Autonomous cross-floor navigation of a stair-climbing mobile robot using wireless and vision sensor

This paper aims to present an autonomous cross-floor navigation system for stair-climbing mobile robot using wireless and vision sensors. Starting from the first floor to the fourth floor in the same building, the discussed map composed of stairways and indoor/outdoor corridors has five road sections. By using upward and forward looking camera setups, imaged based navigation is conducted in most road sections. Image features including ceiling landmarks, stair lines, and skirting lines are adopted to detect robot guiding lanes with appropriate image-processing algorithms. Particularly, wireless sensor modules are installed in the image dead zones so that the robot can adjust and continue its motion accordingly, achieving such long-distance navigation task. To let the robot follow the detected image lanes correctly, a visual servo control driven by image errors and based on car-like mobile robot differential kinematics is also applied for motion control. A self-made stair-climbing robot is finally used to validate the effectiveness of the proposed navigation method.