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Conference proceeding
Distributed Attack-Robust Submodular Maximization for Multi-Robot Planning
2020 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION (ICRA), pp 2479-2485
01 Jan 2020
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
We aim to guard swarm-robotics applications against denial-of-service (DoS) attacks that result in withdrawals of robots. We focus on applications requiring the selection of actions for each robot, among a set of available ones, e.g., which trajectory to follow. Such applications are central in large-scale robotic applications, e.g., multi-robot motion planning for target tracking. But the current attack-robust algorithms are centralized, and scale quadratically with the problem size (e.g., number of robots). In this paper, we propose a general-purpose distributed algorithm towards 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 K cliques of robots. The cliques optimize in parallel, independently of each other. That way, DRM also offers computational speed-ups up to 1/K-2 the running time of its centralized counterparts. K depends on the robots' communication range, which is given as input to DRM. DRM also achieves a close-to-optimal performance. We demonstrate DRM's performance in Gazebo and MATLAB simulations, in scenarios of active target tracking with multiple robots. We observe DRM achieves significant computational speed-ups (it is 3 to 4 orders faster) and, yet, nearly matches the tracking performance of its centralized counterparts.
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Details
- Title
- Distributed Attack-Robust Submodular Maximization for Multi-Robot Planning
- Creators
- Lifeng Zhou - Virginia TechVasileios Tzoumas - Massachusetts Institute of TechnologyGeorge J. Pappas - University of PennsylvaniaPratap Tokekar - Virginia Tech
- Publication Details
- 2020 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION (ICRA), pp 2479-2485
- Series
- IEEE International Conference on Robotics and Automation ICRA
- Publisher
- IEEE
- Number of pages
- 7
- Grant note
- 479615 / National Science Foundation; National Science Foundation (NSF) ARL CRA DCIST N000141812829 / U.S. Department of Defense (DOD); United States Department of Defense N000141812829 / Office of Naval Research; United States Department of Defense; United States Navy
- Resource Type
- Conference proceeding
- Language
- English
- Academic Unit
- Electrical and Computer Engineering
- Web of Science ID
- WOS:000712319501122
- Scopus ID
- 2-s2.0-85092710234
- Other Identifier
- 991021945874904721
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InCites Highlights
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- Collaboration types
- Domestic collaboration
- Web of Science research areas
- Automation & Control Systems
- Engineering, Electrical & Electronic
- Robotics