Intelligent and Autonomous Flight Technology for Launch Vehicles

This paper proposes the architecture of an intelligent flight launcher system as well as fundamental solutions to capability prediction and dynamic planning. This effort reflects the latest progress in the applications of intelligent and autonomous technology for launcher flights. The paper first describes the characteristics and capabilities of intelligent and autonomous systems and classifies various related technologies. In the context of intelligent and autonomous technology in aerospace engineering, it then focuses on technical difficulties involved with intelligent flight and reviews developments in the field. An E^3 classification model of an intelligent flight launcher is then proposed and its application scenarios are discussed. Based on an intelligent flight system configuration of the launcher, the online trajectory planning and initial value guess are examined, and vertical landing is provided as an example to explain the effects of the implementation of computational intelligence to flight systems.

Concept of Intelligent Mechanical Design for Autonomous Mobile Robots

The concept of Intelligent Mechanical Design （IMD） is presented to show how a mechanical structure can be designed to affect robot controllability, simplification and task performance. Exploring this concept produces landmarks in the territory of mechanical robot design in the form of seven design principles. The design principles, which we call the Mecha-Telligence Principles （MTP）, provide guidance on how to design mechanics for autonomous mobile robots. These principles guide us to ask the right questions when investigating issues concerning self-controllable, reliable, feasible, and compatible mechanics for autonomous mobile robots. To show how MTP can be applied in the design process we propose a novel methodology, named as Mecha-Telligence Methodology （MTM）. Mechanical design by the proposed methodology is based on preference classification of the robot specification described by interaction of the robot with its environment and the physical parameters of the robot mechatronics. After defining new terms, we investigate the feasibility of the proposed methodology to the mechanical design of an autonomous mobile sewer inspection robot. In this industrial project we show how a passive-active intelligent moving mechanism can be designed using the MTM and employed in the field.

A New Generation of Rules-based Approach:Mivar-based Intelligent Planning of Robot Actions(MIPRA)and Brains for Autonomous Robots

To create autonomous robots,both hardware and software are needed.If enormous progress has already been made in the field of equipment,then robot software depends on the development of artificial intelligence.This article proposes a solution for creating“logical”brains for autonomous robots,namely,an approach for creating an intelligent robot action planner based on Mivar expert systems.The application of this approach provides opportunities to reduce the computational complexity of solving planning problems and the requirements for the computational characteristics of hardware platforms on which intelligent planning systems are deployed.To theoretically and practically justify the expediency of using logically solving systems,in particular Mivar expert systems,to create intelligent planners,the MIPRA(Mivar-based Intelligent Planning of Robot Actions)planner was created to solve problems such as STRIPS for permutation cubes in the Blocks World domain.The planner is based on the platform for creating expert systems of the Razumator.As a result,the Mivar planner can process information about the state of the subject area based on the analysis of cause-effect relationships and an algorithm for automatically constructing logical inference(finding a solution from“Given”to“Find”).Moreover,an important feature of the MIPRA is that the system is built on the principles of a“white box”,due to which the system can explain any of its decisions and provide justification for the actions performed in the form of a retrospective of the stages of the decision-making process.When preparing a set of robot actions aimed at changing control objects,expert knowledge is used,which is the basis for the functioning algorithms of the planner.This approach makes it possible to include an expert in the process of organizing the work of the intelligent planner and use existing knowledge about the subject area.Practical experiments of this study have shown that instead of many hours and powerful multiprocessor servers,the MIPRA on a personal computer solves the planning problems with the following number of cubes:10 cubes can be rearranged in 0.028 seconds,100 cubes in 0.938 seconds,and 1000 cubes in 84.188 seconds.The results of this study can be used to reduce the computational complexity of solving tasks of planning the actions of robots,as well as their groups,multilevel heterogeneous robotic systems,and cyber-physical systems of various bases and purposes.

Car-following strategy of intelligent connected vehicle using extended disturbance observer adjusted by reinforcement learning

Disturbance observer-based control method has achieved good results in the carfollowing scenario of intelligent and connected vehicle(ICV).However,the gain of conventional extended disturbance observer(EDO)-based control method is usually set manually rather than adjusted adaptively according to real time traffic conditions,thus declining the car-following performance.To solve this problem,a car-following strategy of ICV using EDO adjusted by reinforcement learning is proposed.Different from the conventional method,the gain of proposed strategy can be adjusted by reinforcement learning to improve its estimation accuracy.Since the“equivalent disturbance”can be compensated by EDO to a great extent,the disturbance rejection ability of the carfollowing method will be improved significantly.Both Lyapunov approach and numerical simulations are carried out to verify the effectiveness of the proposed method.

Energy-efficient joint UAV secure communication and 3D trajectory optimization assisted by reconfigurable intelligent surfaces in the presence of eavesdroppers

We consider a scenario where an unmanned aerial vehicle(UAV),a typical unmanned aerial system(UAS),transmits confidential data to a moving ground target in the presence of multiple eavesdroppers.Multiple friendly reconfigurable intelligent surfaces(RISs) help to secure the UAV-target communication and improve the energy efficiency of the UAV.We formulate an optimization problem to minimize the energy consumption of the UAV,subject to the mobility constraint of the UAV and that the achievable secrecy rate at the target is over a given threshold.We present an online planning method following the framework of model predictive control(MPC) to jointly optimize the motion of the UAV and the configurations of the RISs.The effectiveness of the proposed method is validated via computer simulations.

基于智能CTC的智慧客运枢纽站方案及应用

铁路客运枢纽站因作业组织复杂、系统间联动性不足及智能化程度低等,面临作业效率不高、应急响应时间长等问题。运用北斗、5G、GIS、数字孪生等先进技术,以智能CTC3.0为基础,构建“智能CTC3.0平台、综合共享平台、5G+北斗应用平台”三大平台,通过三大平台完成行车指挥、设备监控、作业管控、旅客司乘、地理信息等重要数据的有机融合和安全运用,实现行车组织、调机作业、客运作业、运维施工、应急处置5类业务的智能化升级。以白云站枢纽工程为契机,建设“三个平台、五个智能化”架构的智慧车站,有效提升了客运枢纽站的运营效率和安全管控能力,可为其他客运枢纽站智慧化建设提供参考。

A Survey on an Emerging Safety Challenge for Autonomous Vehicles:Safety of the Intended Functionality

As the complexity of autonomous vehicles(AVs)continues to increase and artificial intelligence algorithms are becoming increasingly ubiquitous,a novel safety concern known as the safety of the intended functionality(SOTIF)has emerged,presenting significant challenges to the widespread deployment of AVs.SOTIF focuses on issues arising from the functional insufficiencies of the AVs’intended functionality or its implementation,apart from conventional safety considerations.From the systems engineering standpoint,this study offers a comprehensive exploration of the SOTIF landscape by reviewing academic research,practical activities,challenges,and perspectives across the development,verification,validation,and operation phases.Academic research encompasses system-level SOTIF studies and algorithm-related SOTIF issues and solutions.Moreover,it encapsulates practical SOTIF activities undertaken by corporations,government entities,and academic institutions spanning international and Chinese contexts,focusing on the overarching methodologies and practices in different phases.Finally,the paper presents future challenges and outlook pertaining to the development,verification,validation,and operation phases,motivating stakeholders to address the remaining obstacles and challenges.

高速铁路智能CTC多区段列车运行协同调整方法研究

为破解调度集中系统(CTC)在多区段调整方面的技术瓶颈,支撑智能高铁2.0时代多线成网运营的智能化行车调度运用场景,梳理并分析现阶段CTC智能调整方面的研究成果及问题,明确了调度管理边界及CTC系统边界将长期存在的客观性,从模型构建、动态协同联盟定界机制、求解算法等方面对多区段调整方法进行探讨。立足于CTC系统现状及规划实施的智能化技术路线,从多区段调整业务主体、信息存储、相关信息综合利用技术、动态信道分配等方面,分析CTC承载多区段调整业务的可行性及技术研究路线。分析研究结果表明:基于智能CTC的多区段列车运行协同调整方法研究具有较强的可行性和紧迫性。分析过程及相关结论对大范围智能行车调度的深入研究具有参考价值。

Deep Learning Based Autonomous Transport System for Secure Vehicle and Cargo Matching

The latest 6G improvements secured autonomous driving's realism in Intelligent Autonomous Transport Systems(IATS).Despite the IATS's benefits,security remains a significant challenge.Blockchain technology has grown in popularity as a means of implementing safe,dependable,and decentralised independent IATS systems,allowing for more utilisation of legacy IATS infrastructures and resources,which is especially advantageous for crowdsourcing technologies.Blockchain technology can be used to address security concerns in the IATS and to aid in logistics development.In light of the inadequacy of reliance and inattention to rights created by centralised and conventional logistics systems,this paper discusses the creation of a blockchain-based IATS powered by deep learning for secure cargo and vehicle matching(BDL-IATS).The BDL-IATS approach utilises Ethereum as the primary blockchain for storing private data such as order and shipment details.Additionally,the deep belief network(DBN)model is used to select suitable vehicles and goods for transportation.Additionally,the chaotic krill herd technique is used to tune the DBN model’s hyper-parameters.The performance of the BDL-IATS technique is validated,and the findings are inspected under a variety of conditions.The simulationfindings indicated that the BDL-IATS strategy outperformed recent state-of-the-art approaches.

AI Safety Approach for Minimizing Collisions in Autonomous Navigation

Autonomous agents can explore the environment around them when equipped with advanced hardware and software systems that help intelligent agents minimize collisions.These systems are developed under the term Artificial Intelligence(AI)safety.AI safety is essential to provide reliable service to consumers in various fields such asmilitary,education,healthcare,and automotive.This paper presents the design of an AI safety algorithmfor safe autonomous navigation using Reinforcement Learning(RL).Machine Learning Agents Toolkit(ML-Agents)was used to train the agentwith a proximal policy optimizer algorithmwith an intrinsic curiositymodule(PPO+ICM).This training aims to improve AI safety and minimize or prevent any mistakes that can cause dangerous collisions by the intelligent agent.Four experiments have been executed to validate the results of our research.The designed algorithmwas tested in a virtual environment with four differentmodels.A comparison was presented in four cases to identify the best-performing model for improvingAI safety.The designed algorithmenabled the intelligent agent to perform the required task safely using RL.A goal collision ratio of 64%was achieved,and the collision incidents were minimized from 134 to 52 in the virtual environment within 30min.

CTCS-3级列控系统无线超时智能分析系统研究

研究CTCS-3级列控系统无线超时智能分析技术,并基于专家系统技术设计无线超时智能分析系统。一方面,通过将知识库分组保证对数据完整性不同的无线超时事件分析的准确性。另一方面,通过在推理机中采用优化的模式匹配算法保证分析效率。本系统能够满足无线超时分析对准确性和时效性的要求。

调度集中(CTC)系统安全防护体系与技术

调度集中(CTC)系统在铁路运输安全保障方面发挥了重要作用,以CTC调度仿真实训系统、CTC生产系统、CTC行车作业检索分析系统为核心,构建行车指挥的事前预防、事中防护、事后分析的全过程闭环安全保障体系,对相关系统采用的具体防护技术进行阐述;提出发展CTC系统智能化技术,通过构建CTC大数据平台,扩大信息共享及融合,在安全卡控作业项点的广度和深度上进一步提升CTC系统的安全保障水平。

基于自主化电台的CTCS-3级列控系统无线通信超时分析

CTCS-3级列控系统车载设备中的电台是实现车地之间双向通信的核心模块,目前多为国外厂商产品,存在维护管理功能接口不开放、售后服务质量不高等问题。针对CTCS-3级列控系统中由干扰导致的单电台、网络单通等引起的无线通信超时问题,利用自主化电台强大的日志记录功能,精确定位故障原因,可为同类故障分析提供思路。

Current trends in the development of intelligent unmanned autonomous systems

Intelligent unmanned autonomous systems are some of the most important applications of artificial intelligence （AI）. The development of such systems can significantly promote innovation in AI technologies. This paper introduces the trends in the development of intelligent unmanned autonomous systems by summarizing the main achievements in each technological platform. Furthermore, we classify the relevant technologies into seven areas, including AI technologies, unmanned vehicles, unmanned aerial vehicles, service robots, space robots, marine robots, and unmanned workshops/intelligent plants. Current trends and de- velopments in each area are introduced.

Autonomous vehicles: challenges, opportunities, and future implications for transportation policies

This study investigates the challenges and opportunities pertaining to transportation policies that may arise as a result of emerging autonomous vehicle （AV） technologies. AV technologies can decrease the transportation cost and increase accessibility to low-income households and persons with mobility issues. This emerging technology also has far-reaching applications and implications beyond all current expectations. This paper provides a comprehensive review of the relevant literature and explores a broad spectrum of issues from safety to machine ethics. An indispensable part of a prospective AV development is communication over cars and infrastructure （connected vehicles）. A major knowledge gap exists in AV technology with respect to routing behaviors. Connected- vehicle technology provides a great opportunity to imple- ment an efficient and intelligent routing system. To this end, we propose a conceptual navigation model based on a fleet of AVs that are centrally dispatched over a network seeking system optimization literature on two fronts： （i） This study contributes to the it attempts to shed light on future opportunities as well as possible hurdles associated with AV technology; and （ii） it conceptualizes a navigation model for the AV which leads to highly efficient traffic circulations.

Autonomous parking control for intelligent vehicles based on a novel algorithm

Along with the increasing number of vehicles, parking space becomes narrow gradually, safety parking puts forward higher requirements on the driver＇s driving technology. How to safely, quickly and accurately park the vehiclo to parking space right？ This paper presents an automatic parking scheme based on trajectory planning, which analyzing the mechanical model oftbe vehicle, establishing vehicle steering model and parking model, coming to the conclusion that it is the turning radius is independent of the vehicle speed at low speed. The Matlab simulation environment verifies the correctness and effectiveness of the proposed algorithm for parking. A class of the automatic parking problem of intelligent vehicles is solved.

TDCS系统与新一代CTC系统二合一仿真系统设计

针对我国铁路第6次大提速,提出了TDCS与新一代CTC结合的二合一仿真系统。根据新一代调度集中与TDCS系统的设计原则,设计出该系统的硬件系统结构和软件系统容错结构,并对其做了详细分析,为我国铁路行车指挥系统升级改造提供参考。

Towards a Theoretical Framework of Autonomous Systems Underpinned by Intelligence and Systems Sciences

Autonomous systems are an emerging AI technology functioning without human intervention underpinned by the latest advances in intelligence,cognition,computer,and systems sciences.This paper explores the intelligent and mathematical foundations of autonomous systems.It focuses on structural and behavioral properties that constitute the intelligent power of autonomous systems.It explains how system intelligence aggregates from reflexive,imperative,adaptive intelligence to autonomous and cognitive intelligence.A hierarchical intelligence model(HIM)is introduced to elaborate the evolution of human and system intelligence as an inductive process.The properties of system autonomy are formally analyzed towards a wide range of applications in computational intelligence and systems engineering.Emerging paradigms of autonomous systems including brain-inspired systems,cognitive robots,and autonomous knowledge learning systems are described.Advances in autonomous systems will pave a way towards highly intelligent machines for augmenting human capabilities.

Intelligent Mining Technology for an Underground Metal Mine Based on Unmanned Equipment

This article analyzes the current research status and development trend of intelligent technologies for underground metal mines in China, where such technologies are under development for use to develop mineral resources in a safe, efficient, and environmentally friendly manner. We analyze and summarize the research status of underground metal mining technology at home and abroad, including some specific examples of equipment, technology, and applications. We introduce the latest equipment and technolo- gies with independent intellectual property rights for unmanned mining, including intelligent and unmanned control technologies for rock-drilling jumbos, down-the-hole （DTH） drills, underground scrapers, underground mining trucks, and underground charging vehicles. Three basic platforms are used for intelligent and unmanned mining： the positioning and navigation platform, information-acquisition and communication platform, and scheduling and control platform. Unmanned equipment was tested in the Fankou Lead-Zinc Mine in China, and industrial tests on the basic platforms of intelligent and unmanned mining were carried out in the mine. The experiment focused on the intelligent scraper, which can achieve autonomous intelligent driving by relying on a wireless communication system, location and navigation system, and data-acquisition system. These industrial experiments indicate that the technol- ogy is feasible. The results show that unmanned mining can promote mining technology in China to an intelligent level and can enhance the core competitive ability of China＇s mining industry.

Expert S-surface control for autonomous underwater vehicles

S-surface control has proven to be an effective means for motion control of underwater autonomous vehicles(AUV).However there are still problems maintaining steady precision of course due to the constant need to adjust parameters,especially where there are disturbing currents.Thus an intelligent integral was introduced to improve precision.An expert S-surface control was developed to tune the parameters on-line,based on the expert system,it provides S-surface control according to practical experience and control knowledge.To prevent control output over-compensation,a fuzzy neural network was included to adjust the production rules to the knowledge base.Experiments were conducted on an AUV simulation platform,and the results show that the expert S-surface controller performs better than an S-surface controller in environments with currents,producing good steady precision of course in a robust way.