Dynamic Obstacle Avoidance for Application of Human-Robot Cooperative Dispensing Medicines

For safety reasons,in the automated dispensing medicines process,robots and humans cooperate to accomplish the task of drug sorting and distribution.In this dynamic unstructured environment,such as a human-robot collaboration scenario,the safety of human,robot,and equipment in the environment is paramount.In this work,a practical and effective robot motion planning method is proposed for dynamic unstructured environments.To figure out the problems of blind zones of single depth sensor and dynamic obstacle avoidance,we first propose a method for establishing offline mapping and online fusion of multi-sensor depth images and 3D grids of the robot workspace,which is used to determine the occupation states of the 3D grids occluded by robots and obstacles and to conduct real-time estimation of the minimum distance between the robot and obstacles.Then,based on the reactive control method,the attractive and repulsive forces are calculated and transformed into robot joint velocities to avoid obstacles in real time.Finally,the robot's dynamic obstacle avoidance ability is evaluated on an experimental platform with a UR5 robot and two KinectV2 RGB-D sensors,and the effectiveness of the proposed method is verified.     

考虑交通小区相关性的小汽车拥有行为研究

为分析建成环境对家庭小汽车拥有的影响，考虑交通小区间的空间相关性，分别基于0-1 邻接矩阵、共同边界邻接矩阵及质心空间距离矩阵构建了层次Bayesian 模型，并与不考虑空间相关性的模型结果进行了对比.基于长春居民出行调查数据对模型参数进行估计，结果表明：交通小区间的空间相关性显著存在；以不考虑空间相关性的模型作为对比，基于公共边界邻接矩阵的层次Bayesian 模型拟合效果最优；在控制家庭层面社会经济变量后，居住密度、土地利用混合度、交叉口密度及公共交通站点密度均对家庭小汽车拥有具有显著的负向效应，表明通过优化城市建成环境策略可有效抑制小汽车拥有量的增长.     

基于网络的高职英语自主学习多模态环境构建

本文探讨了在网络技术不断发展的背景下,如何建立网络的多模态环境,从多个方面给予高职学生不同的学习体验,以提高高职英语自主学习的效果,最后提出了一种基于网络多模态英语自主学习模型。     

基于环境的道路交通安全分析

介绍了道路交通安全环境的涵义,分析了道路交通安全环境中的软环境和硬环境,提出了改善我国道路交通安全环境的相关措施。     

SBR法在天津港污水处理中心化学污水处理工程中的应用

介绍天津港化学污水处理工程的污水水源、水质及为实现处理方案而作的试验室试验情况，最后采用SBR法处理化学污水，主要指标达到国家三废排放标准。     

Environmental invitingness for transport-related cycling in middle-aged adults: A proof of concept study using photographs

IntroductionCurrent evidence on associations between modifiable environmental characteristics and transport-related cycling remains inconsistent. Most studies on these associations used questionnaires to determine environmental perceptions, but such tools may be subject to bias due to unreliable recall. Moreover, questionnaires only measure separate environmental characteristics, while real environments are a combination of different characteristics. To overcome these limitations, the present proof of concept study used panoramic photographs of cycling environments to capture direct responses to the physical environment. We examined which depicted environmental characteristics were associated to environments’ invitingness for transportation cycling. Furthermore, interactions with gender and participants’ cycling behavior were examined.MethodsFifty-nine middle-aged adults were recruited through purposeful convenience sampling. During a home visit, participants took part in a structured interview assessing demographics and PA during the preceding seven days, followed by an intuitive choice task and a (cognitive) rating task, which both measured 40 photographed environments’ invitingness to cycle along. Multi-level cross-classified analyses were conducted using MLwiN 2.26.ResultsBoth tasks’ multivariate results showed that presence of vegetation was identified as the most important environmental characteristic to invite people for engaging in transportation cycling, even when the amount of vegetation was relatively small. In the bivariate analyzes, some differences between results of the cognitive rating task and the intuitive choice task were found, showing that invitingness measured by the rating task was associated with environmental maintenance and cycling infrastructure, whereas invitingness determined by the choice task was associated with more traffic-oriented characteristics. Moreover, only for the choice task’s results, moderating effects of gender and participants’ cycling behavior in the preceding week were observed.ConclusionThe present study provides proof of concept that capturing people’s less cognitive, more intuitive responses to an environment’s invitingness for transport-related cycling may be important for revealing environment-behavior associations. If replicated in future studies using larger samples, results of our innovative measurements with photographs, especially those on vegetation, can complete the existing knowledge on which environmental characteristics are important for transportation cycling in adults and could form a basis to inform health promoters and local policy makers. However, future studies replicating our study method in larger samples and other population subgroups are highly encouraged. Moreover, causal relationships should be explored.     

Dynamic diurnal social taxonomy of urban environments using data from a geocoded time use activity-travel diary and point-based business establishment inventory

In this paper, we explore the diurnal dynamics of joint activity participation in a small city in Pennsylvania, USA, using behavioral data and an inventory of business establishments. We account for the variation caused by the collective impact of social, temporal and spatial choices of individuals to produce predicted space–time visualizations of activity participation. The focus is on how social contexts of an activity impact the temporal and spatial decisions regarding the activity locations and how this impact varies depending on activity types. A comparison across activity types and social interaction types is made among spatial patterns during a day. The CentreSIM dataset, which is a household-based activity diary survey collected in Centre County (Pennsylvania, USA) in 2003, provides very detailed social interaction information enabling the analysis of social, spatial and temporal aspects of activity participation. In this paper we use this information to develop a spatio-temporal interpolation method and demonstration based on kriging. In this way, we extract the dynamic social taxonomy of places from the behavioral information in the dataset and suggest how urban and transportation models can be informed from the dynamics of places by observing “what is taking place” (activities being pursued in the context of this paper) combined with “what exists” (business establishments) or “what is available” (businesses that are open). The method here can also be used to improve the design of urban environments (e.g., filling gaps in desired activity locations), manage specific places (e.g., extending the opening and closing times of businesses), study transportation policies that are sensitive to time of day (e.g., pricing of parking to discourage crowding and traffic congestion), and modeling of spatio-temporal decisions of social activities in travel demand models (e.g., to guide the development of model specification and representation of the space in which behavioral models are applied).     

Smarter and more connected: Future intelligent transportation system

Emerging technologies toward a connected vehicle-infrastructure-pedestrian environment and big data have made it easier and cheaper to collect, store, analyze, use, and disseminate multi-source data. The connected environment also introduces new approaches to flexible control and management of transportation systems in real time to improve overall system performance. Given the benefits of a connected environment, it is crucial that we understand how the current intelligent transportation system could be adapted to the connected environment.     

张力腿平台的环境荷载及响应

通过对张力腿平台的资料分析和案例模拟研究，概括了张力腿平台的环境荷载，探讨了平均环境荷载、波频荷载、低频荷载和高频荷载对张力腿平台运动的影响，分析了张力腿平台的运动特点，介绍了环境荷载与平台响应计算中所涉及到的关键因素以及世界上通用的设计规范，提出了开展我国深水海域开发研究的建议。     

Gas transfer velocities of CO2 and CH4 in a tropical reservoir and its river downstream

We have measured simultaneously the methane (CH₄) and carbon dioxide (CO₂) surface concentrations and water–air fluxes by floating chambers (FC) in the Petit-Saut Reservoir (French Guiana) and its tidal river (Sinnamary River) downstream of the dam, during the two field experiments in wet (May 2003) and dry season (December 2003). The eddy covariance (EC) technique was also used for CO₂ fluxes on the lake. The comparison of fluxes obtained by FC and EC showed little discrepancies mainly due to differences in measurements durations which resulted in different average wind speeds. When comparing the gas transfer velocity (k₆₀₀) for a given wind speed, both methods gave similar results. On the lake and excluding rainy events, we obtained an exponential relationship between k₆₀₀ and U₁₀, with a significant intercept at 1.7 cm h^− 1, probably due to thermal effects. Gas transfer velocity was also positively related to rainfall rates reaching 26.5 cm h⁻¹ for a rainfall rate of 36 mm h^− 1. During a 24-h experiment in dry season, rainfall accounted for as much as 25% of the k₆₀₀. In the river downstream of the dam, k₆₀₀ values were 3 to 4 times higher than on the lake, and followed a linear relationship with U₁₀.