  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 novel method to encapsulate
cooperative robotic missions in an authenticated data structure known as 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 towards 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 operations 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 such as environmental monitoring, infrastructure surveillance, and
disaster management.
