Forecast-Island and Bidding A*-Euclidean Selecting Boustrophedon Coordination Algorithm for Exploration

Abstract

Exploration algorithms based on the Boustrophedon path seldom consider the impacts of a robot turning at corners on the exploration time. This paper proposes the Forecast-Island and Bidding A*-Euclidean Selecting Boustrophedon Coordination (FIBA*ESBC) algorithm to calculate the turning time at corners in the overall exploration time and introduces a method to estimate the walking time in the Boustrophedon paths in order to determine the directions for path execution. Typically, in bidding-based exploration tasks, the cost is the Euclidean distance between the current position of the robot and the target point. When there is an obstacle between two points, the cost is set to infinity. Therefore, the selected target point is sometimes not optimal. The FIBA*ESBC algorithm is based on the exploration cost of a combination of the Euclidean distance and A* algorithm walking path, which can effectively solve this problem. Because the bidding is based on a greedy algorithm, the robot has a small unexplored island in the later exploration stage; therefore, full exploration is not possible or requires a long time with several repeated paths. The FIBA*ESBC algorithm prioritizes the exploration and estimation of hidden and existing unexplored islands. It can realize complete exploration and decrease the exploration time. Through simulation experiments conducted using Gazebo and RViz, the feasibility of the FIBA*ESBC algorithm is verified. Moreover, a simulation experiment is conducted in MATLAB for comparison with other algorithms. The analysis of the experimental data shows that the proposed algorithm has a relatively short exploration time.