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RSS FeedsRemote Sensing, Vol. 13, Pages 4135: Immunized Token-Based Approach for Autonomous Deployment of Multiple Mobile Robots in Burnt Area (Remote Sensing)

 
 

15 october 2021 14:11:41

 
Remote Sensing, Vol. 13, Pages 4135: Immunized Token-Based Approach for Autonomous Deployment of Multiple Mobile Robots in Burnt Area (Remote Sensing)
 


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.


 
61 viewsCategory: Geology, Physics
 
Remote Sensing, Vol. 13, Pages 4138: Source Model and Simulated Strong Ground Motion of the 2021 Yangbi, China Shallow Earthquake Constrained by InSAR Observations (Remote Sensing)
Remote Sensing, Vol. 13, Pages 4140: Fusing Retrievals of High Resolution Aerosol Optical Depth from Landsat-8 and Sentinel-2 Observations over Urban Areas (Remote Sensing)
 
 
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