B-Theta*: an Efficient Online Coverage Algorithm for Autonomous Cleaning Robots

We propose a novel approach to deal with the online complete-coverage task of cleaning robots in unknown workspaces with arbitrarily-shaped obstacles. Our approach is based on the boustrophedon motions, the boundary-following motions, and the Theta* algorithm known as B-Theta*. Under control of B-Theta*, the robot performs a single boustrophedon motion to cover an unvisited region. While performing the boustrophedon motion, if the robot encounters an obstacle with a boundary that has not yet been covered, it switches to the boundary mode to cover portions along the obstacle boundary, and then continues the boustrophedon motion until it detects an ending point. To move to an unvisited region, the robot detects backtracking points based on its accumulated knowledge, and applies an intelligent backtracking mechanism thanks to the proposed Theta* for multi-goals in order to reach the next starting point. Complete coverage is achieved when no starting point exists for a new boustrophedon motion. Computer simulations and experiments on real workspaces show that our proposed B-Theta* is efficient for the complete-coverage task of cleaning robots.