Adaptive Environment Modeling Based Reinforcement Learning for Collision Avoidance in Complex Scenes

The major challenges of collision avoidance for robot navigation in crowded scenes lie in accurate environment modeling, fast perceptions, and trustworthy motion planning policies. This paper presents a novel adaptive environment model based collision avoidance reinforcement learning (i.e., AEMCARL) framework for an unmanned robot to achieve collision-free motions in challenging navigation scenarios. The novelty of this work is threefold: (1) developing a hierarchical network of gated-recurrent-unit (GRU) for environment modeling; (2) developing an adaptive perception mechanism with an attention module; (3) developing an adaptive reward function for the reinforcement learning (RL) framework to jointly train the environment model, perception function and motion planning policy. The proposed method is tested with the Gym-Gazebo simulator and a group of robots (Husky and Turtlebot) under various crowded scenes. Both simulation and experimental results have demonstrated the superior performance of the proposed method over baseline methods.Comment: accepted by IROS202

Understanding Transport of an Elastic, Spherical Particle through a Confining Channel

The transport of soft particles through narrow channels or pores is ubiquitous in biological systems and industrial processes. On many occasions, the particles deform and temporarily block the channel, inducing a built-up pressure. This pressure buildup often has a profound effect on the behavior of the respective system; yet, it is difficult to be characterized. In this work, we establish a quantitative correlation between the built-up pressure and the material and geometry properties through experiments and mechanics analysis. We fabricate microgels with a controlled diameter and elastic modulus by microfluidics. We then force them to individually pass through a constrictive or straight confining channel and monitor the pressure variation across the channel. To interpret the pressure measurement, we develop an analytical model based on the Neo-Hookean material law to quantify the dependence of the maximum built-up pressure on the radius ratio of the elastic sphere to the channel, the elastic modulus of the sphere, and two constant parameters in the friction constitutive law between the sphere and the channel wall. This model not only agrees very well with the experimental measurement conducted at large microgel deformation but also recovers the classical theory of contact at small deformation. Featuring a balance between accuracy and simplicity, our result could shed light on understanding various biological and engineering processes involving the passage of elastic particles through narrow channels or pores

Spatial and temporal distribution characteristics and prediction analysis of nitrogen and phosphorus surface source pollution in Shandong Province under the climate and land use changes

The aim of this study was to explore the characteristics of non-point source pollution of nitrogen (N) and phosphorus (P) under the background of climate and land use in Shandong Province. First, using the InVEST NDR module in the model, N and P non-point source pollution in 2010 and 2020 in Shandong Province were simulated; then, based on precipitation data under three different global climate models (MRI-ESM-0, GFDL-ESM4, and Ec-Earth3) and two Shared Socioeconomic Pathways (SSP245 and SSP585), land use data under two Shared Socioeconomic Pathways (SSP245 and SSP585) were used to simulate and predict the non-point source pollution of N and P in Shandong Province in 2030. The results showed the following: (1) On the time scale, the output load and total output of N and P decreased during 2010–2020, while the output load and total output of N and P increased during 2020–2030. (2) On the spatial scale, the spatial distribution of N and P output loads in 2010, 2020, and 2030 is roughly the same, being “low in the northwest and high in the southeast”. (3) Different climate scenarios have a great influence on N and P output load and total output, and the N and P pollution in the SSP585 scenario is more serious. The total output of N and P did not change much in different climate models, while the spatial distribution of the output load of N and P varied significantly, indicating that different climate models had a greater impact on the spatial distribution of the output load of N and P. (4) The overall cold hot spot pattern of nitrogen and phosphorus pollution in Shandong Province is stable, basically showing a “band + cluster + scatter” distribution pattern; the hot spot area in the central and southern region of Shandong Province changes little regardless of the model, the northwest is basically a cold spot area, and the nitrogen and phosphorus hot spot area under the SSP245 scenario in Ec-Earth3 model had the least amount of change. According to research results, combined with the actual situation of Shandong Province, it is hoped that it can provide theoretical basis for the prevention and control of non-point source pollution in Shandong Province in the future

Confined FeNi alloy nanoparticles in carbon nanotubes for photothermal oxidative dehydrogenation of ethane by carbon dioxide

Oxidative dehydrogenation of ethane with CO2 (ODEC) is an attractive reaction for reduction of carbon footprints and ethene production. In this work, we present photothermal catalysis on confined bimetal catalysts for ODEC. Carbon nanotubes confined non-noble bimetal alloy (i.e., CoNi@CNTs and FeNi@CNTs) catalysts were prepared and FeNi@CNTs showed effective performance in photothermal catalytic ODEC to ethene. Experiments and simulations reveal that UV and visible lights (420 – 490 nm) are responsible for ODEC and non-oxidative dehydrogenation of ethane, respectively, to ethene. Additionally, ODEC to ethene is preferred to C-C cracking to methane on FeNi@CNTs in light ( \u3e 490 nm)-induced thermocatalysis. The photothermal effect turns more significant when introduced into thermocatalytic ODEC (500 °C), with ethene generation at one order of magnitude. This work advances new mechanism of photo-mediated catalysis and sheds light on utilization of full-spectrum solar energy and non-noble metallic catalysts for ethene production and CO2 recycling at moderate conditions

16S Next-generation sequencing and quantitative PCR reveal the distribution of potential pathogens in the Liaohe Estuary

The existence of potentially pathogenic bacteria seriously threatens aquatic animals and human health. Estuaries are closely related to human activities, and the detection of pathogens is important for aquaculture and public health. However, monitoring only indicator microorganisms and pathogens is not enough to accurately and comprehensively estimate water pollution. Here, the diversity of potentially pathogenic bacteria in water samples from the Liaohe estuary was profiled using 16S next-generation sequencing (16S NGS) and quantitative polymerase chain reaction (qPCR) analysis. The results showed that the dominant genera of environmental pathogens were Pseudomonas, Vibrio, Mycobacterium, Acinetobacter, Exiguobacterium, Sphingomonas, and Legionella, and the abundance of enteric pathogens was significantly less than the environmental pathogens, mainly, Citrobacter, Enterococcus, Escherichia-Shigella, Enterobacter, Bacteroides. The qPCR results showed that the 16S rRNA genes of Vibrio were the most abundant, with concentrations between 7.06 and 9.48 lg copies/L, followed by oaa gene, fliC gene, trh gene, and uidA gene, and the temperature and salinity were the main factors affecting its abundance. Variance partitioning analysis (VPA) analysis of spatial factors on the potential pathogen’s distribution (19.6% vs 5.3%) was greater than environmental factors. In addition, the co-occurrence analysis of potential pathogens in the estuary revealed significant co-occurrence among the opportunistic pathogens Testosteronemonas, Brevimonas vesicularis, and Pseudomonas putida. Our findings provide an essential reference for monitoring and occurrence of potentially pathogenic bacteria in estuaries

Fundamentals of Microgel Flooding and Nanoparticles-Stabilized Foams in Enhanced Oil Recovery

For centuries oil has remained a critical energy source for human civilization. After years of extraction, many oil fields have reached or are reaching a decline stage of production, even though up to a half of the total crude oil reserves in these fields has not been recovered yet. One reason is due to the structural heterogeneity of the oil reservoirs—reservoirs may consist of regions of higher permeability with larger pore size and regions of lower permeability with smaller pore size. Displacing fluids tend to flow through large permeability zones only without reaching the oil trapped in low permeability region; this poor sweep efficiency results in low oil recovery rate and excessive water production. Among various enhanced oil recovery (EOR) technologies, preformed particle gel (PPG) treatment and foam flooding are commonly used and can both effectively improve the sweep efficiency. The performance of these EOR technologies depends on a number of geometrical, materials, and flow properties that can be measured or controlled. However, the relation between the large-scale performance and the controllable or measurable quantities remains poorly understood. Another challenge to be addressed in EOR foam flooding is implementing long-term stability of the foams against coarsening and coalescence. This dissertation addresses these critical issues in PPG treatment and foam flooding from two aspects. First, we investigate the transport of soft spherical particles through porous media at both pore scale and macroscale and develop a generalized capillary bundle model to quantitatively correlate the overall pressure drop and permeability reduction with the concentration and mechanical property of microgels, the size ratio of microgel to pore throat, and the flux. Second, we produce monodisperse nanoparticles-stabilized foams and characterize their morphology, stability, and rheology; these foams exhibit long-term stability and much higher storage and viscous moduli than surfactant-stabilized foams. Besides the application in EOR, this work can also potentially benefit other processes and industries such as particle transport in soils or aquifers, food, cleaning, and personal care products