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Improved A* algorithm for path planning in dynamic environments 3

Improved A* algorithm for path planning in dynamic environme...

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3rd international conference on Algorithms, Microchips, and Network applications, AMNA 2024

作者： Hu, Chenhao Zhang, Zhian School of Mechanical Engineering Nanjing University of Science and Technology Nanjing China

ISBN: (纸本)9781510680098

To improve the global path planning capabilities of mobile robots and achieve real-time obstacle avoidance, a robot path planning algorithm that improves the traditional A* algorithm is proposed. The A* algorithm is utilized for the design of global path planning, incorporating weight coefficients into the heuristic function to bolster search efficiency. Path smoothing is performed by improving the Floyd algorithm, aiming to reduce inflection points and increase the path smoothness. For local path planning, the artificial potential field method is adopted to address the real-time obstacle avoidance limitations of the A* algorithm. Simultaneously, local corrections are applied to mitigate potential issues associated with local minima in the artificial potential field method. Additionally, attempts are made to navigate around obstacles by fine-tuning the turning angle. Simulation results validate that the improved A* algorithm can effectively construct reasonable paths in the map environment with better search mechanism and flexibility. The improved artificial potential field algorithm successfully achieves real-time obstacle avoidance, surpassing local optimal points. © 2024 SPIE.

关键词： Motion planning

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Multi-strategy Central Pattern Generator and Reinforcement Learning Integration for Quadruped Locomotion 3rd

Multi-strategy Central Pattern Generator and Reinforcement L...

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3rd international conference on Machine Learning, Cloud Computing and Intelligent Mining, MLCCIM 2024

作者： Zuo, Guoyu Wang, Yong Yu, Shuangyue Beijing University of Technology Beijing100124 China

ISBN: (纸本)9789819624676

Legged animals have the flexibility to change their gait locomotion pattern strategies under different environments and walking speeds, which is important for efficient locomotion. However, legged locomotion is currently studied as a fixed set of pre-programmed gait patterns, which limits locomotor flexibility. Moreover, the process of designing multiple coping strategies for multiple tasks is cumbersome. In this study, we introduce a novel framework for quadrupedal locomotion learning, enabling robots to swiftly and adaptably transition between gait patterns tailored to various environments. In addition, we introduce an environmental feedback framework to improve the quadrupedal robot's ability to perceive external environmental features. We obtain a strategy network through a two-stage training and deploy it to real robots. Finally, a multi-strategy controller is obtained, which enables the quadruped robot to realize flexible strategy shifts and, moreover, efficient traversal of various complex terrain environments. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Deep reinforcement learning

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HOG and Cloud Computing based Face Recognition for Attendance Monitoring 3

HOG and Cloud Computing based Face Recognition for Attendanc...

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3rd international conference on Artificial intelligence and Smart Energy, ICAIS 2023

作者： Sudha, V. Kalaiselvi, R. Jithenthiriya, C.K. Government Polytechnic College Dept. of Computer Engineering Coimbatore India Kumaraguru College of Technology Information Science and Engineering Coimbatore India Kumaraguru College of Technology Dept. Computer Science and Engineering Coimbatore India

ISBN: (纸本)9781665462167

Participation plays a key role in the classroom culture. When calling out the students' names at the beginning and end of a lecture, lecturers may miss a student, or someone may respond several times to substitute their peers. Face identification can be difficult when using low-definition video and other information systems with the assistance of facial recognition technologies. This necessitates the need to develop a novel device to quickly and accurately identify human faces from images and videos. Many algorithms and techniques have been recently developed to improve the facial recognition accuracy. Deep learning has been recently implemented in various real-time applications to identify and perceive multiple faces at the same time. When it comes to computers, however, it is unrealistic to attempt any of the human identity. The identification of the human identity is a critical aspect of biometrics. The biometric results are consistent with human characteristics. Remote and applied facial expressions can be used to enhance the results. Computers that identify and recognize faces can be used for a variety of purposes, including criminal recognition, network surveillance, biometric authentication, and so on. In this paper, an automated system for attendance recognition is proposed. © 2023 IEEE.

关键词： Face recognition

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Status and Application of Artificial intelligence-Based Cooperative Positioning and Navigation technology for UAV Clusters 1

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3rd international conference on Autonomous Unmanned Systems, ICAUS 2023

作者： Sheng, Danting Cheng, Jin Li, Fengyi Hao, Mingrui Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing100074 China Intelligent Science and Technology Academy Limited of CASIC Beijing100041 China

ISBN: (数字)9789819710911

ISBN: (纸本)9789819710904

Aiming at the UAV cluster cooperative navigation, this paper tries to summarize the development experience and existing results on two issues, namely, the application of filtering and artificial intelligence in UAV cluster cooperative navigation. The application of filtering in UAV cluster cooperative navigation briefly describes the application of Kalman filtering and extended Kalman filtering, traceless Kalman filtering and other nonlinear filters, intelligent optimization algorithms combined with particle filtering in cooperative navigation. Artificial intelligence Methods in Cooperative Navigation of UAV Clusters describes the application of deep feed-forward networks, brain-like information fusion methods based on integrated learning, multivariate interpolation of radial-based neural networks and Kalman filtering combined in the field of cooperative navigation. The results of existing applications of filtering and artificial intelligence in UAV cluster cooperative navigation are analyzed and summarized, and the future development of the field is outlooked. © Beijing HIWING Scientific and Technological Information Institute 2024.

关键词： Kalman filters

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Optimization of Milling robot Trajectory Based on Whale Optimization Algorithm 3rd

Optimization of Milling Robot Trajectory Based on Whale Opti...

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3rd international conference on Artificial intelligence, robotics, and Communication, ICAIRC 2023

作者： Zhou, Yang Li, Qingxin Sun, Yong Software College Shenyang University of Technology Shenyang China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang110016 China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110169 China

ISBN: (纸本)9789819721993

In response to the problem of vibration and low work efficiency during robot milling, taking into account the work indicators of milling time and stability, combined with the kinematic constraints of the robotic arm, the time impact optimization problem is transformed into a multi-objective optimization problem. The paper proposes an improved whale optimization algorithm, which introduces a differential mutation strategy to improve the problem of traditional whale algorithms easily getting stuck in local optima. Compared with traditional whale optimization algorithms, the improved whale algorithm significantly improves the convergence speed and accuracy during the milling process. Finally, it is verified by a solid robot. The results showed that the pulse value of the planned trajectory was reduced by up to 99.76%, and the efficiency was improved by 47.62%, effectively avoiding robot vibration during the milling process. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Multiobjective optimization

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Artificial intelligence in Wearables - Challenges and Opportunities in Physical Therapy and Sports Training 3

Artificial Intelligence in Wearables - Challenges and Opport...

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3rd international conference on Hybrid Human-Artificial intelligence, HHAI 2024

作者： Sorysz, Joanna RPTU Kaiserslautern-Landau Kaiserslautern Germany

ISBN: (纸本)9781643685229

Adherence to procedures and rules is essential in order to obtain the best results in medicine and sports. However, traditional clinical setups can induce stress in patients, hindering recovery. Meanwhile, advancements in activity recognition and monitoring technology have revolutionised the sports industry, yet systems suggesting exercises for performance improvement are sparse. At the same time, children training supervision is lacking comprehensive research altogether. In my research, I propose a project that aims to unify wearables solutions in physical therapy, sport training and children development. The key aspects of the research include the exploration of sensor modality fusion in order to obtain better results, body motion tracking, and physiological parameters recording. Planned experiments will focus on joint and torso movement mapping, integration with vital signs in order to perform real-life evaluations in cooperation with athletes, patients, coaches, and therapists. © 2024 The Authors.

关键词： Sports

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Business intelligence Model for Customer Targeting Using Fuzzy-C-Means and FP-Growth 3

Business Intelligence Model for Customer Targeting Using Fuz...

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3rd international conference on Emerging Smart Technologies and applications, eSmarTA 2023

作者： Ahmed Mohammed, Sam Abdulilah Saeed, Mogeeb A. Software Engineering Taiz University Taiz Yemen Computer Networks and Distributed Systems Taiz University Taiz Yemen

ISBN: (纸本)9798350305333

In the era of business, business intelligence (BI) technology can inform the decision-maker of the right data and insight. In this study, a business intelligence model is built to help the marketing department build an efficient promotion strategy. This paper aims to understand the impact of segmenting customers using the soft clustering technique (fuzz-c-means) based on their spending behavior or Recency, Frequency, and Monetary Model (RFM model) on product affiliation or market basket analysis to develop more efficient promotions to target customers. This aim is approached first by, downloading a dataset called online retail from Kaggle, exploring data to remove the missing value and detect and remove outliers, and constructing an RFM model (Recency, frequency, and monetary). Second, the clustering algorithm is performed fuzzy-c-means, to segment customers into clusters with similar characteristics. Third, product affiliation or association rules are obtained as per cluster using the FP-growth algorithm. Eventually, spending behavior is concluded to show a significant impact on product affiliation which means that clustering based on spending behavior increases the efficiency of market basket analysis (MBA). © 2023 IEEE.

关键词： Decision making

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Design of a Non-destructive Testing System based on Terahertz technology 3

Design of a Non-destructive Testing System based on Terahert...

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

作者： Yifei, Tang Zhen, Zhang Daxing, Dong Yannan, Yang Nanjing University of Aeronautics and Astronautics Nanjing China

ISBN: (纸本)9781665490788

Terahertz waves, electromagnetic waves possessing frequencies that fall within the range of 0.1 THz to 10 THz and wavelengths that span between 0.03 mm to 3 mm, have found their utility in various applications. It is, therefore, self-evident that the significance and imperative nature of deploying terahertz technology for non-destructive testing (NDT) cannot be overlooked. This article aims to acquaint the reader with a terahertz-based NDT system that comprises two parts, namely the hardware system and the software system, and explicate the operation principle of the system. Having successfully built the terahertz NDT system, diverse samples were subjected to testing. The results of these experiments reveal the suitability of the system for the inspection of different materials. In addition, surface imaging of composite structures was also performed, demonstrating the efficiency and precision of the terahertz NDT system in NDT. Consequently, the system presents a viable solution for the application of terahertz technology in the domain of NDT. © 2023 IEEE.

关键词： Nondestructive examination

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Design and Evaluation of a Medical Chatbot Built on BERT Language Model for Remote Health Assistance 3

Design and Evaluation of a Medical Chatbot Built on BERT Lan...

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3rd international conference for Innovation in technology, INOCON 2024

作者： Rao, D. Rajeswara Thottempudi, Kokila Surla, Bharath Kumar Satapathy, Ashutosh Velagapudi Ramakrishna Siddhartha Engineering College Department of Computer Science and Engineering Vijayawada India Velagapudi Ramakrishna Siddhartha Engineering College Department of Artificial Intelligence and Data Science Vijayawada India

ISBN: (纸本)9798350381931

Telemedicine refers to delivering healthcare services, including diagnosis, treatment, and consultations, remotely through digital communication tools such as video calls, phone calls, and online messaging. Access to quality healthcare remains a significant challenge in underserved rural areas worldwide. Due to transportation issues and financial support in remote areas, people can only visit hospitals close to their location. Current telemedicine applications provide video conversations with doctors but need more seamless services due to the huge population increase in cities and the unavailability of internet services for people in rural areas. This article presents a medical chatbot application trained on a customized health assistant corpus to generate fast responses in text format to queries related to common health issues. The solution is built on the BERT model to train the chatbot, which includes MLM and NSP, which is one of the best ways to obtain accurate results. The BERT model trained on customized health assessment corpus consists of multiple health assessment corpora and health assistant queries/responses collected from different sources and achieved 96.5% test accuracy. Since the model is pre-trained, it will generate the response as fast as possible. In addition to that, the application provides 24/7 availability, user-friendly interfaces, remote monitoring, and robust data security. © 2024 IEEE.

关键词： Rural areas

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Bias Inheritance and its Amplification in GAN-Based Synthetic Data Augmentation for Skin Lesion Classification 3

Bias Inheritance and its Amplification in GAN-Based Syntheti...

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3rd international conference on Artificial intelligence For Internet of Things, AIIoT 2024

作者： Jindal, Marut Singh, Birmohan Sant Longowal Institute of Engineering & Technology Deptt. of Computer Science & Engineering Sangrur India

ISBN: (纸本)9798350372120

Even with the increasing availability of high-quality public datasets, the shortage of training samples remains a primary hurdle in deep learning skin analysis. Generative Adversarial Networks (GANs) present a promising solution by generating synthetic skin lesion images that closely resemble real images. Numerous studies have investigated the potential of GANs in medical contexts, yet their applicability remains uncertain due to prevalent biases in biomedical datasets and associated risks. Initial experiments on skin lesion datasets have yielded unreliable outcomes, prompting the fundamental question: 'Is GAN truly beneficial for biomedical classification tasks?' Additionally, concerns about the amplification of dataset biases by AI models warrant further investigation into the inherent biases inherited by GANs. Considering these gaps, this study conducts experiments on skin lesion classification using four GAN architectures to assess their effectiveness in data generation, both conditional and unconditional. Among these models, StyleGAN2, when unconditionally applied, produced samples that contributed to classification improvement. Moreover, the visual analysis of generated samples revealed that GANs tend to amplify the existing biases with high distribution while suppressing those with low distribution. These findings highlight the limited efficacy of GAN-based augmentation for skin lesion classification in specific scenarios. Thus, caution is advised against the widespread adoption of GANs in medical applications due to computational costs and associated risks. © 2024 IEEE.

关键词： Generative adversarial networks

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