A Centralized Task Allocation Algorithm for a Multi-Robot Inspection Mission With Sensing Specifications

A Centralized Task Allocation Algorithm for a Multi-Robot Inspection Mission With Sensing Specifications

Blog Article

Recently, considerable attention has focused on enhancing the security and safety of industries with high-risk level activities in order to protect the equipment and environment.In particular, chemical processes and nuclear power generation may have a deep impact on their surroundings.In the case of major events, such as chemical spills, oil rig explosions, or nuclear accidents, collecting accurate and rapidly evolving data becomes a challenging task.

So, coordinating a fleet of autonomous mobile robots is blade paste a very promising way to deal with unpredicted events and also prevent malicious actions.This paper addresses the problem of assigning optimally a set of tasks to a set of mobile robots equipped with different sensors to minimize a global objective function.The robots perform sensing tasks in order to monitor the area and to facilitate firefighters and inspectors Hair Care work if a disaster occurs by providing the necessary measures.

For this purpose, a centralized Genetic Algorithm (GA) is proposed to determine the task each robot will perform and the order of execution.The proposed approach is tested through a simulation scenario of a grid map environment that represents an industrial area of the city of Le Havre, France.Moreover, a comparative study is conducted with the Hybrid Filtered Beam Search (HFBS) approach and the Mixed-Integer Linear Programming (MILP) solver Cplex.

The results demonstrate that the GA approach offers a favorable balance between optimality and execution time.