智能“机器人”拍摄装备对影视领域的影响及前景

随着科技的飞速发展,智能“机器人”拍摄装备逐渐崭露头角,已经成为影视领域中不可或缺的一部分,技术的变革对影视领域产生了深远的影响。智能“机器人”拍摄装备并不仅仅局限于在电视台节目制作中应用,而是扩展到整个影视制作行业。首先,介绍智能“机器人”拍摄装备的定义、架构、特点及分类。其次,分析它在大型综艺节目、体育赛事和演播室的应用,并探讨其对影视领域的影响。最后,展望生成式人工智能(Artificial Intelligence Generated Content,AIGC)时代智能“机器人”拍摄装备在影视领域的发展前景。

智能“机器人”制作入门(二) DP-811控制三色LED发光管变色[套件供应]

一、基本指令的介绍运用DP-811完成智能化控制,关键是必须掌握基本指令的操作。指令就是指挥计算机完成某种操作的命令。指令的组成 DP-811指令系统中绝大多数指令机器码的形式分为指令码和数据(操作数)两部分。指令的作用是让中央处理器(CPU)知道要去做什么事情。

Intelligent emergency service system based on wireless sensor and actuator networks

An intelligent emergency service（ IES） system is designed for indoor environments based on a wireless sensor and actuator network（ WSAN） composed of a gateway, sensor nodes, and a multi-robot system（ MRS）. If the MRS receives accident alarm information, the group of robots will navigate to the accident sites and provide corresponding emergency services.According to the characteristics of the MRS, a distributed consensus formation protocol is designed, which can assure that the multiple robots arrive at the accident site in a specified formation. The prototype emergency service system was designed and implemented, and some relevant simulations and experiments were carried out. The results showthat the MRS can successfully provide emergency lighting and failure node replacement services when accidents happen. The effectiveness of the algorithm and the feasibility of the system are verified.

BACKGROUND KNOWLEDGE AND SECONDARY KNOWLEDGE BASES IN LEARNINGS YSTEMS

This paper presents the differences and relations between background knowledge and domain theories in learning systems. The roles they play during learning procedures are discussed. It is emphasized that background knowledge plays an important role in enhancing the ability of a learning system. An explanation based learning system with domain theory in primary knowledge base and background knowledge in secondary knowledge base is introduced as an example. It shows how background knowledge can be used to solve some of the problems caused by incomplete domain theory in an explanation based learning system. The system can accomplish knowledge level learning through purely deductive approach. At last the acquisition of background knowledge is briefly discussed.

Design of intelligent line-tracking chess robot based on STM32

An intelligent line-tracking chess robot based on STM32 is introduced in this paper. Its hardware consists of photo- electric detection circuit, main control circuit, motor driven circuit, steering engine driven circuit and dial switch. The hardware structure and software flow chart of the system are described in details in this paper. The robot is driven by rear wheel motors, and the real-time position of the robot is determined by the ground information collected by infrared sensors. The heading direction of robot is adjusted by steering engine installed in front wheel, and the open angle of manipulator is controlled by the other steering engine which can ensure the robot moving chessmen accurately and quickly during the moving process. The test shows that the kind of intelligent chess robot can complete the task in a fast and accurate way.

Design of intelligent line-tracking robot based on STM32

An intelligent line-tracking robot using the enhanced microprocessor STM32F103RBT6 as its core controller is introduced in this paper. The hardware configuration and line-tracking control principle of the system are described, and the black-white marked program design of the sensor is analyzed. Two motors are respectively driven by two H-bridge driving circuits, which are formed by four discrete components of metal oxide semiconductor （MOS） field effect transistor respectively. By altering values of voltage directions and pulse width modulation （PWM）, the walking direction and the speed of robot are adjusted, and the traditional PID control theory is adopted to adjust the robot during walking process. The results indicate that the design is scientific and reasonable, low cost, good adaptability and high applicability.

Design of novel sliding-mode controller for high-velocity AUV with consideration of residual dead load

This work focuses on motion control of high-velocity autonomous underwater vehicle(AUV).Conventional methods are effective solutions to motion control of low-and-medium-velocity AUV.Usually not taken into consideration in the control model,the residual dead load and damping force which vary with the AUV’s velocity tend to result in difficulties in motion control or even failure in convergence in the case of high-velocity movement.With full consideration given to the influence of residual dead load and changing damping force upon AUV motion control,a novel sliding-mode controller(SMC)is proposed in this work.The stability analysis of the proposed controller is carried out on the basis of Lyapunov function.The sea trials results proved the superiority of the sliding-mode controller over sigmoid-function-based controller(SFC).The novel controller demonstrated its effectiveness by achieving admirable control results in the case of high-velocity movement.

Active Tracking with Pan-Tilt-Zoom Camera

This paper intends to introduce the active vision system with autonomous robot competition in the background. It presents some characteristics of the human oculomotor system in active ma-chine vision svstem: smooth pursuit and saccade. Besides, zoom tracking is used to continuous ad-justment of a camera's focal length to keep a constant sized image of an object moving along the camera's optical axis. Experiments indicate the technology to be efficient for tracking the bail in the robot competition.

Research on an inertial piezoelectric actuator for a micro in-pipe robot

A new kind of inertial piezoelectric actuator for a micro in-pipe robot is proposed and studied. The actuator is composed of a body, corresponding to a mass rod, and four elastic legs. Each leg is a composite piezoelectric bimorph beam, made up of a middle metal element, an upper and lower piezoelectric elements. The mechanism is driven by an asymmetric waveform voltage, such as saw-toothed waveform, and utilizes the dynamic relationship between the maximum static friction force and the inertial force. To study the actuator, firstly, the constituent equation of a composite piezoelectric bimorph under both applied voltage and external force was inferred by thermodynamics. Secondly, the dvnamic model of the actuator was established analyzing the relationship between the locomotive states, viz. displacement and velocity, and design parameters, such as piezoelectric strain constant, elastic modulus,length, width and thickness of the piezoelectric element, actuator mass, and driving vohage. At last, the dynamic equation was solved and the theoretical calculation of the inherent frequency was more consistent with the experimental data, which proved the rationality of the model. All these lay a theoretical foundation of the micro actuator parameter optimization and more research on a micro robot.

Can nurses remain relevant in a technologically advanced future?

Technological breakthroughs occur at an ever-increasing rate thereby revolutionizing human health and wellness care.Technological advancements have drastically changed the structure and organization of the healthcare industry.McKinsey Global Institute estimates that 800 million workers worldwide could be replaced by robots by the year 2030.There is already a robotic revolution happening in healthcare wherein robots have made tasks and procedures more efficient and safer.Locsin and Ito has addressed the threat to nursing practice with human nurses being replaced by humanoid robots.Routine nursing care dictated solely by prescribed procedures and accomplishment of nursing tasks would be best performed by machines.With the future practice of nursing in a technologically advanced future transcending the implementation of nursing actions to achieve predictable outcomes,how can human nurses remain relevant as practitioners of nursing?Nurses should be involved in deciding which aspects of their practice can be delegated to technology.Nurses should oversee the introduction of automated technology and artificial intelligence ensuring their practice to be more about the universal aspects of human care continuing under a novel system.Nursing education and nursing research will change to encompass a differentiated demand for professional nursing practice with,and not for,robots in healthcare.

Intelligent PID controller based on ant system algorithm and fuzzy inference and its application to bionic artificial leg

A designing method of intelligent proportional-integral-derivative(PID) controllers was proposed based on the ant system algorithm and fuzzy inference. This kind of controller is called Fuzzy-ant system PID controller. It consists of an off-line part and an on-line part. In the off-line part, for a given control system with a PID controller,by taking the overshoot, setting time and steady-state error of the system unit step response as the performance indexes and by using the ant system algorithm, a group of optimal PID parameters K*p , Ti* and T*d can be obtained, which are used as the initial values for the on-line tuning of PID parameters. In the on-line part, based on Kp* , Ti*and Td* and according to the current system error e and its time derivative, a specific program is written, which is used to optimize and adjust the PID parameters on-line through a fuzzy inference mechanism to ensure that the system response has optimal transient and steady-state performance. This kind of intelligent PID controller can be used to control the motor of the intelligent bionic artificial leg designed by the authors. The result of computer simulation experiment shows that the controller has less overshoot and shorter setting time.

Dyna-QUF:Dyna-Q based univector field navigation for autonomous mobile robots in unknown environments

A novel approach was presented to solve the navigation problem of autonomous mobile robots in unknown environments with dense obstacles based on a univector field method. In an obstacle-free environment, a robot is ensured to reach the goal position with the desired posture by following the univector field. Contrariwise, the univector field cannot guarantee that the robot will avoid obstacles in environments. In order to create an intelligent mobile robot being able to perform the obstacle avoidance task while following the univector field, Dyna-Q algorithm is developed to train the robot in learning moving directions to attain a collision-free path for its navigation. Simulations on the computer as well as experiments on the real world prove that the proposed algorithm is efficient for training the robot in reaching the goal position with the desired final orientation.

The Future of Manufacturing： A New Perspective

Many articles have been published on intelligent manufacturing, most of which focus on hardware, soft-ware, additive manufacturing, robotics, the Internet of Things, and Industry 4.0. This paper provides a dif-ferent perspective by examining relevant challenges and providing examples of some less-talked-about yet essential topics, such as hybrid systems, redefining advanced manufacturing, basic building blocks of new manufacturing, ecosystem readiness, and technology scalahility. The first major challenge is to （re-）define what the manufacturing of the future will he, if we wish to： ① raise public awareness of new manufacturing＇s economic and societal impacts, and ② garner the unequivocal support of policy- makers. The second major challenge is to recognize that manufacturing in the future will consist of sys-tems of hybrid systems of human and robotic operators; additive and suhtractive processes; metal and composite materials; and cyher and physical systems. Therefore, studying the interfaces between con- stituencies and standards becomes important and essential. The third challenge is to develop a common framework in which the technology, manufacturing business case, and ecosystem readiness can he eval- uated concurrently in order to shorten the time it takes for products to reach customers. Integral to this is having accepted measures of ＂scalahility＂ of non-information technologies. The last, hut not least, chal-lenge is to examine successful modalities of industry-academia-government collaborations through public-private partnerships. This article discusses these challenges in detail.

Dynamics model of underwater robot motion control in 6 degrees of freedom

In order to analyze underwater robot control system dynamics features, a system 6-DOF dynamics model was founded. Underwater robot linear and nonlinear hydrodynamics were analyzed by Taylor series, based on general motion equation. Special control system motion equation was deduced by cluster of inertial items and non-inertial items. For program convenience, motion equation matrix format was presented. Experimental principles of screw propellers, rudders and wings were discussed. Experimental data least-square curve fitting, interpolation and their corresponding traditional equation helped us to obtain the whole system dynamic response procedure. A series of simulation experiments show that the dynamics model is correct and reliable. The model can provide theory proof for analyzing underwater robot motion control system physics characters and provide a mathematic model for traditional control method.

Advances of Artificial Intelligence Application in Medical Imaging of Ovarian Cancers

Ovarian cancer is one of the three most common gynecological cancers in the world,and is regarded as a priority in terms of women’s cancer.In the past few years,many researchers have attempted to develop and apply artificial intelligence(AI)techniques to multiple clinical scenarios of ovarian cancer,especially in the field of medical imaging.AI-assisted imaging studies have involved computer tomography(CT),ultrasonography(US),and magnetic resonance imaging(MRI).In this review,we perform a literature search on the published studies that using AI techniques in the medical care of ovarian cancer,and bring up the advances in terms of four clinical aspects,including medical diagnosis,pathological classification,targeted biopsy guidance,and prognosis prediction.Meanwhile,current status and existing issues of the researches on AI application in ovarian cancer are discussed.

Cartesian impedance control of dexterous robot hand

Presents a novel compliant motion control for a robot hand using the Cartesian impedance approach based on fingertip force measurements. The fingertip can accurately track desired motion in free space and appear as mechanical impedance in constrained space. In the position based impedance control strategy, any switching mode in contact transition phase is not needed. The impedance parameters can be adjusted in a certain range according to various tasks. In this paper, the analysis of the finger’s kinematics and dynamics is given. Experimental results have shown the effectiveness of this control strategy.

Interval Type-2 fuzzy position control of electro-hydraulic actuated robotic excavator

This paper deals with fuzzy intelligent position control of electro-hydraulic activated robotic excavator for the control of boom, arm and bucket axes. Intelligent control systems are required to overcome unde- sirable stick-slip motion, limit cycles and oscillations. Models of electro-hydraulic servo controlled front end loader excavators are highly nonlinear. The nonlinear model accounts for fluid flow rate of valve, pump hydraulics, and friction forces. The friction forces are modelled by Coulomb, viscous and Stribeck function. Interval Type-2 Fuzzy Logic Controller （IT2FLC） is used to study the time-domain position responses of axes in the presence of external applied load. It has the ability to control the position of each of the three axes with minimum actuator position errors. Models presented are accurate and study the dynamics of the actuator and load. To improve the transient behaviour of the robotic excavator, we elim- inated iitter of the bucket movement in the presence of nonlinearities.

A study on key technologies of unmanned driving

Although the development of machine intelligence is far from simulating all the cognitive competence of our brains, still it is absolutely possible to peel the driving activity from people＇s cognitive activities and then make the machine finish some low-level, complicated and lasting driving cognition by simulating our brains. The goal of driving is to replace drivers and free them from boring driving activities. Based on some studies on unmanned driving, this paper summarizes and analyzes the background, significance, research status and key technology of unmanned driving and the research group also introduces some research on brain cognition of driving and sensor placement of intelligent vehicles, which offers more meaningful reference to push the study of unmanned driving.

Assessment criteria for nonverbal interaction contents in r-learning

r-learning,which is based on e-learning and u-learning,is defined as a learning support system that intelligent robots serve verbal and nonverbal interactions on ubiquitous computing environment.In order to guarantee the advantages of r-learning contents with no limits of timc and place and with nonverbal interaction which are not in e-learning contents,in recent years,assessment criteria for r-learning contents are urgently rcquired.Therefore,the reliable and valid assessment criteria were developed for nonverbal interaction contents in r-learning,and its detailed research content is as follows.First,assessment criteria for nonverbal interaction in r-learning contents will be specified into gesture,facial expression,semi-verbal message,distance,physical contact and time.Second,the validity of the developed assessment criteria will be proved by statistics.Consequently,the assessment criteria for nonverbal interaction contents will be helpful when choosing the better r-learning content and producing the better r-learning content,and the reliability of school education is improved ultimately.

Artificial intelligence and its application for cardiovascular diseases in Chinese medicine

Cardiovascular diseases(CVDs)are major disease burdens with high mortality worldwide.Early prediction of cardiovascular events can reduce the incidence of acute myocardial infarction and decrease the mortality rates of patients with CVDs.The pathological mechanisms and multiple factors involved in CVDs are complex;thus,traditional data analysis is insufficient and inefficient to manage multidimensional data for the risk prediction of CVDs and heart attacks,medical image interpretations,therapeutic decision-making,and disease prognosis prediction.Meanwhile,traditional Chinese medicine(TCM)has been widely used for treating CVDs.TCM offers unique theoretical and practical applications in the diagnosis and treatment of CVDs.Big data have been generated to investigate the scientific basis of TCM diagnostic methods.TCM formulae contain multiple herbal items.Elucidating the complicated interactions between the active compounds and network modulations requires advanced data-analysis capability.Recent progress in artificial intelligence(AI)technology has allowed these challenges to be resolved,which significantly facilitates the development of integrative diagnostic and therapeutic strategies for CVDs and the understanding of the therapeutic principles of TCM formulae.Herein,we briefly introduce the basic concept and current progress of AI and machine learning(ML)technology,and summarize the applications of advanced AI and ML for the diagnosis and treatment of CVDs.Furthermore,we review the progress of AI and ML technology for investigating the scientific basis of TCM diagnosis and treatment for CVDs.We expect the application of AI and ML technology to promote synergy between western medicine and TCM,which can then boost the development of integrative medicine for the diagnosis and treatment of CVDs.