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We consider the problem of bearing-based visual homing: Given a mobile robotwhich can measure bearing directions with respect to known landmarks, the goalis to guide the robot toward a desired "home" location. We propose a controllaw based on the gradient field of a Lyapunov function, and give sufficientconditions for global convergence. We show that the well-known Average LandmarkVector method (for which no convergence proof was known) can be obtained as aparticular case of our framework. We then derive a sliding mode control law fora unicycle model which follows this gradient field. Both controllers do notdepend on range information. Finally, we also show how our framework can beused to characterize the sensitivity of a home location with respect to noisein the specified bearings. This is an extended version of the conference paper[1].

Technical report on Optimization-Based Bearing-Only Visual Homing with Applications to a 2-D Unicycle Model