Research on strategy of intelligent disinfection robot based on distributed constraint optimization

Abstract

In the current serious COVID-19 epidemic environment, disinfection is a laborious and extremely risky task. To improve the disinfection efficiency and reduce the disinfection risky, in this paper, the intelligent robot collaborative disinfection problem is constructed as a Distributed constrained optimization problem, in which each intelligent disinfection robot is modeled as an Agent and the constraint graph is constructed based on the actual application scenario to optimize the comprehensive benefits of energy consumption and machine wear of disinfection robots in the collaborative working process. The Proposed Distributed constrained optimization problem model is solved by the state-of-the-art algorithms DSA, MGM, Max-Sum and RM. Based on our extensive empirical evaluations, we experimentally show that the constructed Distributed constrained optimization problem model for intelligent robot collaborative disinfection can effectively plan the optimal collaborative robot patterns for identified disinfection scenarios as well as recommend the optimum parameters for each disinfection robot.