Inverse reinforcement learning-based time-dependent A* planner for human-aware robot navigation with local vision

In an environment where robots coexist with humans, mobile robots should be human-aware and comply with humans' behavioural norms so as to not disturb humans' personal space and activities. In this work, we propose an inverse reinforcement learning-based time-dependent A* planner for human-aware robot navigation with local vision. In this method, the planning process of time-dependent A* is regarded as a Markov decision process and the cost function of the time-dependent A* is learned using the inverse reinforcement learning via capturing humans' demonstration trajectories. With this method, a robot can plan a path that complies with humans' behaviour patterns and the robot's kinematics. When constructing feature vectors of the cost function, considering the local vision characteristics, we propose a visual coverage feature for enabling robots to learn from how humans move in a limited visual field. The effectiveness of the proposed method has been validated by experiments in real-world scenarios: using this approach robots can effectively mimic human motion patterns when avoiding pedestrians; furthermore, in a limited visual field, robots can learn to choose a path that enables them to have the larger visual coverage which shows a better navigation performance.     

Manpower supply planning for aircraft line maintenance under stochastic incidents

We plan the manpower supply for aircraft line maintenance, taking into account two types of stochastic incidents: manpower demands for a flight and the number of aircraft needing to be serviced at one time. The problem is solved to find the shift and maintenance group combinations best suited for the given airline. The optimal aircraft maintenance certification for a crew is also analyzed to improve the entire manpower structure. In addition, the addition of temporary manpower required for actual daily operations is also considered as a part of understanding the total manpower utilized in actual operations. An integrated method including scenario generation and a stochastic model is developed to deal with the problem. Finally, we perform a case study based on operating data obtained from a major airline in Taiwan. The results and findings are compared with the airline’s current manpower plan in the discussion, and suggestions for improvement are made.     

基于改进蚁群算法的三维路径规划

针对移动机器人在海水环境中的三维路径规划问题容易陷入局部最优和收敛慢等瑕疵，根据三维环境全局信息来改进蚁群算法以提高实时性和收敛速度。改进蚁群算法的启发函数，采用局部信息和全局信息结合动态地改进信息素更新方式，以及根据三维空间中路径的平坦程度和光滑度二阶微分分别增加了一阶微分和二阶微分来再次修改信息素更新规则。仿真对比实验结果显示改进后的蚁群算法克服了收敛速度慢、容易陷入局部最优的缺点。     

交互与新生——武汉大学早期校园规划思想解读

武汉大学早期校园具有较高的历史、科学、艺术和文化价值,是我国近代大学校园规划和设计的典范,然而关于其校园规划思想的研究却比较匮乏。本文根据设计师开尔斯和莱文斯比尔的设计手稿以及多种关于校园建设的原始文字档案,从时代背景、建校理念用地环境三个方面分析影响早期校园规划和建筑形制形成的因素。旨在全球视阈下解读武汉大学早期校园规划思想,凸显出武汉大学校园规划及建设的全球关联性。     

功能性小麦品种的概念、类别和发展前景（网络首发、推荐阅读）

结合全球倡导的营养导向型农业和功能性食品的内容，首次提出“功能性小麦品种”的概念，将其定义为“含有对人体健康有益的活性成分，可调节人体有益代谢，能给人体健康带来某种益处或满足特定人群的特殊需求，同时可以作为日常食物的口感正常、无毒副作用的小麦品种类型”；结合疫情警示和我国进入后工业时代后，人们需求必将由“吃得饱”、“吃得好”向“吃得健康”转变，因而提出继高产品种、优质品种之后培育“功能性小麦品种”的育种目标。根据多年关于小麦淀粉、蛋白、酯类和其他成分的功能研究结果，介绍新育成的“麦黄酮”、“高色素”、“高抗性淀粉”、“富锌”、“低醇溶蛋白”和“低植酸”等功能性小麦新品种（系）的营养特性和农艺产量状况；根据“健康中国2030”规划等国家战略，进行“功能性品种培育是解决我国功能性食品‘卡脖子’的关键基础，一种功能性品种可以形成一类功能性食品，多种功能性品种可以形成我国功能性面制品产业，推动我国整个食品工业的发展”的前景展望；根据功能性品种及其食品的稳定性和可靠性是产品和市场的“生命线”，从对消费者负责的高度，提出关于“功能性农作物品种审定导向和组建功能性成分检测机构；编制有关功能性品种和食品的国家或行业标准，设立功能性食品和功能性农作物品种的商业标志，保证我国功能性农作物品种及其食品健康发展”等方面的具体建议。     

KSUTraffic: A Microscopic Traffic Simulator for Traffic Planning in Smart Cities

Simulation is a powerful tool for improving, evaluating and analyzing the performance of new and existing systems. Traffic simulators provide tools for studying transportation systems in smart cities as they describe the evolution of traffic to the highest level of detail. There are many types of traffic simulators that allow simulating traffic in modern cities. The most popular traffic simulation approach is the microscopic traffic simulation because of its ability to model traffic in a realistic manner. In many cities of Saudi Arabia, traffic management represents a major challenge as a result of expansion in traffic demands and increasing number of incidents. Unfortunately, employing simulation to provide effective traffic management for local scenarios in Saudi Arabia is limited to a number of commercial products in both public and private sectors. Commercial simulators are usually expensive, closed source and inflexible as they allow limited functionalities. In this project, we developed a local traffic simulator “KSUtraffic” for traffic modeling, planning and analysis with respect to different traffic control strategies and considerations. We modeled information specified by GIS and real traffic data. Furthermore, we designed experiments that manipulate simulation parameters and the underlying area. KSUTraffic visualizes traffic and provides statistical results on the simulated traffic which would help to improve traffic management and efficiency.     

A fast genetic algorithm for a critical protection problem in biomedical supply chain networks

In this paper, we present a new bilevel model for a biomedical supply chain network with capacity and budget constraint due to the protection and interdiction operations. The components considered in this model are biomedical devices, distribution centers (DCs), medical suppliers (MSs), and hospitals and patients as the demand points. On the other hand, two levels of decisions in the network planning is suggested: (1) the defender’s decision about protection operations of MSs and DCs, the assignment of clients to the DCs, and quantity of products shipped to DCs from MSs to minimize the demand-weighted traveling costs and transport costs and (2) the attacker’s decision about interdiction operations of MSs and DCs to maximize the capacity or service reduction and losses. Because of nondeterministic polynomial time (NP)-hardness of the problem under consideration, an efficient and fast approach based on a genetic algorithm and a fast branch and cut method (GA–FBC) was developed to solve the proposed model. Also, the efficiency via the comparison of results with the genetic algorithm based on CPLEX (GA-CPLEX) and decomposition method (DM) is investigated. In order to assess the performance of the presented GA–FBC, a set of 27 instances of the problem is used. Comprehensive analysis indicates that the proposed approach significantly solves the problem. In addition, the benefits and advantages of preference with running times and its accuracy is shown numerically. Simulation results clearly demonstrate that the defender’s objective effectively reduced and CPU time also within the large-sized instances of the problem in comparison with the GA-CPLEX and DM.     

犹豫模糊环境下准则具有偏好关系的TODIM方法

针对智慧制造评估时专家的决策信息具有犹豫模糊不确定性问题，提出了一种关于准则具有犹豫模糊偏好关系的改进交互式多准则决策（TODIM）方法。首先提出了准则间的犹豫模糊偏好关系概念，并证明了其基本性质。在TODIM方法优势度的计算过程中，将准则权重犹豫模糊偏好关系替代原有的精确值权重，使信息的准确性最大化。将该方法用于智能制造的评估上，实例分析结果表明所提方法是可行和有效的。     

Human–Cyber–Physical Systems (HCPSs) in the Context of New-Generation Intelligent Manufacturing

An intelligent manufacturing system is a composite intelligent system comprising humans, cyber systems, and physical systems with the aim of achieving specific manufacturing goals at an optimized level. This kind of intelligent system is called a human–cyber–physical system (HCPS). In terms of technology, HCPSs can both reveal technological principles and form the technological architecture for intelligent manufacturing. It can be concluded that the essence of intelligent manufacturing is to design, construct, and apply HCPSs in various cases and at different levels. With advances in information technology, intelligent manufacturing has passed through the stages of digital manufacturing and digital-networked manufacturing, and is evolving toward new-generation intelligent manufacturing (NGIM). NGIM is characterized by the in-depth integration of new-generation artificial intelligence (AI) technology (i.e., enabling technology) with advanced manufacturing technology (i.e., root technology); it is the core driving force of the new industrial revolution. In this study, the evolutionary footprint of intelligent manufacturing is reviewed from the perspective of HCPSs, and the implications, characteristics, technical frame, and key technologies of HCPSs for NGIM are then discussed in depth. Finally, an outlook of the major challenges of HCPSs for NGIM is proposed.