Journal article
Distributed Resilient Submodular Action Selection in Adversarial Environments
IEEE robotics and automation letters, v 6(3), pp 5832-5839
01 Jul 2021
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
In this letter, we consider a distributed submodular maximization problem for multi-robot systems when attacked by adversaries. One of the major challenges for multi-robot systems is to increase resilience against failures or attacks. This is particularly important for distributed systems under attack as there is no central point of command that can detect, mitigate, and recover from attacks. Instead, a distributed multi-robot system must coordinate effectively to overcome adversarial attacks. In this work, our distributed submodular action selection problem models a broad set of scenarios where each robot in a multi-robot system has multiple action selections that may fulfill a global objective, such as exploration or target tracking. To increase resilience in this context, we propose a fully distributed algorithm to guide each robot's action selection when the system is attacked. The proposed algorithm guarantees performance in a worst-case scenario where up to a portion of the robots malfunction due to attacks. Importantly, the proposed algorithm is also consistent, as it is shown to converge to the same solution as a centralized method. Finally, a distributed resilient multi-robot exploration problem is presented to confirm the performance of the proposed algorithm.
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Details
- Title
- Distributed Resilient Submodular Action Selection in Adversarial Environments
- Creators
- Jun Liu - Virginia TechLifeng Zhou - University of PennsylvaniaPratap Tokekar - University of Maryland, College ParkRyan Williams - Virginia Tech
- Publication Details
- IEEE robotics and automation letters, v 6(3), pp 5832-5839
- Publisher
- IEEE
- Number of pages
- 8
- Grant note
- National Institute of Food and Agriculture (10.13039/100005825) 2018-67007-28380 N00014-18-1-2829 / Office of Naval Research (10.13039/100000006) National Science Foundation (10.13039/100006435)
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Electrical and Computer Engineering
- Web of Science ID
- WOS:000663515000003
- Scopus ID
- 2-s2.0-85105856342
- Other Identifier
- 991021945881904721
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InCites Highlights
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- Collaboration types
- Domestic collaboration
- Web of Science research areas
- Robotics