Visual path following using a sequence of target images and smooth robot velocities for humanoid navigation

In this paper, we propose an approach of following a visual path for humanoid navigation. The problem consists in computing appropriate robot velocities for the humanoid walking task from the visual data shared between the current robot view and a set of target images. Two types of visual controllers are evaluated: a position-based scheme and an image-based scheme. Both of them rely on the estimation of the homography model even for non-planar scenes. We assume that the sequence of target images is given and we focus on the controllers performance. Because classical visual path following controllers generate discontinuous robot velocities, we propose a generic controller (applicable for different types of visual feedback) to alleviate this issue, which is a main contribution of the paper. The stability of such controller is addressed theoretically and verified through experiments with a NAO humanoid robot.