Insect-Inspired Robot Coordination: Foraging and Coverage

Alers, Sjriek; Tuyls, Karl; Ranjbar-Sahraei, Bijan; Claes, D. R.; Weiß, Gerhard

doi:10.7551/978-0-262-32621-6-ch123

Cited by 13 publications

(5 citation statements)

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“…MRS has greatly promoted many applications, such as search and rescue [19], [20], foraging and coverage [21], [22], flocking and formation [23], [24], and cooperative object transport [10]. Darmanin et al [1] give a brief MRS survey focusing on the MRS application domain.…”

Section: Mrs Representative Applicationmentioning

confidence: 99%

Multi-Robot Systems and Cooperative Object Transport: Communications, Platforms, and Challenges

Lin

et al. 2023

IEEE Open J. Comput. Soc.

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Multi-robot systems gain considerable attention due to lower cost, better robustness, and higher scalability as compared with single-robot systems. Cooperative object transport, as a well-known use case of multi-robot systems, shows great potential in real-world applications. The design and implementation of a multi-robot system involve many technologies, specifically, communication, coordination, task allocation methods, experimental platforms, and simulators. However, most of recent multi-robot system studies focus on coordination and task allocation problems, with little focus on communications among multiple robots. In this review, we focus on the communication, validation platform, and simulator of multi-robot systems, and discuss one of the important applications, cooperative object transport. First, we study the multi-robot system fundamentals and comprehensively review the multi-robot system communication technologies. Then, the multi-robot system validating platform, testbed, simulator, and middleware used in academia and industry are investigated. Finally, we discuss recent advances in cooperative object transport, and challenges and possible future research directions for multi-robot systems.

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Section: Mrs Representative Applicationmentioning

confidence: 99%

Multi-Robot Systems and Cooperative Object Transport: Communications, Platforms, and Challenges

Lin

et al. 2023

IEEE Open J. Comput. Soc.

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“…This exploration topic has been also well investigated in swarm robotics and can be used with extended resources [19] to do tasks such as foraging, discovering and coverage. In this context, different methods are used.…”

Section: Related Workmentioning

confidence: 99%

Cooperative exploration strategy for micro-aerial vehicles fleet

Mahdoui¹,

Frémont²,

Natalizio³

2017

2017 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI)

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In this paper, the problem of the exploration of an unknown environment by deploying a fleet of Micro-Aerial Vehicles (MAV) is considered. As a single robot has already proven its efficiency for this task, the challenge is to extend it to a multi-robots system to reduce the exploration time. For this purpose, a cooperative navigation strategy is proposed based on a specific utility function and inter-robots data exchange. The novelty comes from the exchange of the frontiers points instead of maps, which allows to reduce computation and data amount within the network. The proposed system has been implemented and tested under ROS using the Gazebo simulator. The results demonstrate that the proposed navigation strategy efficiently spreads robots over the environment for a faster exploration.

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“…At present, the mainstream design of microrobots only retains perception and motion modules, and wirelessly obtains instructions from a central server and executes them. Alers et al [2] introduced two different types of robots, and for resource-constrained robots, he used the electronic punk platform as an example. Although it only has a few hardware and micro cameras, it is very suitable for the research field of swarm intelligence.…”

Section: Introductionmentioning

confidence: 99%

Development and Review of Group Rescue Robots Based on Artificial Intelligence Technology

2024

AETR

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Rescue robots can perform rescue missions in dangerous and complex environments, protect humans from harm, and improve the efficiency and effectiveness of rescue, thus playing an increasingly important role in disaster management and rescue. This article reviews the technologies and methods required to apply artificial intelligence to rescue robot teams. Firstly, the feasibility of motion control for swarm robots was explored from the perspective of biomimetic robots. Through the analysis of animal biomimetics and the comparison of commonly used topological structures, the nature of team rescue robot rescue is emphasized, and based on this, a scheme for optimizing topological networks by combining environmental intelligence is proposed. Secondly, several existing micro robots were introduced and their data loading capabilities were evaluated. On this basis, the process of robot vision and motion commands was outlined. At the meanwhile, researchers focus on the current mainstream robot motion trajectory algorithms, and study the algorithm optimization process from extending the motion path planning of a single robot to group coordinated motion. This includes traditional cell decomposition algorithms and algorithms combined with machine learning to improve path planning efficiency. Finally, the above methods were summarized, and the impact of other possible feasible methods in the field of artificial intelligence was explored and analyzed.

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Insect-Inspired Robot Coordination: Foraging and Coverage

Cited by 13 publications

References 0 publications

Multi-Robot Systems and Cooperative Object Transport: Communications, Platforms, and Challenges

Multi-Robot Systems and Cooperative Object Transport: Communications, Platforms, and Challenges

Cooperative exploration strategy for micro-aerial vehicles fleet

Development and Review of Group Rescue Robots Based on Artificial Intelligence Technology

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