MALIS , Ezio

Computing the pose from 3D data acquired in two different frames is of high importance for several robotic tasks like odometry, SLAM and place recognition. The pose is generally obtained by solving a least-squares problem given points-to-points, points-to-planes or points to lines correspondences. The non-linear least-squares problem can be...

The conception of full autonomous robotic systems is an enduring ambition for humankind. Nowadays theoretical and technological advances have allowed engineers to conceive complex systems that can replace humans in many tedious or dangerous applications. However, in order to considerably enlarge the flexibility and the domain of applications of...

Existing visual servoing techniques which do not need metric information require, on the other hand, prior knowledge about the object's shape and/or the camera's motion. In this paper, we propose a new visual servoing technique which does not require any of them. The method is direct in the sense that: the intensity value of all pixels is used...

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The objective of this paper is to propose a new homography-based approach to image-based visual servoing. The visual servoing method does not need any measure of the 3D structure of the observed target. Only visual information measured from the reference and the current image are needed to compute the task function (isomorphic to the camera...

The displacement of a calibrated camera between two images of a planar object can be estimated by decomposing a homography matrix. The aim of this document is to propose a new method for solving the homography decomposition problem. This new method provides analytical expressions for the solutions of the problem, instead of the...

This paper describes a new image-based approach to tracking the 6 degrees of freedom trajectory of a stereo camera pair using a corresponding reference image pair whilst simultaneously determining pixel matching between onsecutive images in a sequence. A dense minimisation approach is employed which directly uses all grey-scale information...

In this paper, we address the problem of increasing the precision of dense direct stereo visual odometry methods. Dense methods need a dense depth map to generate warped images (virtual views) that will match with reference images if the estimated pose is good. Previous works have shown that generating the depth map by machine learning methods...

Autonomous mobile robot navigation in a human populated and encumbered environment is recognized as a hard problem to be solved in real-time. Most of the time, robots face the so-called 'Freezing Robot Problem', that occurs when the robot stops because no feasible and safe motion can be found. In order to provide to the robot the capability of...

Visual odometry is an important part of the perception module of autonomous robots. Recent advances in deep learning approaches have given rise to hybrid visual odometry approaches that combine both deep networks and traditional pose estimation methods. One limitation of deep learning approaches is the availability of ground truth data needed...

Stereo matching is one of the low-level visual perception tasks. Currently, two-stage 2D-3D networks and three-stage recurrent networks dominate deep stereo matching. These methods build a cost volume with low-resolution stereo feature maps, which splits the network into a feature net and a matching net. However, the 2D feature map is not...

Hybrid visual odometry methods achieve state-of-the-art performance by fusing both data-based deep learning networks and model-based localization approaches. However, these methods also suffer from deep learning domain gap problems, which leads to an accuracy drop of the hybrid visual odometry approach when new type of data is considered. This...

This paper presents a novel approach for Visual Servoing (VS) using a multispectral camera, where the number of data are more than three times that of a standard color camera. To meet real-time feasibility, the multispectral data captured by the camera are processed using dimensionality reduction techniques. Instead of relying on traditional...

This article proposes a nonlinear complementary filter for the special linear Lie-group SL(3) that fuses low-frequency state measurements with partial velocity measurements and adaptive estimation of unmeasured slowly changing velocity components. The obtained results have direct application on the problem of filtering a sequence of image...

During the last decade, a number of highly successful visual servo control and real-time image processing algorithms have been proposed that use the homography between images of a planar scene as the primary measurement. The performance of the algorithms depends directly on the quality of the homography estimates obtained, and these estimates...

This work focuses on localizing a single target robot with multi-robot formations in 2D space. The cooperative robots employ inter-robot range measurements to assess the target position. In the presence of noisy measurements, the choice of formation geometries significantly impacts the accuracy of the target robot's pose estimation. While an...

In the last decade, many vision-based robot controllers have been designed using Cartesian information encoded in the homography transformation that links two images of a planar object. For any approach, the performance of the closed-loop system depends on the quality of the homography estimates obtained. In this paper, we exploit the special...

We present a comprehensive framework based on direct Visual Simultaneous Localization and Mapping (V-SLAM) to observe a vertical coastal cliff. The precise positioning of data measurements (such as ground-penetrating radar) is crucial for environmental observations. However, in GPS-denied environments near large structures, the GPS signal can...

The ability to perform long-term robotic operations in dynamic environments remains a challenge in fields such as surveillance, agriculture and autonomous vehicles. For improved localization and monitoring over time, this paper proposes a novel model update framework using image-based 3D change localization and segmentation. Specifically,...

As image registration becomes more and more central to many biomedical imaging applications, the efficiency of the algorithms becomes a key issue. Image registration is classically performed by optimizing a similarity criterion over a given spatial transformation space. Even if this problem is considered as almost solved for linear...

In robotic assisted beating heart surgery, motion of the heart surface might be virtually stabilized to let the surgeon work as in on-pump cardiac surgery. Virtual stabilization means to compensate physically the relative motion between instrument tool tip and point of interest on the heart surface, and to offer surgeon a stable visual display...