Abstract
Human intelligence plays a critical role in the operation of a multi-agent system. In order to explore, identify, and cover an environment, a human operator can collaborate with a robot thanks to the methods for operating swarm robots proposed in this research. Then, using an interactive control framework and control algorithms defined for an abstract task function, a human operator can control the movement of a swarm robot inside a working environment. In order for the human operator to comprehend the coverage control state of the swarm robot, environmental data is sent to the master devices. Input-to-state stability with static coverage control and stability and location tracking with dynamic coverage control are investigated for the human swarm system. The efficacy and efficiency of the suggested system are verified through experiments and numerical examples.
Published Version
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