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Secure and secret cooperation in robot swarms
Science Robotics ( IF 25.0 ) Pub Date : 2021-07-28 , DOI: 10.1126/scirobotics.abf1538
Eduardo Castelló Ferrer 1, 2, 3 , Thomas Hardjono 2 , Alex Pentland 1, 2 , Marco Dorigo 3
Affiliation  

The importance of swarm robotics systems in both academic research and real-world applications is steadily increasing. However, to reach widespread adoption, new models that ensure the secure cooperation of large groups of robots need to be developed. This work introduces a method to encapsulate cooperative robotic missions in an authenticated data structure known as a Merkle tree. With this method, operators can provide the “blueprint” of the swarm’s mission without disclosing its raw data. In other words, data verification can be separated from data itself. We propose a system where robots in a swarm, to cooperate toward mission completion, have to “prove” their integrity to their peers by exchanging cryptographic proofs. We show the implications of this approach for two different swarm robotics missions: foraging and maze formation. In both missions, swarm robots were able to cooperate and carry out sequential tasks without having explicit knowledge about the mission’s high-level objectives. The results presented in this work demonstrate the feasibility of using Merkle trees as a cooperation mechanism for swarm robotics systems in both simulation and real-robot experiments, which has implications for future decentralized robotics applications where security plays a crucial role.



中文翻译:

机器人群中的安全和秘密合作

群体机器人系统在学术研究和实际应用中的重要性正在稳步增加。然而,为了得到广泛采用,需要开发确保大型机器人群体安全合作的新模型。这项工作介绍了一种将协作机器人任务封装在称为 Merkle 树的经过验证的数据结构中的方法。通过这种方法,操作员可以提供群体任务的“蓝图”,而无需透露其原始数据。换句话说,数据验证可以与数据本身分离。我们提出了一个系统,其中一群机器人为了完成任务而合作,必须通过交换加密证明来向同行“证明”他们的完整性。我们展示了这种方法对两种不同的群体机器人任务的影响:觅食和迷宫形成。在这两个任务中,群机器人能够合作并执行连续任务,而无需明确了解任务的高级目标。这项工作中提出的结果证明了在模拟和真实机器人实验中使用 Merkle 树作为群机器人系统协作机制的可行性,这对未来的分散机器人应用具有重要意义,其中安全性起着至关重要的作用。

更新日期:2021-07-30
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