Decentralized multi-agent robotic systems have many advantages over centralized ones. Such systems make it possible to distribute computational and communication operations between all its elements, and are also more resistant to the loss of individual elements of a swarm, but they complicate the implementation of complex high-level tasks. An example of such a problem is the selection of one of the possible alternatives, in which the swarm must choose the most favorable solution from a list of possible alternatives. This paper proposes an algorithm for reaching a consensus for robotic swarms deployed in scenarios in which they can choose one of the two most common signs in the external environment. The proposed algorithm is based on the calculation of the measured features of the environment, as well as the distribution of this data between robots. The algorithm was tested using the ARGoS simulator.
The active introduction of robotics swarm systems into life brings the issues of their information security up to date. Known security approaches often do not take into account the peculiarities of the implementation of swarm systems, such as collective design-making, and only consider the presence of Byzantine robots with a strategy of behavior consisting in voting against a majority when a consensus is reached. The aim of this work is to increase the security of the collective design-making process in a swarm robotics system from the imposition of false and ineffective alternatives by Byzantine robots with a random behavior strategy. It is proposed to use an approach based on the use of a distributed ledger and analysis of deviations in the process of collective design-making, which will allow identifying and isolating harmful effects. The solution to the problem of detecting Byzantine robots is based on the application of the criterion of the degree of confidence of a robot in choosing an alternative when a consensus is reached by the swarm system and is based on the assumption that the distribution of the degree of confidence of a Byzantine robot due to ignoring the parameters of the external environment and voting for random alternatives is significantly different from the behavior an ordinary robot. The elements of novelty of the presented solution include the use of the degree of confidence criterion to ensure the safety of collective design-making and the ability to take into account various strategies of behavior of Byzantine robots. The use of the presented solution makes it possible to increase the efficiency of reaching consensus by a swarm robotics system in the presence of Byzantine robots. The simulation for a swarm of 20 robots, including 5 Byzantine ones with random behavior, showed an increase in the probability of correctly reaching a consensus by 12.5%. The practical significance of the presented solutions lies in the possibility of ensuring the stability of reaching consensus by a swarm robotics system in the presence of robots with harmful behavior.
The technological development and popularity of swarm robotics actualizes the issues of increasing the efficiency and safety of consensus achievement between the swarm elements. Currently, most studies have little or no regard for information security issues when consensus achievement among swarm elements in the presence of robots with arbitrarily malfunctioning or malicious behavior. However, in many practical applications, when exploring the external environment, a swarm of one or more malicious robots may be sufficient to allow the current consensus mechanisms to fail. One of the promising ways to ensure information security in collective decision-making is the use of blockchain technology as a distributed system designed to work in conditions of lack of trust between the parties. The use of distributed ledger technologies, due to their complexity, leads to reducing efficiency in consensus achievement. The aim of the work is to improve the safety of the process of consensus achievement in swarms of robots through the use of blockchain technology in collective design making while maintaining the effectiveness of consensus achievement between robots. Increasing the safety of decision-making by a swarm will increase the stability and the possibilities of practical application of swarm robotic systems for solving problems in aggressive environments.
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