Application Of Intelligent Robot Research Articles

Bioinspired Ultra‐Stretchable and Highly Sensitive Structural Color Electronic Skins

AbstractOrganisms possess remarkably adaptive ability to complex environments. For example, chameleons can alter their skin color to adapt to varying environments, which has inspired significant advances in bioinspired soft electronic skins (E‐skins), and their wide applications in wearable sensors, intelligent robots, and health monitoring. However, current bioinspired E‐skins face challenges in ultra‐stretchability, high sensitivity, and long‐term stability owing to the intrinsic limitations associated with their mismatched interface between soft matrix and hard conductive fillers, hindering their practical applications. Here, it is reported that bioinspired structural color electronic skins (SC E‐skins) that consist of liquid metal particles (LMPs), periodical ordered colloidal crystal arrays, and ultra‐stretchable hydrogel, imparting synergistic and durable electrical–optical sensing capabilities. Such SC E‐skins demonstrate outstanding performances including superior flexibility (elongation at break > 1100%), high sensitivity (gauge factor = 3.26), fast synergetic electric–optical response time (≈100 ms), outstanding durability (over 1500 cycles), and high accuracy (R2 > 99.5%). These bioinspired SC E‐skins with excellent capability of converting mechanical signals into synergetic electrical–optical outputs hold great promise for smart wearable devices, affording a new horizon in developing advanced health monitoring technologies.

A skin-inspired anisotropic multidimensional sensor based on low hysteresis organohydrogel with linear sensitivity and excellent robustness for directional perception

Human skin has complex sensors to perceive three-dimensional stimuli from the environment. Skin-inspired flexible sensors with multidimensional and directional perception are desirable for applications in intelligent robots and human–machine interaction. Herein, wearable multidimensional sensors have been fabricated by macroscopically assembling 3D-printed microstructured anisotropic organohydrogel sensory units through robust interfacial adhesion. The organohydrogel is crosslinked using microgels and starch microparticles through non-covalent interactions, and composited with short carbon fibers as conductive fillers. The physical network exhibits low hysteresis against 5000 cyclic loadings, which demonstrates excellent robustness in both mechanical properties and sensory performance. The organohydrogel precursor is printed into a cone-shaped sensor with a pressure sensitivity 50 times higher than that of its bulk counterpart. A sea cucumber epidermis-like microstructured sensor with abundant highly sensitive cone array is assembled with 3D-printed anisotropic gels with highly aligned carbon fibers inside, generating a multidimensional sensor capable of perceiving stimuli along X-, Y-, and Z-axis. The assembled sensor can directionally distinguish external forces and identify human motions. This study demonstrates a promising strategy to fabricate well-structured organohydrogel sensors for applications in electronic skin, biomimetic flexible electronics, and artificial intelligence.

Application of Virtual Reality Technology and Intelligent Robot in Architectural Heritage Protection

Application of Virtual Reality Technology and Intelligent Robot in Architectural Heritage Protection

The Application of Intelligent Robots and Deep Learning in the Construction Management Platform System of Construction Engineering

The Application of Intelligent Robots and Deep Learning in the Construction Management Platform System of Construction Engineering

The Application of Deep Learning Intelligent Robots in the Design and Implementation of Information Retrieval Systems

The Application of Deep Learning Intelligent Robots in the Design and Implementation of Information Retrieval Systems

The Application of Intelligent Welding Robots and Visual Detection Algorithms in Building Steel Structures

The Application of Intelligent Welding Robots and Visual Detection Algorithms in Building Steel Structures

Research on the promotion of intelligent entertainment voice robots in personalized English learning based on data mining and gamified teaching experience

With the development of educational technology and the arrival of the intelligent era, intelligent entertainment voice robots have gradually become a research hotspot in the field of education. This study aims to explore the application of intelligent entertainment voice robots based on data mining in the promotion of personalized English learning, and combine with gamified virtual teaching to improve learners’ learning interest and learning effect. The study uses data mining technology to analyze learners’ learning data, interest preferences and learning performance, and provides learners with targeted learning resources and gamified virtual teaching environment based on personalized recommendation. The study creates a virtual teaching environment presented in the form of games, which contains various interesting tasks, challenges and reward mechanisms. Learners can participate in the virtual teaching environment at the same time, experience the fun and stimulation of games, so as to stimulate the interest and motivation of learning. Learners can engage in interactive speech learning through conversations with intelligent entertainment speech robots. The robot can provide real-time answers to learners’ questions, provide personalized learning suggestions, and provide encouragement and feedback. By interacting with robots, learners can get more flexible and personalized learning support, improving learning effectiveness and satisfaction. Through experiments and data analysis, it is found that intelligent entertainment voice robot based on data mining and gamification teaching experience can effectively improve learners’ learning interest and learning effect. Learners show higher engagement and motivation in personalized recommended learning resources and gamified virtual teaching environments.

Graphene Sterically-Wrapped textile piezoresistive Sensors: A spray coating path for synergistically advancing sensitivity and response range

Trade-off between a high sensitivity and a broad sensing range remains a persistent challenge for flexible pressure sensors. Not to suffer from this dilemma, a flexible textile piezoresistive sensor sterically-wrapped with graphene by spray coating is reported, which constructs enriched three-dimensional conductive networks from leather fabric’s inherent fibers and pore structures, synergistically advancing the sensitivity and response range. Such a sensor renders bulky spatial deformation and augmented pressure-induced conducting paths, and hence affords an ultra-high sensitivity of 259.6 kPa−1(0–100 kPa) and an exceptional response range of up to 1 MPa. Besides, the graphene/textile sensor demonstrates outstanding durability (>12000 cycles). With these advantages, real-time monitoring of human physiological activities such as wrist pulses and throat swallowing is successfully achieved. Benefitting from the scalability of the spraying methodology, a large-size 45 × 45 cm2 sensing array with a 32 × 32 matrix is facilely fabricated to map the spatial pressure of human interactive behaviors for ergonomics. And smart insoles incorporating graphene/textile sensors can capture plantar pressure distribution and provide effective analysis for diverse static/dynamic movements of feet. Such spray-coated textile sensors could not only find potential applications in wearable electronics and intelligent robotics, but also open the possibility of monitoring complex heavy machinery and large-scale infrastructures.

A Review of Orchard Robot Research

In modern agricultural production, orchards, as one of the important agricultural fields, are facing difficulties such as labor shortage, low production efficiency, and rising costs. To cope with these difficulties, orchard robots were introduced as an emerging technology. With the rapid development of robotics, artificial intelligence and machine learning, the application of intelligent robots in the agricultural field is becoming more and more mature. Advances in sensing technology, navigation technology, image recognition and other technologies have provided technical support for the research and application of orchard robots. Through the precise operation of orchard robots, precise management of orchard crops can be realized, including precise fertilization, pest and disease monitoring, directional irrigation, etc., so as to improve the yield and quality of orchards. This increases production efficiency, reduces costs, increases yields, and drives agriculture towards sustainable development. This paper combs the research status of picking robots by combining literature collation and market research, shows the scientific research results of various types of orchard picking robots at home and abroad, makes an in-depth analysis of the existing problems, and discusses the basic system composition of orchard picking robots Existing problems, and propose solutions to the problems found. Orchard picking robot has a huge application space in China, but due to the difficulty of research and development, there are still few economical and practical orchard picking robot products at home and abroad. It is necessary to increase the research and development of intelligent picking robots, integrate multidisciplinary high and new technologies, vigorously carry out innovative research on intelligent picking technology and equipment, improve the precision, portability, and low cost of robots, and promote the early application of orchard picking robots in China.

Exploration of the Application of Agricultural Intelligent Robots in the Qinghai-Tibet Plateau

In order to improve agricultural efficiency, reduce labor intensity, and improve the quality and yield of agricultural products on the Tibetan Plateau, this paper takes the application of traditional agricultural robots as an example and proposes the application of agricultural robots to agriculture on the Qinghai-Tibet Plateau based on the special breeding environment of the Qinghai-Tibet Plateau combined with the current situation of traditional agriculture. Through the application practice of robots in traditional agriculture, the possibility of the application of agricultural robots in the Qinghai-Tibet Plateau is pointed out, the working methods and advantages of robots in the Qinghai-Tibet Plateau are expounded, and the application of intelligent agricultural robots in the agriculture of the Qinghai-Tibet Plateau is discussed and analyzed. The results show that with the progress of science and technology, intelligent robots have gradually played an important role in various fields, and intelligent robots have broad application prospects in plateau agriculture. The application of agricultural robots in the Qinghai-Tibet Plateau should be aimed at the Qinghai-Tibet Plateau to make some adaptive research and development, intelligent upgrading and demonstration project promotion in order to promote the Qinghai-Tibet Plateau agricultural automation.

Double-sided microstructured flexible iontronic pressure sensor with wide linear sensing range

Iontronic pressure sensors have garnered significant attention for their potential in wearable electronic devices. While simple microstructures can enhance sensor sensitivity, the majority of them predominantly amplify sensitivity at lower pressure ranges and fail to enhance sensitivity at higher pressure ranges, leading to nonlinearity. In the absence of linear sensitivity in a pressure sensor, users are unable to derive precise information from its output, necessitating further signal processing. Hence, crafting a linearity flexible pressure sensor through a straightforward approach remains a formidable task. Herein, a double-sided microstructured flexible iontronic pressure sensor is presented with wide linear sensing range. The ionic gel is made by 1-Ethyl-3-methylimidazolium bis(tri-fluoromethylsulfonyl)imide (EMIM:TFSI) into the matrix of poly(vinylidene fluoride-co-hexafluoropropylene) (PVDF-HFP), which acts as active layer, featuring irregular microstructures (IMS) and pyramid microstructures (PMS) on both sides. Unlike previous complex methods, IMS and uniform PMS are easily and achieved through pattern transfer from a sandpaper mold and micro-pyramid template. The iontronic pressure sensor exhibits exceptional signal linearity with R2 values of 0.9975 and 0.9985, in the wide pressure range from 100 to 760 kPa and 760 kPa to 1000 kPa, respectively. This outstanding linearity and wide sensing range stem from a delicate balance between microstructure compression and mechanical alignment at the ionic gel interface. This study provides valuable insights into achieving linear responses by strategically designing microstructures in flexible pressure sensors, with potential applications in intelligent robots and health monitoring.

Multi-scene application of intelligent inspection robot based on computer vision in power plant

As industries develop, the automation and intelligence level of power plants is constantly improving, and the application of patrol robots is also increasingly widespread. This research combines computer vision technology and particle swarm optimization algorithm to build an obstacle recognition model and obstacle avoidance model of an intelligent patrol robot in a power plant respectively. Firstly, the traditional convolutional recurrent neural network is optimized, and the obstacle recognition model of an intelligent patrol robot is built by combining the connection timing classification algorithm. Then, the artificial potential field method optimizes the traditional particle swarm optimization algorithm, and an obstacle avoidance model of an intelligent patrol robot is built. The performance of the two models was tested, and it was found that the highest precision, recall, and F1 values of the identification model were 0.978, 0.974, and 0.975. The highest precision, recall, and F1 values of the obstacle avoidance model were 0.97, 0.96, and 0.96 respectively. The two optimization models designed in this research have better performance. In conclusion, the two models in this study are superior to the traditional methods in recognition effect and obstacle avoidance efficiency, providing an effective technical scheme for intelligent patrol inspection of power plants.

Bioinspired sensors and applications in intelligent robots: a review

PurposeVision, audition, olfactory, tactile and taste are five important senses that human uses to interact with the real world. As facing more and more complex environments, a sensing system is essential for intelligent robots with various types of sensors. To mimic human-like abilities, sensors similar to human perception capabilities are indispensable. However, most research only concentrated on analyzing literature on single-modal sensors and their robotics application.Design/methodology/approachThis study presents a systematic review of five bioinspired senses, especially considering a brief introduction of multimodal sensing applications and predicting current trends and future directions of this field, which may have continuous enlightenments.FindingsThis review shows that bioinspired sensors can enable robots to better understand the environment, and multiple sensor combinations can support the robot’s ability to behave intelligently.Originality/valueThe review starts with a brief survey of the biological sensing mechanisms of the five senses, which are followed by their bioinspired electronic counterparts. Their applications in the robots are then reviewed as another emphasis, covering the main application scopes of localization and navigation, objection identification, dexterous manipulation, compliant interaction and so on. Finally, the trends, difficulties and challenges of this research were discussed to help guide future research on intelligent robot sensors.

Research on Key Technologies of Artificial Intelligence for Intelligent Manufacturing

Intelligent manufacturing, as the main form of future manufacturing, is the highland of a new round of competition in the global manufacturing industry, which will fundamentally change the production and manufacturing methods and technological and economic paradigms formed by human beings since the industrial revolution. At present, the intelligent manufacturing industry is still in the early stage of development, which is characterized by three typical characteristics: continuous growth of market size, strong promotion by national governments and diversification of competition subjects. At present, China's manufacturing industry is facing transformation, and the manufacturing industry is bound to need to transform to intelligent manufacturing. Industrial robots are the main content of current intelligent manufacturing, how to fully apply artificial intelligence technology to the manufacturing of industrial robots, so that its manufacturing efficiency, manufacturing accuracy and other product attributes are improved, to maximize its economic benefits, has a particularly important application value. The application of intelligent manufacturing and robots can not only promote the faster development of manufacturing, but also reconstruct new forms of manufacturing. Based on this, the paper first summarizes the application technology of intelligent manufacturing, and then analyzes the key technology of robot application for reference to relevant workers.

A Path Planning System for Orchard Mower Based on Improved A* Algorithm

The application of intelligent mobile robots in agriculture has emerged as a new research frontier, with the integration of autonomous navigation technology and intelligent agricultural robots being the key to the widespread adoption of smart agricultural machinery. This paper investigates comprehensive coverage path planning for tracked lawnmowers within orchard environments and addresses challenges related to task allocation and battery life. Firstly, in this study, the motion model of the tracked lawnmower was initially simplified based on assumptions about the orchard environment. Force analyses were conducted on each of its motion mechanisms. For the known orchard environment, a grid-based mapping technique was employed to model the orchard environment. Then, in order to improve the algorithm speed and reduce the number of turns during the lawnmower’s traversal, the A* search algorithm was enhanced by combining the method of robot cluster traversal in the orchard environment. Finally, the improved method was simulated and verified in the MATLAB platform to investigate the influence of the number of lawnmower clusters on the path planning in the connected and non-connected orchards. Furthermore, two sets of on-site field trials were meticulously designed to validate the reliability, practicality, and efficacy of the simulation experiments.

The applications and prospects of intelligent services robots in medicine

With the rapid growth of the ageing population and the increasing demand for medical services, the medical market is facing great challenges and opportunities. Intelligent service robots can provide various medical services, such as patient monitoring, drug distribution, medical record management, etc., which can improve medical efficiency, reduce the burden of medical staff, and have the advantage of 24-hour uninterrupted service. However, the application of intelligent service robots in the medical field still faces some challenges, such as technical limitations, legal and ethical issues. In addition, there are also differences in patient acceptance and demand for intelligent service robots. Based on the summary of intelligent medical treatment, this paper will introduce the application of intelligent service robots, study the application and prospect of intelligent service robots in medical treatment and the innovation of intelligent service robots in business models. Through literature review, SWOT analysis and data, the paper explains the wide application of intelligent service robots and their future opportunities and challenges.

Development analysis of intelligent robots in manufacturing industry

With the continuous development of the manufacturing industry, the application of intelligent robots is becoming more and more extensive. Many emerging technologies can be applied to intelligent robots. Typical intelligent robots still have room for further improvement in terms of automatic control and adaptation to the surrounding environment. And independent learning of production tasks and realization of human-computer interaction is the future development direction of industrial robots. In view of these deficiencies, the development of intelligent robots is particularly important. This paper introduces the application fields, key technologies and needs of intelligent robots, and explains the important position of intelligent robots in the future manufacturing industry. The functions of intelligent robot control, perception and human-computer interaction based on artificial intelligence technology are studied. Possible future challenges, limitations and problems will be presented at the end of this paper.

An intelligent dual-sensing e-skin system for pressure and temperature detection using laser-induced graphene and polydimethylsiloxane

Motivated by artificial intelligence, we present a novel electronic skin (e-skin) system capable of dual-sensing pressure and temperature signals. Our approach utilizes laser-induced graphene and polydimethylsiloxane, offering a simple yet efficient method for e-skin preparation. Experimental results reveal exceptional performance with good pressure sensitivity (0.037 kPa−1 at 0–50 kPa), a wide detection range (0–220 kPa), a fast response time of 56 ms, an ultra-low detection limit (30 Pa), and excellent stability (8000 cycles). Additionally, the e-skin exhibits positive temperature coefficients (0.0025 ℃-1) within 20–100 ℃, a rapid response time of 2.57 s, an extremely low detection limit (1 ℃), and stability after 50 cycles. Crucially, our intelligent e-skin system, employing a Long Short-Term Memory algorithm, enables real-time multi-modal tactile perception, accurately separating mixed pressure and temperature signals. This versatile technology holds immense potential for applications in intelligent robotics and human health monitoring.

The Application of Intelligent Robot in the Modern Hotel Industry—Take the Full Season Hotel as an Example

The Application of Intelligent Robot in the Modern Hotel Industry—Take the Full Season Hotel as an Example

Thermochromic and conductive hydrogels with tunable temperature sensitivity for dual sensing of temperature and human motion

Skin-like body sensors have important applications in soft-bodied intelligent robots, electronic skins, and medical health monitoring.