Biologically inspired swarm robotic network ensuring coverage and connectivity

Mathews, Emi; Graf, Tobias; Kulathunga, Kosala S. S. B.

doi:10.1109/icsmc.2012.6377681

Cited by 17 publications

(12 citation statements)

References 12 publications

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“…This is because of their limited local observation. In a swarm-inspired algorithm for deployment, for example, obviously the utility can be significantly improved by the location changes of the boundary robots, but in existing approaches such as [14], the boundary robots and inner robots are based on the same rules to move. After several periods of the location adjustment, some inner robots' locations remain approximately unchanged, but they have consumed some resources trembling between the original location.…”

Section: Related Workmentioning

confidence: 99%

“…During the deployment, robots already have knowledge about the pre-calculated locations they should go to. For other approaches, such as the virtual-force [14] based algorithm, the capability of gaining real-time information and knowledge is assumed, therefore the AMR team can interact with low network latency and perform actions in a synchronized way. However, those assumptions are sometimes infeasible in unexplored areas.…”

Section: Introductionmentioning

confidence: 99%

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Immunized Token-Based Approach for Autonomous Deployment of Multiple Mobile Robots in Burnt Area

et al. 2021

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Collaborative exploration, sensing and communication in previously unknown environments with high network latency, such as outer space, battlefields and disaster hit areas are promising in multi-agent applications. When disasters such as large fires or natural disasters occur, previously established networks might be destroyed or incapacitated. In these cases, multiple autonomous mobile robots (AMR) or autonomous unmanned ground vehicles carrying wireless devices and/or thermal sensors can be deployed to create an end-to-end communication and sensing coverage to support rescue efforts or access the severity of damage. However, a fundamental problem is how to rapidly deploy these mobile agents in such complex and dynamic environments. The uncertainties introduced by the operational environment and wide range of scheduling problem have made solving them as a whole challenging. In this paper, we present an efficient decentralized approach for practical mobile agents deployment in unknown, burnt or disaster hit areas. Specifically, we propose an approach that combines methods from Artificial Immune System (AIS) with special token messages passing for a team of interconnected AMR to decide who, when and how to act during deployment process. A distributed scheme is adopted, where each AMR makes its movement decisions based on its local observation and a special token it receives from its neighbors. Empirical evidence of robustness and effectiveness of the proposed approach is demonstrated through simulation.

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Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Immunized Token-Based Approach for Autonomous Deployment of Multiple Mobile Robots in Burnt Area

et al. 2021

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“…Few studies take a swarm robotics approach to coverage and mapping. In [15], the coverage problem is tackled through a flocking algorithm ensuring permanent connectivity among robots. Similarly in [16], multi-robot coverage is performed to maximise spread while maintaining connectivity among robots and reducing the communication overhead.…”

Section: Institute Of Cognitive Sciences and Technologies (Istc) Nati...mentioning

confidence: 99%

Field coverage and weed mapping by UAV swarms

Albani

Nardi

Trianni

2017

2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

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The demands from precision agriculture (PA) for high-quality information at the individual plant level require to re-think the approaches exploited to date for remote sensing as performed by unmanned aerial vehicles (UAVs). A swarm of collaborating UAVs may prove more efficient and economically viable compared to other solutions. To identify the merits and limitations of a swarm intelligence approach to remote sensing, we propose here a decentralised multi-agent system for a field coverage and weed mapping problem, which is efficient, intrinsically robust and scalable to different group sizes. The proposed solution is based on a reinforced random walk with inhibition of return, where the information available from other agents (UAVs) is exploited to bias the individual motion pattern. Experiments are performed to demonstrate the efficiency and scalability of the proposed approach under a variety of experimental conditions, accounting also for limited communication range and different routing protocols.

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“…For the surveillance task, multi-robot coverage was specified in [5], where the problem of positioning a team of mobile robots was solved with GPS. Approaches of biologically inspired swarm coverage can be found in [6], [7].…”

Section: Introductionmentioning

confidence: 99%

Autonomous deployment of swarms of micro-aerial vehicles in cooperative surveillance

Saska

Chudoba

Precil

et al. 2014

2014 International Conference on Unmanned Aircraft Systems (ICUAS)

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An algorithm for autonomous deployment of groups of Micro Aerial Vehicles (MAVs) in the cooperative surveillance task is presented in this paper. The algorithm enables to find a proper distributions of all MAVs in surveillance locations together with feasible and collision free trajectories from their initial position. The solution of the MAV-group deployment satisfies motion constraints of MAVs, environment constraints (non-fly zones) and constraints imposed by a visual onboard relative localization. The onboard relative localization, which is used for stabilization of the group flying in a compact formation, acts as an enabling technique for utilization of MAVs in situations where an external local system is not available or lacks the sufficient precision.

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Biologically inspired swarm robotic network ensuring coverage and connectivity

Cited by 17 publications

References 12 publications

Immunized Token-Based Approach for Autonomous Deployment of Multiple Mobile Robots in Burnt Area

Immunized Token-Based Approach for Autonomous Deployment of Multiple Mobile Robots in Burnt Area

Field coverage and weed mapping by UAV swarms

Autonomous deployment of swarms of micro-aerial vehicles in cooperative surveillance

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