Technical report on Optimization-Based Bearing-Only Visual Homing with Applications to a 2-D Unicycle Model
Abstract
We consider the problem of bearing-based visual homing: Given a mobile robot which can measure bearing directions with respect to known landmarks, the goal is to guide the robot toward a desired "home" location. We propose a control law based on the gradient field of a Lyapunov function, and give sufficient conditions for global convergence. We show that the well-known Average Landmark Vector method (for which no convergence proof was known) can be obtained as a particular case of our framework. We then derive a sliding mode control law for a unicycle model which follows this gradient field. Both controllers do not depend on range information. Finally, we also show how our framework can be used to characterize the sensitivity of a home location with respect to noise in the specified bearings. This is an extended version of the conference paper [1].
Cite
@article{arxiv.1402.3584,
title = {Technical report on Optimization-Based Bearing-Only Visual Homing with Applications to a 2-D Unicycle Model},
author = {Roberto Tron and Kostas Daniilidis},
journal= {arXiv preprint arXiv:1402.3584},
year = {2014}
}
Comments
This is an extender version of R. Tron and K. Daniilidis, "An optimization approach to bearing-only visual homing with applications to a 2-D unicycle model," in IEEE International Conference on Robotics and Automation, 2014, containing additional proofs