Journal article
Distributed Attack-Robust Submodular Maximization for Multirobot Planning
IEEE transactions on robotics, v 38(5), pp 3097-3112
Oct 2022
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
In this article, we design algorithms to protect swarm-robotics applications against sensor denial-of-service attacks on robots. We focus on applications requiring the robots to jointly select actions, e.g., which trajectory to follow, among a set of available actions. Such applications are central in large-scale robotic applications, such as multirobot motion planning for target tracking. But the current attack-robust algorithms are centralized. In this article, we propose a general-purpose distributed algorithm toward robust optimization at scale, with local communications only. We name it distributed robust maximization ( DRM ). DRM proposes a divide-and-conquer approach that distributively partitions the problem among cliques of robots. Then, the cliques optimize in parallel, independently of each other. We prove DRM achieves a close-to-optimal performance. We demonstrate DRM 's performance in Gazebo and MATLAB simulations, in scenarios of active target tracking with swarms of robots . In the simulations, DRM achieves computational speed-ups, being 1 to 2 orders faster than the centralized algorithms. Yet , it nearly matches the tracking performance of the centralized counterparts. Since, DRM overestimates the number of attacks in each clique, in this article, we also introduce an improved distributed robust maximization ( IDRM ) algorithm. IDRM infers the number of attacks in each clique less conservatively than DRM by leveraging three-hop neighboring communications. We verify IDRM improves DRM 's performance in simulations.
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Details
- Title
- Distributed Attack-Robust Submodular Maximization for Multirobot Planning
- Creators
- Lifeng Zhou - University of PennsylvaniaVasileios Tzoumas - University of MichiganGeorge J. Pappas - University of PennsylvaniaPratap Tokekar - University of Maryland, College Park
- Publication Details
- IEEE transactions on robotics, v 38(5), pp 3097-3112
- Publisher
- IEEE
- Number of pages
- 16
- Grant note
- N000141812829 / Office of Naval Research (10.13039/100000006) ARL CRA DCIST 1943368 / National Science Foundation (10.13039/501100008982)
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Electrical and Computer Engineering
- Web of Science ID
- WOS:000788889000001
- Scopus ID
- 2-s2.0-85129408434
- Other Identifier
- 991021945758904721
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- Collaboration types
- Domestic collaboration
- Web of Science research areas
- Robotics