Particle filter-based direct visual servoing
With respect to classical visual servoing (VS) technics based on geometrical features, the main drawback of direct visual servoing is its limited convergence area. In this paper we propose a new direct visual servoing control law that relies on a particle filter to achieve non-local and non-linear optimization in order to increase this convergence area. Thanks to multi-view geometry and image transfer techniques, a set of particles (which correspond to potential camera velocities) are drawn and evaluated in order to evaluate the best camera trajectory. This new control law is validated on a 6 DOF positioning task performed on a real gantry robot and statistical comparisons are also provided from simulation results.