Diego Borro

A large haptic device for aircraft engine maintainability

The virtual reality for maintainability (Revima) VR system supports maintainability simulation in aeronautics. Within this project we have developed and integrated a haptic device, the large haptic interface for aeronautic maintainability (LHIfAM). We use this device to track hand movements and provide force feedback within the large geometric models that describe aircraft engines. The user movements are the same as those that occur when testing physical mock-ups. An integrated haptic device and VR system for testing aircraft engines reduces development costs and avoids the necessity of physical mock-ups formaintainability.

Description of a haptic system for virtual maintainability in aeronautics

This paper describes a haptic system for maintainability simulation in aeronautics, called REVIMA (Virtual Reality for Maintainability). In this project a software-hardware tool is designed and built to realistically simulate assembly-disassembly operations. It also helps to perform accessibility, interference and maintainability analysis by using virtual reality techniques without physical mock-ups. The system gives the user a reliable and realistic response. In order to achieve these requirements, the device has a workspace similar to the size of a turbo-engine. In addition this workspace can be placed in different positions to study ergonomics aspects of the simulated tasks.

Providing guidance for maintenance operations using automatic markerless Augmented Reality system

This paper proposes a new real-time Augmented Reality based tool to help in disassembly for maintenance operations. This tool provides workers with augmented instructions to perform maintenance tasks more efficiently. Our prototype is a complete framework characterized by its capability to automatically generate all the necessary data from input based on untextured 3D triangle meshes, without requiring additional user intervention. An automatic offline stage extracts the basic geometric features. These are used during the online stage to compute the camera pose from a monocular image. Thus, we can handle the usual textureless 3D models used in industrial applications. A self-supplied and robust markerless tracking system that combines an edge tracker, a point based tracker and a 3D particle filter has also been designed to continuously update the camera pose. Our framework incorporates an automatic path-planning module. During the offline stage, the assembly/disassembly sequence is automatically deduced from the 3D model geometry. This information is used to generate the disassembly instructions for workers.

A review of surgical robots for spinal interventions.

This study aimed to describe the state of the art in surgical robotics for spinal interventions, a challenging problem for which robots can provide valuable assistance.

Approximation of Optimal Voxel Size for Collision Detection in Maintainability Simulations within Massive Virtual Environments

This paper describes a Collision Method for massive virtual environments composed of millions of triangles. It has been applied in the aeronautics industry for maintainability simulations using virtual aircraft engine mock‐ups. The method performs well and has a good interactive frame rate even when it is used for computing force feedback with haptic devices. Space sorting problems chiefly related to voxel techniques, such as memory requirements and optimal voxel size, have been solved. We use advanced memory structures and hashing techniques. To find the optimal voxel size, several analytical solutions have been proposed and compared. These solutions are based on the performance cost function of the algorithm used. Experiments have been undertaken to verify these analytical solutions.

GPU local triangulation: an interpolating surface reconstruction algorithm

A GPU capable method for surface reconstruction from unorganized point clouds without additional information, called GLT (GPU Local Triangulation), is presented. The main objective of this research is the generation of a GPU interpolating reconstruction based on local Delaunay triangulations, inspired by a pre‐existing reconstruction algorithm. Current graphics hardware accelerated algorithms are approximating approaches, where the final triangulation is usually performed through either marching cubes or marching tetrahedras. GPU‐compatible methods and data structures to perform normal estimation and the local triangulation have been developed, plus a variation of the Bitonic Merge Sort algorithm to work with multi‐lists. Our method shows an average gain of one order of magnitude over previous research.

Towards real time 3D tracking and reconstruction on a GPU using Monte Carlo simulations

This paper addresses the problem of camera tracking and 3D reconstruction from image sequences, i.e., the monocular SLAM problem. Traditionally, this problem is solved using non-linear minimization techniques that are very accurate but hardly used in real time. This work presents a highly parallelizable random sampling approach based on Monte Carlo simulations that fits very well on the graphics hardware. The proposed algorithm achieves the same precision as non linear optimization, getting real time performance running on commodity graphics hardware. Both accuracy and performance are evaluated using synthetic data and real video sequences captured with a hand-held camera. Moreover, results are compared with an implementation of Bundle Adjustment showing that the presented method gets similar results in much less time.

Influence of multisensory feedback on haptic accessibility tasks

Environments of a certain nature, such as those related to maintenance tasks can benefited from haptic stimuli by performing accessibility simulation in a realistic manner. Accessibility is defined as the physical feasibility of accessing an element of a 3D model avoiding undesirable collisions. This paper studies the benefits that multisensory systems can provide in performing this kind of tasks. The research is specially focused on the improvements provided by auditory feedback to the user’s performance. We have carried out a user study where participants had to perform an accessibility task with the aid of different combinations of sensorial stimuli. A large haptic interface for aeronautic maintainability has been extended with real-time sound generation capabilities to study this issue. The results of these experiments show that auditory stimuli provide with useful cues to the users helping them to correct trajectories and hence improving their performance.

Real-time deformation, registration and tracking of solids based on physical simulation

This paper proposes a novel approach to registering deformations of 3D non-rigid objects for Augmented Reality applications. Our prototype is able to handle different types of objects in real-time regardless of their geometry and appearance (with and without texture) with the support of an RGB-D camera. During an automatic offline stage, the model is processed in order to extract the data that serves as input for a physics-based simulation. Using its output, the deformations of the model are estimated by considering the simulated behaviour as a constraint. Furthermore, our framework incorporates a tracking method based on templates in order to detect the object in the scene and continuously update the camera pose without any user intervention. Therefore, it is a complete solution that extends from tracking to deformation formulation for either textured or untextured objects regardless of their geometrical shape. Our proposal focuses on providing a correct visual with a low computational cost. Experiments with real and synthetic data demonstrate the visual accuracy and the performance of our approach.

A Brain Surgery Simulator

A proposed real-time neurosurgery simulator handles skull drilling and surgical interaction with the brain. This involves the development and combination of areas such as collision handling, haptic rendering, physical simulation, and volumetric visualization. The simulators input data comes from computed-tomography and magnetic-resonance-imaging images of the patients. Collision detection for drilling uses only density data; collision detection for interaction with the brain is based on uniform spatial subdivision of a tetrahedral mesh. To take advantage of all the information, the simulator employs visualization methods such as volumetric isosurfaces and deformable volume rendering.