Research On Autonomous Control Level Adjustment For Unmanned Surface Vehicle

In the1990s, with the application of the Global Positioning System, a longer-distancewireless data transmission system with a higher-bandwidth has been invested, also thecomputer and electronic technology has developed rapidly, based on which a more complexUnmanned Surface Vehicle (USV) system has been developed and tested. As theautonomous control capacity of the Unmanned Surface Vehicle grows, it has become morepopular and people’s high demand leads to a more complex working environment, whichresults in a challenge to the intelligent system of USV as well as a problem to be solved. Theadjustable autonomous control method as a combination of humans’ and machines’intelligence is an effective way to improve the intelligence of the autonomous control system,which appeals attention from more and more scholars.This paper presents a two-dimensional classification method of an adjustable autonomycontrol level, which is applied to the USV system. The assessment method of autonomouscontrol level is achieved for USV while performing an obstacle avoid mission in unknownmarine environment. An index system is established for the autonomous control levelassessment of USV, which includes the performance of USV, environmental complexity anduser status. And a multi-attribute decision-making method is presented, which can choosedecision indicators and build the hierarchy based on the Analytic Hierarchy Process, calculatethe weight of the decision indicators based on the Probability Ranking Input Matrix method,an optimal selection method of decision scheme is presented according to the TOPSIS methodwhich is called AHP-PRIM-TOPSIS Decision-making method, short for APTDecision-making method. This multi-attribute decision-making method can be used for theautonomous control level assessment of USV. This paper also presents an index system forthe efficiency rating of the obstacle avoid mission of USV, which is used to evaluate theperformance of USV.The autonomous control level assessment method is realized by Visual C++6.0. And thesimulation platform of USV is designed by Visual C++6.0and Firemonkey. The autonomouscontrol level assessment method of USV is simulated in the simulation platform, which cancertify that adjustable autonomy can improve the performance of USV.