The investigation of an autonomous intelligent mobile robot system for indoor environment navigation

The autonomous mobile robotics system designed and implemented for indoor environment navigation is a nonholonomic differential drive system with two driving wheels mounted on the same axis driven by two PID controlled motors and two caster wheels mounted in the front and back respectively. It is furnished with multiple kinds of sensors such as IR detectors, ultrasonic sensors, laser line generators and cameras, constituting a perceiving system for exploring its surroundings. Its computation source is a simultaneously running system composed of multiprocessor with multitask and multiprocessing programming. Hybrid control architecture is employed on the mobile robot to perform complex tasks. The mobile robot system is implemented at the Center for Intelligent Design, Automation and Manufacturing of City University of Hong Kong.

Speech Recognition Technology Applied to Intelligent Mobile Navigation System

The capability of human_computer interaction reflects the intelligent degree of mobile navigation system.The navigation data and functions of mobile navigation system are divided into system commands and non_system commands in this paper.And then a group of speech commands are abstracted.This paper applies speech recognition technology to intelligent mobile navigation system to process speech commands and does some deep research on the integration of speech recognition technology with mobile navigation system.The navigation operation can be performed by speech commands,which makes human_computer interaction easy during navigation.Speech command interface of navigation system is implemented by Dutty ++ Software,which is based on speech recognition system _Via Voice of IBM.Through navigation experiments,navigation can be done almost without keyboard,which proved that human_computer interaction is very convenient by speech commands and the reliability is also higher.

Global Inverse Optimal Tracking Control of Underactuated Omni-directional Intelligent Navigators （ODINs）

This paper presents a design of optimal controllers with respect to a meaningful cost function to force an underactuated omni-directional intelligent navigator （ODIN） under unknown constant environmental loads to track a reference trajectory in two-dimensional space. Motivated by the vehicle＇s steering practice, the yaw angle regarded as a virtual control plus the surge thrust force are used to force the position of the vehicle to globally track its reference trajectory. The control design is based on several recent results developed for inverse optimal control and stability analysis of nonlinear systems, a new design of bounded disturbance observers, and backstepping and Lyapunov＇s direct methods. Both state- and output-feedback control designs are addressed. Simulations are included to illustrate the effectiveness of the proposed results.

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.

Clinical use of augmented reality,mixed reality,three-dimensionalnavigation and artificial intelligence in liver surgery

A precise knowledge of intra-parenchymal vascular and biliary architecture and the location of lesions in relation to the complex anatomy is indispensable to perform liver surgery.Therefore,virtual three-dimensional(3D)-reconstruction models from computed tomography/magnetic resonance imaging scans of the liver might be helpful for visualization.Augmented reality,mixed reality and 3Dnavigation could transfer such 3D-image data directly into the operation theater to support the surgeon.This review examines the literature about the clinical and intraoperative use of these image guidance techniques in liver surgery and provides the reader with the opportunity to learn about these techniques.Augmented reality and mixed reality have been shown to be feasible for the use in open and minimally invasive liver surgery.3D-navigation facilitated targeting of intraparenchymal lesions.The existing data is limited to small cohorts and description about technical details e.g.,accordance between the virtual 3D-model and the real liver anatomy.Randomized controlled trials regarding clinical data or oncological outcome are not available.Up to now there is no intraoperative application of artificial intelligence in liver surgery.The usability of all these sophisticated image guidance tools has still not reached the grade of immersion which would be necessary for a widespread use in the daily surgical routine.Although there are many challenges,augmented reality,mixed reality,3Dnavigation and artificial intelligence are emerging fields in hepato-biliary surgery.

A review:On path planning strategies for navigation of mobile robot

This paper presents the rigorous study of mobile robot navigation techniques used so far.The step by step investigations of classical and reactive approaches are made here to understand the development of path planning strategies in various environmental conditions and to identify research gap.The classical approaches such as cell decomposition(CD),roadmap approach(RA),artificial potential field(APF);reactive approaches such as genetic algorithm(GA),fuzzy logic(FL),neural network(NN),firefly algorithm(FA),particle swarm optimization(PSO),ant colony optimization(ACO),bacterial foraging optimization(BFO),artificial bee colony(ABC),cuckoo search(CS),shuffled frog leaping algorithm(SFLA)and other miscellaneous algorithms(OMA)are considered for study.The navigation over static and dynamic condition is analyzed(for single and multiple robot systems)and it has been observed that the reactive approaches are more robust and perform well in all terrain when compared to classical approaches.It is also observed that the reactive approaches are used to improve the performance of the classical approaches as a hybrid algorithm.Hence,reactive approaches are more popular and widely used for path planning of mobile robot.The paper concludes with tabular data and charts comparing the frequency of individual navigational strategies which can be used for specific application in robotics.

A Survey of Human-centered Intelligent Robots:Issues and Challenges

Intelligent techniques foster the dissemination of new discoveries and novel technologies that advance the ability of robots to assist and support humans. The human-centered intelligent robot has become an important research field that spans all of the robot capabilities including navigation, intelligent control, pattern recognition and human-robot interaction. This paper focuses on the recent achievements and presents a survey of existing works on human-centered robots. Furthermore, we provide a comprehensive survey of the recent development of the human-centered intelligent robot and discuss the issues and challenges in the field.

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.

E-Navigation框架下船舶智能航线服务系统设计研究

文中提出一种基于多种通信方式的船舶智能航线服务系统的设计思路,通过通航环境的大数据分析为船舶提供最优航线,在此基础上实现船与船、船与岸之间的计划/实时航线交换,并依据船舶计划航线提供相应的智能导助航信息服务。

The Development of Intelligent Operation Method of Urban Public Infrastructure Driven by Accurate Spatio-temporal Information

Urban public infrastructure is an important basis for urban development.It is of great significance to deepen the research on intelligent management and control of urban public infrastructure.Spatio-temporal information contains the law of state evolution of urban public infrastructure,which is the information base of intelligent control of infrastructure.Due to the needs of operation management and emergency response,efficient sharing and visualization of spatio-temporal information are important research contents of comprehensive management and control of urban public infrastructure.On the basis of summarizing the theoretical research and application in recent years,the basic methods and current situation of the acquisition and analysis of spatio-temporal information,the forecast and early warning,and the intelligent control of urban public infrastructure are reviewed in this paper.

Game Theory Optimization via Diverse Genetic Crossover Intelligence

Game theory is explored via a maze application where combinatorial optimization occurs with the objective of traversing through a defined maze with an aim to enhance decision support and locate the optimal travel sequence while minimizing computation time. This combinatorial optimization approach is initially demonstrated by utilizing a traditional genetic algorithm (GA), followed by the incorporation of artificial intelligence utilizing embedded rules based on domain-specific knowledge. The aim of this initiative is to compare the results of the traditional and rule-based optimization approaches with results acquired through an intelligent crossover methodology. The intelligent crossover approach encompasses a two-dimensional GA encoding where a second chromosome string is introduced within the GA, offering a sophisticated means for chromosome crossover amongst selected parents. Additionally, parent selection intelligence is incorporated where the best-traversed paths or population members are retained and utilized as potential parents to mate with parents selected within a traditional GA methodology. A further enhancement regarding the utilization of saved optimal population members as potential parents is mathematically explored within this literature.

Short-term effectiveness of intelligent navigated laser photocoagulation versus subthreshold micropulse laser in patients with chronic central serous chorioretinopathy

AIM:To compare the short-term effectiveness of intelligent navigated laser photocoagulation and 577-nm subthreshold micropulse laser(SML)treatment in patients with chronic central serous chorioretinopathy(cCSC).METHODS:This observational retrospective cohort study included 60 consecutive patients who underwent intelligent navigated laser photocoagulation(n=30)or 577-nm SML treatment(n=30)for cCSC between Jan.2021 and Oct.2022.During 3mo follow-up,all patients underwent assessments of best correct visual acuity(BCVA)and optical coherence tomography(OCT).RESULTS:The operation of laser treatment was successful in all cases.At 1mo,BCVA improved significantly more in the intelligent navigated laser photocoagulation group compared to the SML group(P<0.05).The change was not significantly different at 3mo(P>0.05).Central macular thickness(CMT)in the intelligent navigated laser photocoagulation group was lower than in the SML group at 1mo(P<0.05).The subfoveal choroidal thickness(SFCT)in two groups were all significantly improved at 3mo(all P<0.05).The change between two groups was not significantly different at 1mo or at 3mo(P>0.05).CONCLUSION:Intelligent navigated laser photocoagulation is superior to SML for treating cCSC,leading to better improvements in vision and CMT for short term.

Intelligent navigation algorithm of plant phenotype detection robot based on dynamic credibility evaluation

Due to the non-standardization and complexity of the farmland environment,Global Navigation Satellite System(GNSS)navigation signal may be affected by the tree shade,and visual navigation is susceptible to winged insect and mud,which makes the navigation information of the plant phenotype detection robot unreliable.To solve this problem,this study proposed a multi-sensor information fusion intelligent navigation algorithm based on dynamic credibility evaluation.First,three navigation methods were studied:GNSS and Inertial Navigation System(INS)deep coupling navigation,depth image-based visual navigation,and maize image sequence navigation.Then a credibility evaluation model based on a deep belief network was established,which used dynamically updated credibility to intelligently fuse navigation results to reduce data fusion errors and enhance navigation reliability.At last,the algorithm was loaded on the plant phenotype detection robot for experimental testing in the field.The result shows that the navigation error is 2.7 cm and the navigation effect of the multi-sensor information fusion method is better than that of the single navigation method in the case of multiple disturbances.The multi-sensor information fusion method proposed in this study uses the credibility model of the deep belief network to perform navigation information fusion,which can effectively solve the problem of reliable navigation of the plant phenotype detection robot in the complex environment of farmland,and has important application prospects.

Swarm intelligence based dynamic obstacle avoidance for mobile robots under unknown environment using WSN

To solve dynamic obstacle avoidance problems, a novel algorithm was put forward with the advantages of wireless sensor network (WSN). In view of moving velocity and direction of both the obstacles and robots, a mathematic model was built based on the exposure model, exposure direction and critical speeds of sensors. Ant colony optimization (ACO) algorithm based on bionic swarm intelligence was used for solution of the multi-objective optimization. Energy consumption and topology of the WSN were also discussed. A practical implementation with real WSN and real mobile robots were carried out. In environment with multiple obstacles, the convergence curve of the shortest path length shows that as iterative generation grows, the length of the shortest path decreases and finally reaches a stable and optimal value. Comparisons show that using sensor information fusion can greatly improve the accuracy in comparison with single sensor. The successful path of robots without collision validates the efficiency, stability and accuracy of the proposed algorithm, which is proved to be better than tradition genetic algorithm (GA) for dynamic obstacle avoidance in real time.

Understanding Human Body Maintenance, Protection, and Modification: Antibodies, Genetics, Stem Cells and Connected Artificial Intelligence Applications—Where Are We?

Research in antibody reaction, genetics, stem cells together with advances in imaging techniques and connected referenced-based applications led to a deeper understanding of the physiological mechanisms of functioning and fine regulation of tissue maintenance, protection, and modification in recent years. Meanwhile, the past major research milestones are up to date more than ever. The article comprehensively breaks down these scientific fields in molecular biology, describes the current knowledge, recent advancements and challenges in antibody, genetics, regulation of gene expression respectively, and stem cell research, and gives an overview of the research supporting the areas of artificial intelligence and its connected reference-based applications, which enable the handling of huge genetic and biochemical data amounts.

Relay navigation strategy study on intelligent drive on urban roads

In order to solve navigation problem of intelligent vehicle driving on urban roads and to achieve the navigation in intersection area, intersection transition area and section area. The relay navigation strategy and algorithm can solve the navigation problem of intelligent vehicle driving in typical urban roads such as intersection area, intersection transition area and section area, realizing seamless handover among different typical areas. Bezier curve function model was introduced to different typical areas, which solved the self-adaption recognition problem in different typical areas and revised positional accuracy with the help of cloud computing positioning service. In order to explain the strategy implement, an instance based on the strategy was adopted. Instance analysis indicates that as for the navigation problem in intersection area, intersection transition area and section area, if the relay navigation strategy is utilized, the self-adaption recognition problem in different typical areas can be handled. Based on the relay navigation strategy, the drive of intelligent vehicle on urban roads can effectively solve the self-adaption recognition problem in different typical areas in urban and further solve driving problems of intelligent vehicle of the same category in urban roads.

基于路径规划特点的语义目标导航方法

为了解决语义目标导航任务中存在的探索效率低、深度不精准等问题,本文构建了一个解决语义目标导航任务的框架,在语义地图构建模块中引入了深度图边缘处理以及地图纠错机制;在探索模块中引入了覆盖范围最大化算法;在路径规划模块中引入了替代点机制。本文在一个3D仿真环境下进行了实验。实验结果表明,本文提出的解决方案明显提升了语义目标导航任务的性能。此外,本文所提方法成功应用到了四足机器人上,从而验证了其在现实场景下的泛化性。

图像语义信息在视觉SLAM中的应用研究进展

视觉同步定位与建图(visual simultaneous localization and mapping,VSLAM)技术以相机为主要传感器采集图像数据,基于多视几何、状态估计等算法原理获取载体的位置和姿态,同时构建一张用于导航定位的地图。视觉SLAM是自动驾驶、AR(augmented reality)、VR(virtual reality)、MR(mix reality)、智能机器人、无人机飞控中的关键技术。近年来,随着各个产业对智能导航定位的需求日渐增多,原本以几何测量为主的视觉SLAM逐渐融入对环境的语义理解。语义信息是指能够被人类直观感受和理解的概念,而图像语义信息是指图像中物体的轮廓、类别、显著性等信息。相比于图像中的几何特征,语义信息更具时空一致性,且更贴近人类感知的结果。将图像语义信息引入视觉SLAM,既能促进系统各个模块的性能,还能够提升视觉SLAM的智能感知能力,形成集几何测量、定位定姿、环境理解等多种功能的视觉语义SLAM。本文根据图像语义信息的应用方式,对视觉语义SLAM经典方案和最新研究进展进行归纳梳理。在此基础上,本文总结了视觉语义SLAM的现存问题与挑战,指出该领域未来的研究方向,以推动其面向智能导航定位进一步发展。

内河水运基础设施及船舶技术发展现状与展望

我国交通运输事业已步入全面建设交通强国的新发展阶段,内河水运在综合交通运输体系中的比较优势尚未得到充分发挥,而“双循环”新发展格局及“双碳”战略的实施将要求内河水运及其核心要素的船舶技术必须实现创新发展。该文通过梳理提炼国内外内河水运以及船舶发展的现状与相关政策演变,分析创新技术研究进展与典型案例,对内河水运基础设施及船舶技术发展趋势进行展望:未来内河水运基础设施与数字、信息和网络技术深度融合,岸基控制中心作为关键性设施和船舶能源供给设施网联化;船舶则向着船型标准化、谱系化、智能化、少人化、能源绿色化及多元化、电力推进主流化等方向演进;船舶编队航行成为创新运输模式。文中所探索的内河水运基础设施及船舶技术的变革方向,可为建设新一代内河水运体系和研发先进船型提供参考。