Team O2AS at the world robot summit 2018: an approach to robotic kitting and assembly tasks using general purpose grippers and tools

ABSTRACT

In this article, we propose a versatile robotic system for kitting and assembly tasks which uses no jigs or commercial tool changers. Instead of specialized end effectors, it uses its two-finger grippers to grasp and hold tools to perform subtasks such as screwing and suctioning. A third gripper is used as a precision picking and centering tool, and uses in-built passive compliance to compensate for small position errors and uncertainty. A novel grasp point detection for bin picking is described for the kitting task, using a single depth map. Using the proposed system we competed in the Assembly Challenge of the Industrial Robotics Category of the World Robot Challenge at the World Robot Summit 2018, obtaining 4th place and the SICE award for lean design and versatile tool use. We show the effectiveness of our approach through experiments performed during the competition.     

Modeling dynamic viscosity of n-alkanes using LSSVM technique

One of the important thermophysical properties is viscosity which expresses the resistance of fluid to flow. The least squares support vector machine (LSSVM) algorithm is proposed as a novel method for prediction of dynamic viscosity of different normal alkanes in a wide range of pressure and temperature. As this study is purely computational, 228 experimental data points were gathered from literature for training and validation of the model. The outcomes of the LSSVM algorithm were compared with the actual data with acceptable average absolute relative deviation and the coefficient of determination (R²) of 1.014 and 0.9968, respectively. The comparisons showed that the predicting model has the potential of prediction of n-alkane dynamic viscosity in terms of pressure, temperature, and carbon number of n-alkane, so this strategy can be used as a simple tool for predicting the behavior of reservoir fluids.     

综放工作面风量及采空区漏风定量检测

通过对中煤塔山煤矿30509综放工作面采空区漏风及有害气体分析的研究，总结了通过定量连续释放SF₆示踪气体，来检测工作面风量与采空区漏风的方法，测定了沿工作面采空区的漏风分布及漏风流线的深度。采用定时测量法，确定了30509工作面随工作面不断推进，与对应地表发生了导通现象；采用定量测量法，确定了内部漏风量和外部漏风量较大，对综采工作面采空区自然发火存在较大风险，同时提出了防范措施，为减少综放工作面采空区漏风、防止自然发火的发生提供了参考。     

Protein quality and antioxidant properties of soymilk derived from black soybean after in vitro simulated gastrointestinal digestion

Protein quality and antioxidant properties of soymilk derived from black soybean (eight varieties) in China were analysed following in vitro simulated gastrointestinal digestion (including dialysis). Soymilk from black soybean possessed high okara weight but low yield, protein content and sensory scores. The in vitro digestibility of protein in all black soymilk samples was higher than 60%, and the Shenmu black soybean exhibited the highest digestibility. Non-digested milk from the black soybean exhibited significantly high total phenolic content (TPC) (127.15–173.04 mg/100 mL), ferric-reducing antioxidant power (FRAP) (272.18–366.27 μmol L⁻¹) and DPPH free radical-scavenging activity (61.20–83.81%). These parameters were significantly lower in the non-digested soymilk than those in soymilk after gastric digestion but higher than those of soymilk in the dialysed fraction. Gastric digestion significantly increased bioactive compound levels released from black soymilk, and the bioaccessibility of phenolic compounds was 24.37–36.05%. Hence, black soymilk was sufficiently available for human absorption.     

基于多变量时间序列及向量自回归机器学习模型的水驱油藏产量预测方法

提出了一种基于多变量时间序列(MTS)及向量自回归(VAR)机器学习模型的水驱油藏产量预测方法,并进行了实例应用。该方法在井网分析的基础上通过MTS分析对注采井组数据进行优选,并将井组内不同采出井产油量及注入井注水量作为彼此相关的时间序列,通过建立VAR模型从多个时间序列中提取出相互作用规律,挖掘注采井间流量的依赖关系从而进行产量预测。水驱油藏历史生产数据分析结果表明,与数值模拟历史拟合结果相比,机器学习模型产量预测结果具有更高精度,同时不确定性分析提升了预测结果的安全性。通过脉冲响应分析对注入井的采油贡献量进行评价,可为注水开发方案调整提供理论指导。     

A General Strategy for Antimony-Based Alloy Nanocomposite Embedded in Swiss-Cheese-Like Nitrogen-Doped Porous Carbon for Energy Storage

Due to its suitable working voltage and high theoretical storage capacity, antimony is considered a promising negative electrode material for lithium-ion batteries (LIBs) and has attracted widespread attention. The volume effect during cycling, however, will cause the antimony anode to undergo a severe structural collapse and a rapid decrease in capacity. Here, a general in situ self-template-assisted strategy is proposed for the rational design and preparation of a series of M Sb (M = Ni, Co, or Fe) nanocomposites with M N C coordination, which are firmly anchored on Swiss-cheese-like nitrogen-doped porous carbon as anodes for LIBs. The large interface pore network structure, the introduction of heteroatoms, and the formation of strong metal N C bonds effectively enhance their electronic conductivity and structural integrity, and provide abundant interfacial lithium storage. The experimental results have proved the high rate performance and excellent cycling stability of antimony-based composite materials. Electrochemical kinetics studies have demonstrated that the increase in capacity during cycling is mainly controlled by the diffusion mechanism rather than the pseudocapacitance contribution. This facile strategy can provide a new pathway for low-cost and high-yield synthesis of Sb-based composites with high performance, and is expected to be applied in other energy-related fields such as sodium-/potassium-ion batteries or electrocatalysis.     

Production of the Carboxylate Reductase from Nocardia otitidiscaviarum in a Soluble,Active Form for in vitro Applications

Accessing aldehydes from carboxylate moieties is often a challenging task. In this regard, carboxylate reductases (CARs) are promising catalysts provided by nature that are able to accomplish this task in just one step, avoiding over-reduction to the alcohol product. However, the heterologous expression of CARs can be quite difficult due to the excessive formation of insoluble protein, thus hindering further characterization and application of the enzyme. Here, the heterologous production of the carboxylate reductase from Nocardia otitidiscaviarum (NoCAR) was optimized by a combination of i) optimized cultivation conditions, ii) post-translational modification with a phosphopantetheinyl transferase and iii) selection of an appropriate expression strain. Especially, the selection of Escherichia coli tuner cells as host had a strong effect on the final 110-fold increase in the specific activity of NoCAR. This highly active NoCAR was used to reduce sodium benzoate to benzaldehyde, and it was successfully assembled with an in vitro regeneration of ATP and NADPH, being capable of reducing about 30 mM sodium benzoate with high selectivity in only 2 h of reaction.