Autonomous Exploration Based on Multi-Criteria Decision-Making and Using D* Lite Algorithm

An autonomous robot is often in a situation to perform tasks or missions an initially unknown environment. A logical approach doing this implies discovering the environment by incremental principle defined applied exploration strategy. large number of strategies apply technique selecting next position between candidate locations on frontier and known parts using function that combines different criteria. The based Multi-Criteria Decision-Making (MCDM) standard SAW, COPRAS TOPSIS methods are presented paper. Their performances evaluated terms analysis comparison influence each one them has efficiency environments with risk level “bad choice” selection position. simulation results show that, due its characteristics related intention minimize risk, application can provide good strategy high considered risk. No significant difference found analyzed MCDM low Also, confirm MCDM-based achieve better than when only criterion used, regardless famous D* Lite algorithm used for path planning.