Adaptive strategy for environment exploration in search and rescue missions by autonomous robot

Abstract

In this research, a new adaptive strategy is proposed for the autonomous mobile robot, which explores the unknown search and rescue (SAR) environment. The robot, which implements the proposed strategy, operates on the frontier-based exploration approach and makes a decision of where to move next by applying a total of eight new strategies for candidate frontier assessment. The fuzzy logic controller is applied to determine the most suitable candidate frontier assessment strategy regarding the current robot state and the discovered environment information. The final decision of where to move next is made by the neutrosophic interval-valued multi-criteria decision-making method, namely WASPAS-IVNS, which enables the modelling of vagueness present in the initial sensor data. The proposed adaptive strategy is tested in the virtual Gazebo simulation. The obtained test results show the increased efficiency when comparing the proposed adaptive environment exploration strategy to the static environment exploration strategies and the standard greedy environment exploration approach.