Data from: Secure and secret cooperation in robot swarms

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 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 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. This dataset includes
all experimental data generated for this paper.