A novel method for estimating the heading angle for a home service robot using a forward-viewing mono-camera and motion sensors

This paper presents a novel method for estimating the heading angle of a home service robot. The images captured from a forward viewing mono-camera, gyroscope data, and wheel encoder data are used as sensory inputs. The data rates of camera, gyroscope, and encoder are 1 Hz, 50 Hz, and 50 Hz, respectively. The camera is slightly tilted by 16.5° to increase the amount of visual information obtained. The context of this study is simultaneous localization and mapping (SLAM) in an indoor home environment. The ceiling lines, i.e., the intersection between the ceiling and wall, are used as the only landmarks for the heading angle estimation. In our method, since the ceiling lines are used as the sole landmarks, line parameterization and data association problem can be simplified when compared to the general line based methods. In home environment, the ceiling line features can be easily detected regardless of the robot rotation. The developed method can be used to accurately estimate the global heading angle while the robot is in motion. A ceiling line map is also reconstructed. The reconstructed ceiling line map provides intuitively understandable spatial information about the environment using only a few features. The experimental results demonstrate that it is feasible to use the proposed method for an indoor home environment.