Mathematical-Based Benchmarking: To Predict ANT Exploration Time-Series Dataset

Exploration robots are sent inside collapsed building in search of trapped victims. Once inside, they have to explore the entire maze of obstacles and debris as quickly as possible without missing any accessible area by means of the search algorithm. Comparing the performances of emerging search algorithms against known benchmarks, inside realistic simulated fields is crucial for fast victim localisation. In this paper we discuss how to apply the ridge regression in order to obtain the coefficient of relationship between the "ANT victim discovery time step" and the "search field complexity". This estimated coefficient allows us to predict the victim discovery time step of ANT exploration algorithm inside various generated search fields.