Reducing Uncertainty Using Placement and Regrasp Planning on a Triangular Corner Fixture

This paper presented an regrasp planning method to eliminate grasp uncertainty while considering the geometric constraints of a fixture. The method automatically finds the Stable Placement Poses (SPPs) of an object on a Triangular Corner Fixture (TCF), elevates the object from its SPPs to dropping poses and finds the Deterministic Dropping Poses (DDPs), builds regrasp graphs by using the SPP-DDP pairs and their associated grasp configurations, and searches the graph to find regrasp motion sequences for precise assembly. Since the SPPs and their associated regrasps are constrained by the TCF's geometry and have high precision, the final object poses regrasped via it has low uncertainty and can be directly used for assembly by position control. In the experimental section, we study the performance of analytical and learning-based methods for estimating the DDPs of different objects and quantitatively examine the proposed method's ability to suppress uncertainty using assembly tasks like peg-in-hole insertion and sheathing tubes, aligning holes, mounting bearing housings, etc. The results demonstrate the method's robustness and efficacy.

Reducing Uncertainty Using Placement and Regrasp Planning on a Triangular Corner Fixture

This paper presented an regrasp planning method to eliminate grasp uncertainty while considering the geometric constraints of a fixture. The method automatically finds the Stable Placement Poses (SPPs) of an object on a Triangular Corner Fixture (TCF), elevates the object from its SPPs to dropping poses and finds the Deterministic Dropping Poses (DDPs), builds regrasp graphs by using the SPP-DDP pairs and their associated grasp configurations, and searches the graph to find regrasp motion sequences for precise assembly. Since the SPPs and their associated regrasps are constrained by the TCF's geometry and have high precision, the final object poses regrasped via it has low uncertainty and can be directly used for assembly by position control. In the experimental section, we study the performance of analytical and learning-based methods for estimating the DDPs of different objects and quantitatively examine the proposed method's ability to suppress uncertainty using assembly tasks like peg-in-hole insertion and sheathing tubes, aligning holes, mounting bearing housings, etc. The results demonstrate the method's robustness and efficacy.

Molecular Learning of a Soft-Disks Fluid

This work is based on the Equivalence between Molecular Dynamics and Neural networks. It provides learning proofs in a Lennard-Jones (LJ) fluid, presented as a network of particles having non-bonded interactions. I describe the fluid's learning as the property of an order that emerges as an adaptation in establishing equilibrium with energy and thermal conservation. The experimental section demonstrates the fluid can be trained with logic-gates patterns. The work goes beyond Molecular Computing's application, explaining how this model uses its intrinsic minimizing properties in learning and predicting outputs. Finally, it gives hints for a theory on real chemistry's computational universality.

Oversampling Errors in Multimodal Medical Imaging Are Due to the Gibbs Effect

To analyze multimodal three-dimensional medical images, interpolation is required for resampling which—unavoidably—introduces an interpolation error. In this work we describe the interpolation method used for imaging and neuroimaging and we characterize the Gibbs effect occurring when using such methods. In the experimental section we consider three segmented three-dimensional images resampled with three different neuroimaging software tools for comparing undersampling and oversampling strategies and to identify where the oversampling error lies. The experimental results indicate that undersampling to the lowest image size is advantageous in terms of mean value per segment errors and that the oversampling error is larger where the gradient is steeper, showing a Gibbs effect.

MODELING THE SNOW DEPOSIT PROCESS ON THE HIGHWAYS IN THE FLOWVISION

Statement of the problem. The problems of snow deposit modeling on the highways with crash barriers during blizzards in the FlowVision. Results. The highway section passing in the embankment as an experimental section has been considered. The geometric model of the highway section was created. The information resources for creating a hydrodynamic model of snowflow stream of highway embankment with barrier barriers during blizzard were identified. The modeling of the snow deposit process in the experimental section using the FlowVision during blizzards with different parameters was carried out. Conclusions. It was concluded that it is possible to use the FlowVision to improve the methodology for snow protection designing and determining of snow removal parameters for winter road maintenance.

Granular Material Development Applied in an Experimental Section for Civil Engineering Purposes

In this study, a granular material (GM) derived from wastes generated in waste-to-energy plants was developed. Weathered bottom ash (WBA) and air pollution control (APC) ashes obtained from municipal solid waste incineration (MSWI) were used as raw materials. A mortar (M) with 50 wt. % of APC and 50 wt. % of Ordinary Portland Cement (OPC) CEM-I was prepared. The GM formulation was 20 wt. % M and 80 wt. % WBA. At the laboratory scale, WBA, APC, M, and crushed GM were evaluated by means of dynamic leaching (EN 12457-4) tests, and WBA, M, and crushed GM by percolation column (CEN/TS 16637) tests. The metal(loid)s analyzed were below the non-hazardous limits, regarding the requirement of the metal(loid)s released for waste revalorization. In order to simulate a road subbase real scenario, the crushed GM was tested in an experimental section (10 × 20 × 0.2 m). During a 600-day period, the leachates generated by the percolation of rainwater were collected. This research shows outstanding results regarding the metal(loid)s released for both the “accumulated” and “punctual” leachates collected. An accomplishment in the immobilization of metal(loid)s from APC residues was achieved because of the encapsulation effect of the cement. The GM formulation from both MSWI wastes can be considered an environmentally safe procedure for revalorizing APC residues.

Modeling the Snow Deposit Process on the Highways in the Flowvision Software

Постановка задачи. Рассмотрена задача моделирования отложения снега во время метелей на автомагистралях с барьерными ограждениями в программе FlowVision . Результаты. В качестве опытного участка рассмотрен участок автомагистрали, проходящий в насыпи. Создана геометрическая модель участка автомагистрали. Обоснованы информационные ресурсы для создания гидродинамической модели обтекания насыпи автомагистрали с барьерными ограждениями снеговетровым потоком во время метелей. Проведено моделирование процесса снегонакопления на опытном участке с использованием программного комплекса FlowVision во время метелей с различными параметрами. Выводы. Сделан вывод о возможности применения программного комплекса FlowVision для совершенствования методики назначения снегозащитных устройств и определения параметров снегоочистки при зимнем содержании автомобильных дорог. Statement of the problem. The problems of snow deposit modeling on the highways with crash barriers during blizzards in the FlowVision was discussed. Results. The highway section passing in the embankment as an experimental section has been considered. The geometric model of the highway section was created. The information resources for designing a hydrodynamic model of a snowflow stream of highway embankment with barriers during blizzard were identified. The modeling of the snow deposit process in the experimental section using the FlowVision software during blizzards with different parameters was carried out. Conclusions. It was concluded that it is possible to use the FlowVision software to improve the methodology for snow protection designing and determining snow removal parameters for winter road maintenance.