A 3D shape segmentation approach for robot grasping by parts

Neuro-psychological findings have shown that human perception of objects is based on part decomposition. Most objects are made of multiple parts which are likely to be the entities actually involved in grasp affordances. Therefore, automatic object recognition and robot grasping should take advantage from 3D shape segmentation. This paper presents an approach toward planning robot grasps across similar objects by part correspondence. The novelty of the method lies in the topological decomposition of objects that enables high-level semantic grasp planning.In particular, given a 3D model of an object, the representation is initially segmented by computing its Reeb graph. Then, automatic object recognition and part annotation are performed by applying a shape retrieval algorithm. After the recognition phase, queries are accepted for planning grasps on individual parts of the object. Finally, a robot grasp planner is invoked for finding stable grasps on the selected part of the object. Grasps are evaluated according to a widely used quality measure. Experiments performed in a simulated environment on a reasonably large dataset show the potential of topological segmentation to highlight candidate parts suitable for grasping.     

Model Checking Linear Programs with Arrays

In previous work we proposed Linear Programs as a fine grained model for imperative programs, and showed how the model checking procedure used in SLAM can be generalised to a model checking procedure for Linear Programs. In this paper we show that our model checking procedure for linear programs can be extended in such a way to support the analysis of linear programs featuring a symbol for undefined values and conditional expressions. This extension is particularly important as it paves the way to the construction of model checking procedures for wider classes of imperative programs such as, e.g., linear programs with arrays. We provide a detailed account of a symbolic model checking procedure for this extended class of linear programs, discuss its implementation in the eureka tool, and present experimental results that confirm its effectiveness in the analysis of linear programs with arrays.     

Physics-based virtual reality for task learning and intelligent disassembly planning

Physics-based simulation is increasingly important in virtual manufacturing for product assembly and disassembly operations. This work explores potential benefits of physics-based modeling for automatic learning of assembly tasks and for intelligent disassembly planning in desktop virtual reality. The paper shows how realistic physical animation of manipulation tasks can be exploited for learning sequential constraints from user demonstrations. In particular, a method is proposed where information about physical interaction is used to discover task precedences and to reason about task similarities. A second contribution of the paper is the application of physics-based modeling to the problem of disassembly sequence planning. A novel approach is described to find all physically admissible subassemblies in which a set of rigid objects can be disassembled. Moreover, efficient strategies are presented aimed at reducing the computational time required for automatic disassembly planning. The proposed strategies take into account precedence relations arising from user assembly demonstrations as well as geometrical clustering. A motion planning technique has also been developed to generate non-destructive disassembly paths in a query-based approach. Experiments have been performed in an interactive virtual environment including a dataglove and motion tracker that allows realistic object manipulation and grasping.     

Numerical Analysis of Convective Instabilities in a Transient Short-Hot-Wire Setup for Measurement of Liquid Thermal Conductivity

Numerical simulation has been used to investigate the effects of natural convection on measurements of the thermal conductivity of fluids by transient hot-wire methods. Comparison of the numerical data with the experimental results obtained with a custom-built setup exploiting a short-wire geometry allows fixing an operationally useful time scale, where convective effects can be safely neglected.     

Endometrial cytology during menstrual cycle, menopause and progestinic treatment

The AA. examined 72 cytological smears of the human normal endometrium. Twenty-three were taken during the proliferative phase, 17 during the secretory phase, 21 during menopause and 11 during estro-progestinic treatment. The study pointed out that the endometrial smear, which has been employed up to now almost exclusively in the cyto-oncological field, is also quite suitable for a dynamic cyto-functional evaluation of ovarian function, because of the series of interpretative elements, easily and readily identifiable at the microscope, which it furnishes.