On the Covariance of ICP-based Scan-matching Techniques

This paper considers the problem of estimating the covariance of roto-translations computed by the Iterative Closest Point (ICP) algorithm. The problem is relevant for localization of mobile robots and vehicles equipped with depth-sensing cameras (e.g., Kinect) or Lidar (e.g., Velodyne). The closed-form formulas for covariance proposed in previous literature generally build upon the fact that the solution to ICP is obtained by minimizing a linear least-squares problem. In this paper, we show this approach needs caution because the rematching step of the algorithm is not explicitly accounted for, and applying it to the point-to-point version of ICP leads to completely erroneous covariances. We then provide a formal mathematical proof why the approach is valid in the point-to-plane version of ICP, which validates the intuition and experimental results of practitioners.Comment: Accepted at 2016 American Control Conferenc

Accurate 3D maps from depth images and motion sensors via nonlinear Kalman filtering

This paper investigates the use of depth images as localisation sensors for 3D map building. The localisation information is derived from the 3D data thanks to the ICP (Iterative Closest Point) algorithm. The covariance of the ICP, and thus of the localization error, is analysed, and described by a Fisher Information Matrix. It is advocated this error can be much reduced if the data is fused with measurements from other motion sensors, or even with prior knowledge on the motion. The data fusion is performed by a recently introduced specific extended Kalman filter, the so-called Invariant EKF, and is directly based on the estimated covariance of the ICP. The resulting filter is very natural, and is proved to possess strong properties. Experiments with a Kinect sensor and a three-axis gyroscope prove clear improvement in the accuracy of the localization, and thus in the accuracy of the built 3D map.Comment: Submitted to IROS 2012. 8 page

Invariant EKF Design for Scan Matching-aided Localization

Localization in indoor environments is a technique which estimates the robot's pose by fusing data from onboard motion sensors with readings of the environment, in our case obtained by scan matching point clouds captured by a low-cost Kinect depth camera. We develop both an Invariant Extended Kalman Filter (IEKF)-based and a Multiplicative Extended Kalman Filter (MEKF)-based solution to this problem. The two designs are successfully validated in experiments and demonstrate the advantage of the IEKF design

Universal design and accessibility in Taipei City: Definitions, design, and the Disability Rights Movement

Abstract In Taiwan, the disability rights advocacy movement has existed since the 1980s. The lift of Martial law in 1987 allowed multiple social movements to flourish. Specifically, the disability rights movement adopted language developed by other global social movements, such as Universal Design. This social movement worked closely with the government to make effectual infrastructural change to institute accessibility in Taipei, the capital city. However, a close review of government objectives and initiatives in published works, and the goals and initiatives of disability advocate groups, reveals that there has been a shift in the definition of accessibility in the advocacy rights movement from infrastructural accessibility to social accessibility. This project is an analysis of the media and published works of the Taiwanese government in relation to universal design goals, and the same media from advocacy groups about their own goals and objectives for disability rights, outlining the definition gap and finding the true definition of social accessibility. The advocacy rights movement has shifted its view of accessibility to a fully liveable society in which disabled persons may thrive and have fully realized social rights, whereas the government of Taipei City still views accessibility as a right to accessible built infrastructure

Investigation of Safe-Level Testing for Beta-lactam, Sulfonamide, and Tetracycline Residues in Commingled Bovine Milk

In the United States more than “a billion pounds of butter, 7 billion pounds of cheese, 1.5 billion pounds of yogurt, and one billion gallons of ice cream” (USDA, 2005) are produced annually. According to the USDA Food Pyramid, it is recommended that every person consume between two and three cups of milk products every day (USDA, 2005). With so much product being consumed by the greater public there is cause for concern on the quality of the product being ingested. The purpose of this research is to explore the quality of milk product, particularly safe-level residue testing for antibiotics in bovine milk, on an international scale. The health hazards of having antibiotic residues in milk have also been widely examined with alarming results. Antibiotic residues have been implicated in transfer of antibiotic resistant plasmids in bacteria as well as possible allergic reaction, both of which are devastating to the citizens of the world. Through previous experimentation different safe levels of antibiotic residues have been derived, some of which are different in various countries worldwide. Knowing that different countries employ multiple testing methods and have different safe levels, it is safe to assert that citizens internationally are receiving different antibiotic levels in their dairy products, thus making this a social justice issue. Many studies have been previously conducted that focus on the safe-levels of particular antibiotics with the various accepted testing methods as well as the false positives that the different tests can cause. The DelvoTest and Charm tests will be the primary tests examined, as they are the most widely used and FDA approved. The final step to ensure justice is a global policy that would include education of farmers and those working in and around the dairy industry as well as recognition of a problem on a regional, national, and world level

RECALAGE RIGIDE DE RELEVÉS LASER PAR MISE EN CORRESPONDANCE ROBUSTE BASÉE SUR DES SEGMENTS

International audienceLe recalage de relevés laser se révèle indispensable pour assembler des données précises devant servir à l'analyse, à la documentation et à la reconstruction tridimensionnelle d'environnements. Ce problème apparaît lorsqu'une zone d'intérêt est numérisée, au fil de temps, deux ou plusieurs fois, ou quand sa complexité nécessite un accroissement du nombre de stations de scanner laser fixe. Aussi, en raison de la variété des techniques disponibles d'acquisition, l'intégration multi-données devient une question importante puisqu'elle permet de mettre en cohérence des données contenant souvent une information complémentaire. La vaste majorité des algorithmes existants s'appuient sur les éléments ponctuels. C'est pourquoi les approches basées sur l'ICP demeurent actuellement les plus répandues. Cet article propose l'utilisation des arêtes sous forme d'intersections entre les plans modelés, pour le recalage rigide des nuages de points mobiles avec d'autres données, qu'elles soient 2D ou 3D. Ces primitives peuvent être aisément extraites, même si les données laser sont peu denses. Quelques méthodes de recalage basées sur les entités linéaires ont été examinées afin de vérifier leur précision et robustesse au bruit. Définie en tant que distance modifiée de Hausdorff entre deux jeux de segments, le critère d'exactitude a été employé pour les besoins d'une analyse quantitative. Au vu de ces éléments, la transformation rigide décrivant le meilleur alignement peut être déterminée avec l'algorithme FMII. Étant donné que la mise en correspondance automatique d'entités linéaires est ardue et influence l'estimation des paramètres de passage, une méthode d'appariement étudiant la similitude relative a été suggérée. Tous ces composants ont été ensuite intégrés pour créer une approche combinée RANSAC-FMII. Enfin, la précision de cette méthode de recalage avec appariements explicites itérés basant sur les segments a été évaluée et discutée. Abstract In the processes of analyzing, documenting and modelling the surrounding environment, an accurate registration of point clouds is necessary in order to obtain high-quality data. This procedure arises whenever a particular area is scanned by a laser more than once or from several different positions. Due to the variety of surveying techniques available, fusing the multi-source, complementary information data into one model is a very important matter. The vast majority of existing registration algorithms operate on feature points, hence ICP-like methods are the prevalent approach. This article proposes the use of edges obtained from intersecting planes modelled within individual point clouds for the accurate registration of mobile laser scans with other data, whether 2D or 3D. This type of primitives can be easily extracted, even from low-density point clouds. Using simulated data, several existing line-based registration algorithms have been evaluated in terms of reliability and robustness to noise. For the purpose of quantitative assessment, an accuracy criterion taking advantage of a modified Hausdorff distance between two sets of lines has been employed. Having regard to these elements, the rigid body transformation that gives the best alignment can be calculated with FMII algorithm. Since the automatic pairing of line segments is a challenging task influencing the accuracy of the estimated transformation parameters, a method that considers the relative similarity is proposed. All these components are used to form an approach combining RANSAC-FMII algorithms. Finally, the accuracy of this line-based registration method with an explicit iterative matching is evaluated and discussed

Alien Registration- Goulette, Blanche A. (Dexter, Penobscot County)

https://digitalmaine.com/alien_docs/11270/thumbnail.jp