Abstract
This paper discusses efficiency and completeness of a sweeping task to ensure the reliability of sweeping robots. Commercial cleaning robots generally adopt a behavior-based motion. The reliability of the robot is insufficient because the robot can't detect an unswept area. This is caused by no information about a working environment and a robot's self-position. To develop realistic and high-performance sweeping robots, this study takes an approach that improves the behavior-based motion by estimating the swept area and the shape of walls in the working environment. Reliable short-range RFID tags are used to estimate the swept area and the shape of walls. The paper proposes a trajectory estimation method and a mapping method using Extended Kalman Filter, fixed-interval smoothing, and occupancy grid mapping in the environment with the tags. The methods construct a map of the swept area and the shape of walls incrementally. An efficient motion control method is proposed using the map. Experimental results confirm the effectiveness of the proposed method.
