Modified E3 exploration algorithm for unknown environments with obstacles
Ilya Mavrin, Tatyana Tsoy, Evgeni Magid · 2022 13th Asian Control Conference (ASCC) · 2022
An efficient autonomous exploration of an unknown environment is an important task for mobile robots, which is required in many domains. This paper considers three existing exploration approaches: frontier exploration algorithm (FEA), greedy algorithm (GrA) and Ergodic Environmental Exploration algorithm (E3). While original E3deals only with empty environments, we propose a new modified version of E3(ME3A) that allows to explore environments with obstacles. FEA, GrA and ME3A were implemented in Robot Operating System and their performance was evaluated in Gazebo simulator within 18 different environments. We employed a total travelled distance and a percentage of explored environment as a comparison criteria.