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检索条件"任意字段=3rd International Conference on Robot Intelligence Technology and Applications"

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Exploring the Influence of Smart applications And Website Service Quality by Smart PLS Software on Continuous Online Shopping Intention 3

Exploring the Influence of Smart Applications And Website Se...

引用

3rd IEEE international conference on Electronic Communications, Internet of Things and Big Data, ICEIB 2023

作者： Chuang, Shu-Hui Ou, Cheng-Chieh Wang, Yu-Xuan Department of Business Administration Asia University Taichung Taiwan

ISBN: (纸本)9798350333862

With the development and popularity of the Internet, consumers can search for information conveniently and rapidly through the Internet. Website service quality has been improving and advancing with the application of artificial intelligence (AI) and big data, leading to the pivotal role of smart applications in shopping. Nowadays, website service quality has become one of the crucial criteria for enterprises. Therefore, we examine the influence of smart applications and website service quality on consumers' online shopping decisions and analyze the effect of expectation confirmation theory on consumer satisfaction and online shopping intention. We collected data from people with online shopping experiences, using questionnaires and Smart PLS for empirical data analysis and validation. A total of 217 valid questionnaires were collected. The results of the analysis show that smart applications, website service quality, and consumer confirmation have a positive impact on consumer satisfaction. Also, consumer satisfaction affects the willingness to continue online shopping. However, the fulfillment of the AI technology and the web service quality in the subdivision of the intelligence application is not supported by those factors. Hence, the results of this study suggest that the operators of shopping sites create excellent shopping sites and service quality to enhance consumer satisfaction and develop membership system management, which gives superiority over competitors. © 2023 IEEE.

关键词： Websites

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Deep Learning based Advanced Image Recognition in Autonomous Vehicles in Industry 4.0 3

Deep Learning based Advanced Image Recognition in Autonomous...

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3rd international conference on Applied Artificial intelligence and Computing, ICAAIC 2024

作者： Aruna, R. Manjula Devi, P. Suresh, D. Arul Pandiyan, M. Sathya, S. Geetha, K. Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology Department of Computer Science and Engineering Chennai India Vtu Affiliated Amc Engineering College Department of Information Science and Engineering Banglore India Unnamalai College of Arts and Science Department of Computer Science Kovilpatti India Bannari Amman Institute of Technolgy Department of Information Science and Engineering Erode India Bannari Kongu Engineering College Department of Mathematics Erode India Dean of Academics and Research Jct College of Engineering and Technology Coimbatore India

ISBN: (纸本)9798350375190

The automation with integration of numerous devices are important factors in the manufacturing and production sectors in Industry 4.0. This involves the use of autonomous vehicles for diverse applications. They are based on advanced image recognition systems. The efficient functioning of the system is achieved using deep learning techniques. These networks have the ability to automatically learn from complex data. These deep learning techniques are used for the detection of obstacles, lane following and object recognition. The various constraints in obtaining the optimum performance are achieved using ant colony optimization techniques. This helps in obtaining the overall efficiency of autonomous operations. They helps in evaluating optimum solutions through iterative updation of the artificial pheromones. They are used for the optimization of hyperparameters and training parameters. They helps in fine tuning of the model for various requirements of autonomous vehicles in Industry 4.0. They results in reduced computational costs with improved convergence. The integration of deep learning with ACO helps in overcoming the challenges in the deployment of advanced image recognition systems in autonomous vehicles. They helps in improving the perception capabilities of the vehicles. These autonomous vehicles provide adaptive solutions for various processes in the manufacturing and production sectors. © 2024 IEEE.

关键词： Image recognition

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Short Inter-robot Distance Following Based on Collision-free Nonlinear Model Predictive Control 6

Short Inter-robot Distance Following Based on Collision-free...

引用

6th international conference on Reconfigurable Mechanisms and robots (ReMAR)

作者： Lin, Xijie Song, Yuan Guo, Lei Beijing Univ Posts & Telecommun Artificial Intelligence Sch Beijing 100876 Peoples R China

ISBN: (纸本)9798350395976;9798350395969

Self-reconfigurable robots aim to develop intelligent robotic systems with shape variability and task adaptability. This technology employs modular design, allowing robots to autonomously adjust their shape and structure according to specific tasks. For multiple self-reconfigurable robots using mecanum wheels as their mobile platform, a collision-free nonlinear model predictive control (NMPC) method is adopted to provide control strategies, enabling them to accomplish short-distance tracking tasks in real-time environments. An external radar module is utilized for global robot localization and obtaining high-precision pose information. Experiments conducted in a 3D simulation environment validate the effectiveness of this approach. In practical applications, overcoming various challenges such as hardware design, communication, and perception is essential to achieve robustness and reliability in self-reconfigurable robot systems.

关键词： Predictive control systems

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robotic Scheduling Strategies based on Machine Learning Algorithm 3

Robotic Scheduling Strategies based on Machine Learning Algo...

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2023 3rd international conference on Artificial intelligence and Industrial technology applications, AIITA 2023

作者： Wu, Hongzhong Xing, Tenghui Li, Weiqing Chen, Hongbiao Kang, Yutao Li, Jiayang School of Electronic Information and Electrical Engineering Huizhou University Huizhou China College of Big Data and Internet Shenzhen Technology University Shenzhen China

Recently, robot scheduling has been widely concerned by numerous companies and researchers. They adopt an intelligent algorithm to design scheduling strategies for automated guided vehicle (AGV) and achieve required moving routes and certain aims. However, the existing robot scheduling strategies employ mathematical program models to arrange robots' control and ignore machine issues that the robots may have. This will cause conflict and may lead the whole robot to a deadlock when the scale of conflict reaches a critical point. In this paper, we present a novel scheduling strategy for intelligent robots by training machine learning algorithms. Initially, we assume the robots contain a communication system, which can only receive signals from the central controller. Subsequently, we utilize the input parameters including robot conditions, working area, and working aims to train the machine learning algorithm. The work accomplishment ratio and conflict ratio are two essential indicators to measure our proposed method. Additionally, we also simulate the existing robot scheduling models to compare. From the extensive experimental results and comparison evaluations, we can conclude that our proposed method can achieve the robots scheduling tasks with reasonable costs. At last, we discuss the challenges of applying machine learning techniques to robotic scheduling and potential solutions and provide future directions in this field. © Published under licence by IOP Publishing Ltd.

关键词： Intelligent robots

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The Research of the Relationship Between Artificial intelligence and Human Brain 3

The Research of the Relationship Between Artificial Intellig...

引用

3rd international conference on Artificial intelligence, Big Data and Algorithms, CAIBDA 2023

作者： Xin, Qiangwei School of Computer Science Xianyang Normal University Shaanxi Xianyang712000 China

ISBN: (纸本)9781643684444

Artificial intelligence is a technology and method that utilizes computers and algorithms to simulate and implement human intelligence. It can learn and optimize through a large number of data and algorithms to achieve various intelligent tasks and functions, such as natural language processing, image recognition, intelligent decision-making, etc. Artificial intelligence technology has been widely applied in fields such as healthcare, finance, transportation, and manufacturing, becoming an important force driving economic and social development. Artificial intelligence is closely related to the human brain. This article analyzes the relationship between artificial intelligence and the human brain, including their connections and differences, imitation mechanisms, neural networks, and deep learning. © 2023 The Authors.

关键词： Brain

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Research on Hardware Controller of BLDC Motor Rehabilitation robot Based on STM32 3

Research on Hardware Controller of BLDC Motor Rehabilitation...

引用

2022 3rd international conference on Computer Information and Big Data applications, CIBDA 2022

作者： Ning, Zhixiang Chen, Liwen Luo, Jian Qi, Linfeng Institute of Ubiquitous Perception and Multi-Sensor Intelligence Fujian University of Technology Fuzhou350000 China

ISBN: (纸本)9783800758760

Taking the DC brushless motor as the controlled object and STM32F103VET6 as the core, the design of the controller hardware circuit is carried out. The circuit mainly includes PWM drive circuit composed of IR2110, inverter circuit composed of IRFP250, Hall position detection circuit, current detection circuit, etc. The system uses current feedback and rotor position feedback to realize double closed-loop control of the motor. The controller has a VR virtual device interface for healing and fun. MATLAB/Simulink is used to simulate, and the fuzzy PID is used to compare with the traditional PID. The experimental results show that the fuzzy PID has faster response speed, better stability and less overshoot than the traditional PID, which can meet the control performance requirements of the rehabilitation lower limb robot. © VDE VERLAG GMBH - Berlin - Offenbach.

关键词： Brushless DC motors

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A Hierarchical Autonomous Exploration Algorithm for Large-scale and Complex Environments with Mobile robot 23

A Hierarchical Autonomous Exploration Algorithm for Large-sc...

引用

3rd international conference on robotics and Control Engineering, RobCE 2023

作者： Chen, Qian Qi, Lizhe Hua, Zhongwei Yang, Zhi Sun, Yunquan Academy for Engineering & Technology Fudan University China

ISBN: (纸本)9781450398107

In order to solve the problem of low exploration efficiency caused by repeatedly backtracking the frontiers in large and complex environments, a hierarchical autonomous exploration algorithm is proposed. Firstly, based on the robot's static model to judge the environment's traversability, which allows robots to explore complex 3D environments. Following that, a hybrid strategy is used to filter out frontiers within a local planning horizon, thus complete exploration of the local area is achieved by solving the traveling salesman problem (TSP). Finally, the sparse global topology map generates transfer paths between sub-areas, transferring the robot to another sub-area to resume exploration. Compared to the RRT autonomous exploration algorithm and the GBP autonomous exploration algorithm, the method in this work reduces the exploration path by more than 13.8% and the exploration time by more than 23.7%. The results show that the proposed algorithm significantly improves the autonomous exploration efficiency of mobile robots in large and complex environments. © 2023 ACM.

关键词： Motion planning

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robot Autonomous Exploration Mapping Based on FD-RRT 3

Robot Autonomous Exploration Mapping Based on FD-RRT

引用

3rd international conference on Computer Science, Electronic Information Engineering and Intelligent Control technology, CEI 2023

作者： Jiang, Quan Yin, Ling Zhang, Chao Chen, Xiangyin Li, Yunlong Yu, Pengfei Dongguan University of Technology Department of Mechanical Engineering Dongguan Guangdong523808 China Guangdong Prov. Key Lab. of Intelligent Disaster Prev. and Emergency Technol. for Urban Lifeline Eng. China

ISBN: (纸本)9798350372052

In order to enhance the autonomous exploration efficiency of robots in unknown environments, this study proposes a Fast Double Rapidly Exploring Random Tree (FD-RRT) algorithm. The algorithm combines a globally exploring random tree with adaptive step size and a locally exploring random tree with directional bias, aiming to quickly locate the boundary points of the map. In the algorithm design, considerations encompass information gain of the map, redundancy of information in boundary points, and navigation cost of the robot. Simultaneously, by eliminating the redundant information in boundary points and based on the gain in boundary information and exploration cost, different cost values are assigned to navigation points, guiding the robot to prioritize the exploration of regions with lower costs. The effectiveness of the proposed strategy is validated through a series of simulation experiments and real-world applications. © 2023 IEEE.

关键词： Navigation

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Design and Characterization of a High-performance Wearable robot Using Symmetric Conjugate Surface Joints 3

Design and Characterization of a High-performance Wearable R...

引用

3rd IEEE international conference on Information technology, Big Data and Artificial intelligence, ICIBA 2023

作者： Liang, Renghao Zhang, Qifeng Yang, Wenlin Wang, Yuqi Yin, Yudong He, Bo Guangdong Institute of Intelligent Unmanned System Guangdong China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China Xi'an Jiaotong University Shaanxi China

ISBN: (纸本)9781665490788

Hand impairments after stroke of a person can result in losing his independence and quality of life. Hand exoskeletons are widely used for hand rehabilitation and assist in grasping tasks in people's daily life. Unfortunately, current hand exoskeletons remain challenges in user-friendly design, portable for daily use, and dexterity for different tasks. Here, we report a wearable hand exoskeleton that incorporates key biomimetic properties of human hand. The exoskeleton contains a series of symmetric conjugate surface joints. The hand exoskeleton proposed here achieves accurate biomimetic performance in the execution of finger natural grasping. Thanks to the conjugate surface joints, the finger exoskeleton is capable of tracking specific trajectories with a simple structure comparing with the traditional n-bar linkage exoskeletons. Experimental results confirm that the exoskeleton covers the range of fingertip forces required to assist users in daily grasping activities. © 2023 IEEE.

关键词： Biomimetics

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DataHarbour: Enabling Decentalized AI Data Marketplace using Blockchain 3

DataHarbour: Enabling Decentalized AI Data Marketplace using...

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3rd IEEE international conference on Blockchain and Distributed Systems Security, ICBDS 2024

作者： Dave, Maheak Saraf, Awantika Kumar, Rishabh Bhattacharya, Rituparna Techno India University Department of Computer Science and Engineering-Artificial Intelligence West Bengal 700091 India Techno India University Department of Computer Science and Engineering India

ISBN: (纸本)9798350354348

Artificial intelligence revolutionizes digital applications through simulation of human intelligence in machines, driving unprecedented progress in technology and decision-making. By adeptly processing large volumes of data, AI systems excel in pattern recognition, learning from experience, and autonomously making decisions. However, the present AI ecosystem suffers from data inequity, with major corporations dominating the market while smaller businesses still struggling. Access to AI data is the privilege of tech giants. In this paper, we propose DataHarbour, a blockchain-based marketplace that addresses issues with AI data access. DataHarbour's decentralized platform seeks to democratize data access and promote cooperation. Built on blockchain- a disruptive emerging technology that buttresses decentralized systems, it leverages smart contracts, incorporates data verification, and a reputation system. This paper also delineates the design and operation of AI data market place and portrays the system's ability to foster a more inclusive AI environment. DataHarbour aims to accelerate AI innovation and close the data divide by facilitating safe data interchange and fostering integrity. © 2024 IEEE.

关键词： Smart contract

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