Vision guided navigation for a nonholonomic mobile robot

Abstract

Visual servoing, i.e. the use of the vision sensor in feedback control, has been of increasing interest. Work has been done by applications in autonomous driving, manipulation, mobile robot navigation and surveillance. This paper studies the navigation task for a nonholonomic ground mobile base tracking an arbitrarily shaped ground curve using vision sensors. This tracking problem is formulated as one of controlling the shape of the curve in the image plane. The study of the controllability of the system characterizing the image curve dynamics shows that the shape of the image curve is controllable only up to its `linear' curvature parameters. A stabilizing control law is presented for tracking (piecewise) analytic curves, and we propose to track arbitrary curves by approximating them by piecewise linear curvature curves. Simulation results are given for these control schemes. The observability of the image curve dynamics using direct measurements from vision sensors as the outputs is studied and an extended Kalman filter is proposed to dynamically estimate the image parameters needed for the feedback control from the actual noisy image sequences.