Evaluation method of airport pavement partition coverage detection based on human-robot interaction

The coverage detection of airport pavement is the premise to ensure civil aviation safety. Due to the hard requirements of ultra-high security of the airport itself, the application of robots to unmanned coverage detection in the airport is not accomplished overnight, but a process of step-by-step and continuous technical iteration. Therefore, for different application stages of the robot in the airport, an appropriate method should be given to guide airport maintenance engineers to flexibly adjust the partition coverage operation mode. In this paper, we design an evaluation index named Partition Quality Function (PQF) to evaluate the quality of partition coverage. In PQF, the degree suitable for human-robot interaction, the efficiency of coverage planning and the coverage failure area are taken into account. And the proportion of factors can be adjusted through the weight coefficient. Then, in order to facilitate engineering application, we design six kinds of rectangular partition templates and use genetic algorithm to optimize PQF. Finally, through simulation research, we discover PQF partition law under different weight coefficients, and gave the PQF setting of the robot in different application stages of the airport. It is an important step to promote the actual landing of robot coverage detection technology in the airport.