanding the search region by avoiding areas already explored, and (3) preventing congestion among robots. The proposed algorithms, named Global Lawnmower Firefly Algorithm (GLFA) and Random Bounce Firefly Algorithm (RBFA), integrate inverse light-based behavior with two random walks: random bounce and global lawnmower. These algorithms were implemented and evaluated using the ArGOS simulator, demonstrating promising performance compared to existing approaches.

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Section: Related Workmentioning

confidence: 99%

Inverse Firefly-Based Search Algorithms for Multi-Target Search Problem

Zedadra,

Guerrieri,

Seridi

et al. 2024

BDCC

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“…Most of the target to robot assignments are based on an utility function that defines the advantage that a robot have to reach this target according to the mission's aim [5]. The work proposed in [2] presents a new utility function that takes into account the traveling cost to the target and the connectivity utility. This allows a trade off between minimizing the amount of exploration time and connectivity.…”

Section: Related Workmentioning

confidence: 99%

Communicating Multi-UAV System for Cooperative SLAM-based Exploration

Mahdoui

Frémont

Natalizio

2019

J Intell Robot Syst

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In the context of multi-robot system and more generally for Technological System-of-Systems, this paper proposes a multi-UAV (Unmanned Aerial Vehicle) framework for SLAM-based cooperative exploration under limited communication bandwidth. The exploration strategy, based on RGB-D grid mapping and group leader decision making, uses a new utility function that takes into account each robot distance in the group from the unexplored set of targets, and allows to simultaneously explore the environment and to get a detailed grid map of specific areas in an optimized manner. Compared to state-of-the-art approaches, the main novelty is to exchange only the frontier points of the computed local grid map to reduce the shared data volume, and consequently the memory consumption. Moreover, communications constraints are taken into account within a SLAM-based multi-robot collective exploration. In that way, the proposed strategy is also designed to cope with communications drop-out or failures. The multi-UAV system is implemented into ROS and GAZEBO simulators on multiple computers provided with network facilities. Results show that the proposed cooperative exploration strategy minimizes

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