A footstep-plan-based floor sensing method using stereo images for biped robot control

In this paper, we propose a floor sensing method using stereo cameras mounted on a biped robot. In the proposed method, we first determine multiple regions of interest (ROI) in a reference image from footstep positions up to several steps, scheduled by a current footstep plan. Then the 3D plane parameters of the floor with respect to each ROI are estimated by a direct method using stereo images. We adopt the fast plane parameter estimation method, along with the compensation for the errors of the initial parameters by using the internal state of the robot, for the enhancement of the robustness and efficiency in the optimization process. Additionally, we estimate the shape of the floor including slopes from the set of the estimated plane parameters, and feedback the results for updating the footstep plan. The validity of the proposed method is demonstrated through on-line experiments using stereo cameras mounted on the body of a biped robot traversing a real environment.