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Award ID contains: 1646576

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  1. ; ; ; ; ; ; (, the Eighth Workshop on Micro Aerial Vehicle Networks, Systems, and Applications)
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  2. ; (, 2021 IEEE 46th Conference on Local Computer Networks (LCN))
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  3. ; (, 2021 IEEE International Conference on Smart Computing (SMARTCOMP))
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  4. ; ; ; (, IEEE Robotics and Automation Letters)
    null (Ed.)
    In many exploration scenarios, it is important for robots to efficiently explore new areas and constantly communicate results. Mobile robots inherently couple motion and network topology due to the effects of position on wireless propagation, e.g., distance or obstacles between network nodes. Information gain is a useful measure of exploration. However, finding paths that maximize information gain while preserving communication is challenging due to the non-Markovian nature of information gain, discontinuities in network topology, and zero-reward local optima. We address these challenges through an optimization and sampling-based algorithm. Our algorithm scales to 50% more robots and obtains 2-5 times more information relative to path cost compared to baseline planning approaches. 
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  5. ; (, IEEE International Conference on Mobile Ad-hoc Sensor Systems (MASS))
    null (Ed.)
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  6. ; ; ; ; ; (, IEEE International Conference on SMART Computing)
    null (Ed.)
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  7. ; ; ; (, 2020 IEEE International Conference on Human-Machine Systems (ICHMS))
    null (Ed.)
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  8. ; ; ; ; (, International Workshop on Mobile Ubiquitous Systems and Technologies (MUST), in conjunction with IEEE International Conference on Mobile Data Management (MDM), Hong Kong, China, June 10-13, 2019)
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  9. ; (, International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services (Mobiquitous), November 2019)
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  10. ; ; ; ; ; (, MobiQuitous '19: Proceedings of the 16th EAI International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services)
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