Perceiving,learning, and exploiting object affordances for autonomous pile manipulation

Autonomous manipulation in unstructured environments will enable a large variety of exciting and important applications. Despite its promise, autonomous manipulation remains largely unsolved. Even the most rudimentary manipulation task—such as removing objects from a pile—remains challenging for robots. We identify three major challenges that must be addressed to enable autonomous manipulation: object segmentation, action selection, and motion generation. These challenges become more pronounced when unknown man-made or natural objects are cluttered together in a pile. We present a system capable of manipulating unknown objects in such an environment. Our robot is tasked with clearing a table by removing objects from a pile and placing them into a bin. To that end, we address the three aforementioned challenges. Our robot perceives the environment with an RGB-D sensor, segmenting the pile into object hypotheses using non-parametric surface models. Our system then computes the affordances of each object, and selects the best affordance and its associated action to execute. Finally, our robot instantiates the proper compliant motion primitive to safely execute the desired action. For efficient and reliable action selection, we developed a framework for supervised learning of manipulation expertise. To verify the performance of our system, we conducted dozens of trials and report on several hours of experiments involving more than 1,500 interactions. The results show that our learning-based approach for pile manipulation outperforms a common sense heuristic as well as a random strategy, and is on par with human action selection.     

From conceptual models to schemata: An object-process-based data warehouse construction method

Data warehouse modeling is a complex task, which involves knowledge of business processes of the domain of discourse, understanding the structural and behavioral system's conceptual model, and familiarity with data warehouse technologies. The suitability of current data warehouse modeling methods for large-scale systems is questionable, as they require multiple manual actions to discover measures and relevant dimensional entities and they tend to disregard the system's dynamic aspects. We present an Object-process-based Data Warehouse Construction (ODWC) method that overcomes these limitations of existing methods by utilizing the operational system conceptual model to construct a corresponding data warehouse schema. We specify the ODWC method, apply it on a case study, evaluate it, and compare it to existing methods.     

Predictive functional control based on an adaptive fuzzy model of a hybrid semi-batch reactor

In this paper a new approach to the control of a nonlinear, time-varying process is proposed. It is based on a recursive version of the fuzzy identification method and predictive functional control. First, the recursive fuzzy identification method is derived, after which it is used in connection with fuzzy predictive functional control to construct an adaptive fuzzy predictive functional controller. The adaptive FPFC is then tested on a nonlinear, time-varying, semi-batch reactor process and compared with the standard FPFC, which uses non-adaptive fuzzy model. The simulation results are promising; they indicate that the control of time-varying, nonlinear processes with the FPFC can be improved with the use of an adaptive fuzzy model. An improvement in reference tracking and disturbance rejection can be observed, but the main advantage is the reduced number of switchings between hot and cold water. This is an important improvement in the case of real applications.     

Towards a contingent approach of customer involvement in defence projects: An exploratory study

This paper reports the main results of an exploratory, multiple case study investigating customer involvement practices in system development projects in the Israeli defence industry. The study proposes and examines a theoretical contingency model regarding the effect of customer involvement modes on project success, moderated by project characteristics. It focuses specifically on the working mode of customers' representatives along the continuum between external supervision to full participation in project activities.     

Trichothecium roseum的酸碱属性及pH值对其胞外酶活性和致病性的影响

目的：明确粉红单端孢（Trichothecium roseum）侵染果实的酸碱性质,测定3 种pH值孢子悬浮液接种对苹果果实病斑直径及胞外酶活性的影响。方法：用T. roseum接种“富士”苹果,测定果实病斑处的pH值变化。用pH值分别为3、5和7的孢子悬浮液接种果实,观察接种对果实病斑直径及病斑处果胶酶和纤维素酶活性的影响。结果：T. roseum接种后果实病斑处的pH值显著升高,由第0天的3.54升高至第12天的4.84,提高了36.7%。3 种pH值孢子悬浮液接种果实后,以pH 7接种的果实病斑直径最大,第9天时分别高出pH 5与pH 3接种的35.2%与68.0%。pH 7接种的果实病斑处具有最高的果胶酶及纤维素酶活性,第9天时的果胶甲酯酶、果胶甲基多聚半乳糖醛酸酶、多聚半乳糖醛酸酶活性分别为pH 3接种的2.95、1.61 倍和1.68 倍,为pH 5接种的2、1.25 倍和1.39 倍。此外,pH 7接种的果实病斑处纤维素酶和β-葡萄糖苷酶第9天的活性分别为pH 3接种的1.97 倍和1.64 倍,为pH 5接种的1.33 倍和1.3 倍。结论：T. roseum属碱化菌,中性或偏碱环境可提高该菌损伤接种苹果果实病斑处的胞外酶活性,增强其致病性。     

Analyzing Dynamic Behavior of Geosynthetic-Reinforced Soil Retaining Walls

An advanced generalized plasticity soil model and bounding surface geosynthetic model, in conjunction with a dynamic finite element procedure, are used to analyze the behavior of geosynthetic-reinforced soil retaining walls. The construction behavior of a full-scale wall is first analyzed followed by a series of five shaking table tests conducted in a centrifuge. The parameters for the sandy backfill soils are calibrated through the results of monotonic and cyclic triaxial tests. The wall facing deformations, strains in the geogrid reinforcement layers, lateral earth pressures acting at the facing blocks, and vertical stresses at the foundation are presented. In the centrifugal shaking table tests, the response of the walls subject to 20 cycles of sinusoidal wave having a frequency of 2 Hz and of acceleration amplitude of 0.2g are compared with the results of analysis. The acceleration in the backfill, strain in the geogrid layers, and facing deformation are computed and compared to the test results. The results of analysis for both static and dynamic tests compared reasonably well with the experimental results.