From Swarms to Stars: Task Coverage in Robot Swarms with Connectivity Constraints

Panerati, Jacopo; Gianoli, Luca G.; Pinciroli, Carlo; Shabah, Abdo; Nicolescu, Gabriela; Beltrame, Giovanni

doi:10.1109/icra.2018.8463193

Cited by 19 publications

(17 citation statements)

References 13 publications

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“…Most of the presented CPP approaches in literature implement model-based viewpoints generation algorithms such as [12,25,46,56,59]. The majority of these papers are generating grids consisting of cells, and are applied on 2D type of environment.…”

Section: Discussion and Future Research Directionsmentioning

confidence: 99%

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A survey on multi-robot coverage path planning for model reconstruction and mapping

Taha²,

et al. 2019

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There has been an increasing interest in researching, developing and deploying multi-robot systems. This has been driven mainly by: the maturity of the practical deployment of a single-robot system and its ability to solve some of the most challenging tasks. Coverage path planning (CPP) is one of the active research topics that could benefit greatly from multi-robot systems. In this paper, we surveyed the research topics related to multi-robot CPP for the purpose of mapping and model reconstructions. We classified the topics into: viewpoints generation approaches; coverage planning strategies; coordination and decision-making processes; communication mechanism and mapping approaches. This paper provides a detailed analysis and comparison of the recent research work in this area, and concludes with a critical analysis of the field, and future research perspectives.

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Section: Discussion and Future Research Directionsmentioning

confidence: 99%

“…Heuristic based algorithms combine randomness and heuristics to drive the exploration process as in [20,21,59]. A good ratio between performance and cost could be provided by these type of methods especially that they do not consume much computational resources and do not require expensive sensors.…”

Section: Discussion and Future Research Directionsmentioning

confidence: 99%

A survey on multi-robot coverage path planning for model reconstruction and mapping

Taha²,

et al. 2019

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“…Maintaining connectivity while executing spatially dis-tributed tasks is a recurrent requirement in mobile-robot systems. Panterati et al [28] present a swarm of robots that move in compact formation through a convex environment and stops at certain locations to visit multiple task locations simultaneously by building one chain of robots towards each task location. The order in which the tasks should be visited is determined by solving a mixed integer linear program (MILP).…”

Section: Sensing Robot Connectivitymentioning

confidence: 99%

Multi-Robot Persistent Surveillance With Connectivity Constraints

Scherer

Rinner

2020

IEEE Access

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Mobile robots, especially unmanned aerial vehicles (UAVs), are of increasing interest for surveillance and disaster response scenarios. We consider the problem of multi-robot persistent surveillance with connectivity constraints where robots have to visit sensing locations periodically and maintain a multihop connection to a base station. We formally define several problem instances closely related to multi-robot persistent surveillance with connectivity constraints, i.e., connectivity-constrained multirobot persistent surveillance (CMPS), connectivity-constrained multi-robot reachability (CMR), and connectivity-constrained multi-robot reachability with relay dropping (CMRD), and show that they are all NP-hard on general graph. We introduce three heuristics with different planning horizons for convex grid graphs and combine these with a tree traversal approach which can be applied to a partitioning of non-convex grid graphs (CMPS with tree traversal, CMPSTT). In simulation studies we show that a short horizon greedy approach, which requires parameters to be optimized beforehand, can outperform a full horizon approach, which requires a tour through all sensing locations, if the number of robots is larger than the minimum number of robots required to reach all sensing locations. The minimum number required is the number of robots necessary for building a chain to the farthest sensing location from the base station. Furthermore, we show that partitioning the area and applying the tree traversal approach can achieve a performance similar to the unpartitioned case up to a certain number of robots but requires less optimization time.

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“…Going from simulations to hardware, sensible performance degradation can occur-the so-called "reality gap" [37]. Hence, the importance of actual robotic implementations.…”

Section: Robotic Experimentsmentioning

confidence: 99%

Robust Area Coverage with Connectivity Maintenance

Siligardi

Panerati

Kaufmann

et al. 2019

2019 International Conference on Robotics and Automation (ICRA)

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Robot swarms herald the ability to solve complex tasks using a large collection of simple devices. However, engineering a robotic swarm is far from trivial, with a major hurdle being the definition of the control laws leading to the desired globally coordinated behavior. Communication is a key element for coordination and it is considered one of the current most important challenges for swarm robotics. In this paper, we study the problem of maintaining robust swarm connectivity while performing a coverage task based on the Voronoi tessellation of an area of interest. We implement our methodology in a team of eight Khepera IV robots. With the assumptions that robots have a limited sensing and communication range-and cannot rely on centralized processing-we propose a tri-objective control law that outperforms other simpler strategies (e.g. a potentialbased coverage) in terms of network connectivity, robustness to failure, and area coverage.

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From Swarms to Stars: Task Coverage in Robot Swarms with Connectivity Constraints

Cited by 19 publications

References 13 publications

A survey on multi-robot coverage path planning for model reconstruction and mapping

A survey on multi-robot coverage path planning for model reconstruction and mapping

Multi-Robot Persistent Surveillance With Connectivity Constraints

Robust Area Coverage with Connectivity Maintenance

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