This paper proposes a solution by genetic algorithms to the problem of planning a robust and suboptimal trajectory in the velocity space of a mobile robot. Robust trajectories are obtained introducing cumulative noise in the evaluation of the fitness function and introducing modifications in the genetic algorithm to taking into account this new feature. Results are presented that show the perfo...

We present a new adaptive Wiener filter (AWF) super-resolution (SR) algorithm that employs a global background motion model but is also robust to limited local motion. The AWF relies on registration to populate a common high resolution (HR) grid with samples from several frames. A weighted sum of local samples is then used to perform nonuniform interpolation and image restoration simultaneously...

A method to compute motion models in real time from point-to-line correspondences using linear programming is presented. Point-to-line correspondences are the most reliable motion measurements given the aperture effect, and it is shown how they can approximate other motion measurements as well. Using an L1 error measure for image alignment based on point-to-line correspondences and minimizing t...

In this thesis we consider the problem of generating motion plans for a nonlinear dynamical system that are guaranteed to succeed despite uncertainty in the environment, parametric model uncertainty, disturbances, and/or errors in state estimation. Furthermore, we consider the case where these plans must be generated online, because constraints such as obstacles in the environment may not be kn...

It is hard to estimate optical flow given a realworld video sequence with camera shake and other motion blur. In this paper, we first investigate the blur parameterization for video footage using near linear motion elements. We then combine a commercial 3D pose sensor with an RGB camera, in order to film video footage of interest together with the camera motion. We illustrates that this additio...

This paper presents a novel approach to incrementally estimating visual motion over a sequence of images. We start by formulating constraints on image motion to account for the possibility of multiple motions. This is achieved by exploiting the notions of weak continuity and robust statistics in the formulation of a minimization problem. The resulting objective function is non{convex. Tradition...

This paper deals with motion planning for a mobile robot on rough terrain. We proposed in 9] a geometrical planner for articulated robots which can take into account uncertainty on the terrain and on the position of the robot. This paper aims at improving the robustness of the trajectory using landmark based approach. We consider regions of the terrain where natural landmarks are visible. We pr...

Our work is focused on defining a generic approach for planning landmark based motion. In previous works we have introduced the formal basis for this and showed simulation results. In this paper we first demonstrate the relevance of our work with experiments on a real robot. Then, on the base of these results we introduce new strategy for planning selecting landmarks in order to improve the rob...

Face detection is fundamental for several important applications, such as, face recognition and human-computer interaction. This paper details a novel hierarchical face detector which combines motion, colour and late fusion. Motion segmentation is employed to eliminate background clutter and to reduce the initial search space. Subsequently, skin segmentation is used to determine a candidate fac...

This paper presents a novel approach to incremen-tally estimating visual motion over a sequence of images. We start by formulating constraints on image motion to account for the possibility of multiple motions. This is achieved by exploiting the notions of weak continuity and robust statistics in the formulation of a minimization problem. The resulting objective function is non{convex. Traditio...