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A Fast and Robust Solution for Common Knowledge Formation in Decentralized Swarm Robots

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Abstract

Common knowledge, that is, a common understanding of environmental conditions, task objectives, coordination rules, etc., can greatly improve the collaborative efficiency of swarm robots. In many complex task scenarios, it is impossible to assume there is a central facility (e.g., a powerful robot or a back-end server that can communicate effectively with everyone) responsible for maintaining the collective’s common knowledge. Instead, we must maintain it in a decentralized way. Blockchain has been proved to be an effective means of meeting this demand. It can even tolerate malicious or malfunctioning individuals to a certain extent, which is an important capability for swarm robots to operate in an open or hostile environment. However, current widely-accepted Blockchain techniques, such as Ethereum, use the proof-of-work mechanism as the basis of reaching consensus, which has to consume huge computing resources and is not suitable for swarm robots. In this paper, we present a fast and robust solution for maintaining common knowledge in swarm robots based on Hashgraph, a lightweight consensus technology being originally proposed for fully-connected, well-conditioned networks. We successfully improve its kernel mechanisms to adapt it to swarm robots with limited communication capabilities. And we novelly introduce the concept of Ranger Robot, a special kind of robot that can significantly accelerate the formation of consensus in sparsely-distributed or physically-partitioned robot swarms. Furthermore, we design a knowledge validation algorithm to enable the robot swarm to recognize attacks from a special kind of malicious robot called Byzantine robots. The results of a set of experiments based on both simulated and real robots show that our solution can greatly reduce computing overhead and accelerate the formation of consensus in comparison with solutions based on the original Hashgraph.

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Code or Data Availability

The code is available on GitHub https://github.com/luoxiaojie9527/swarm-hashgraph.

Types of papers

Category(1),(2),(3)

Classification code

68-04

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Funding

This work is partially supported by the major Science and Technology Innovation 2030 “New Generation Artificial Intelligence” project 2020AAA0104803 and Scientific Research Plan of National University of Defense Technology under Grant No.ZK-20-38.

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Authors and Affiliations

  1. National Laboratory for Parallel and Distributed Processing, National University of Defense Technology, Changsha, 410000, Hu’nan, China

    Jie Luo, Xiao Shu, Yuanzhao Zhai, Xiang Fu & Bo Ding

  2. School of Computing, University of Leeds, Leeds, LS29JT, West Yorkshire, UK

    Jie Xu

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  1. Jie Luo
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  2. Xiao Shu
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  3. Yuanzhao Zhai
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  4. Xiang Fu
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  5. Bo Ding
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Contributions

All authors contributed to the study’s conception and design. Material preparation, data collection, and analysis were performed by Jie Luo. The first draft of the manuscript was written by Jie Luo and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.

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Correspondence to Bo Ding.

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Luo, J., Shu, X., Zhai, Y. et al. A Fast and Robust Solution for Common Knowledge Formation in Decentralized Swarm Robots. J Intell Robot Syst 106, 68 (2022). https://doi.org/10.1007/s10846-022-01759-1

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