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VGRISys: A Vision-Guided Robotic Intelligent System for Autonomous Instrument Calibration

VGRISys: A Vision-Guided Robotic Intelligent System for Auto...

引用

2023 IEEE international conference on robotics and Biomimetics, ROBIO 2023

作者： Li, Zhenqi Wang, Hewei Li, Yijie Dev, Soumyabrata Zuo, Guoyu Beijing University of Technology Beijing-Dublin International College Beijing100124 China University College Dublin School of Computer Science Dublin Ireland Beijing University of Technology Faculty of Information Technology Beijing100124 China Beijing Key Laboratory of Computing Intelligence and Intelligent Systems Beijing100124 China

ISBN: (纸本)9798350325706

With the increasing sophistication of musical instruments and the importance of precise tuning, a novel and efficient approach to instrument calibration is of significant necessity. This paper presents VGRISys, an innovative system leveraging robotics and artificial intelligence to facilitate the intricate process of instrument tuning. VGRISys incorporates a multi-axis robotic arm, meticulously engineered for fine-tuned physical interaction with various musical instruments, alongside an intelligent system that guides the robotic arm using real-time audio feedback analysis. In addition, it employs advanced signal processing and machine learning algorithms, allowing the system to identify pitch discrepancies and respond with appropriate corrective action. VGRISys remarkably reduces the time required for instrument tuning, thus improving efficiency and democratizing access to high-quality tuning. Furthermore, the system's machine learning capabilities allow it to refine its tuning process over repeated operations, providing a scalable solution to the ever-evolving complexities of instrument tuning. The exploration and development of VGRISys contribute significantly to the wider fields of robotics, artificial intelligence, and music technology. © 2023 IEEE.

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Verification Method of Intelligent Prosthetic Algorithm Based on Anthropomorphic Walking Robot 3

Verification Method of Intelligent Prosthetic Algorithm Base...

引用

3rd international conference on robotics, Automation and Artificial intelligence (RAAI)

作者： An, Honglei Sun, Lei Ma, Hongxu Wei, Qing Natl Univ Def Technol Coll Intelligence Sci & Technol Changsha Peoples R China

ISBN: (纸本)9798350307573;9798350307566

A key issue in the research of intelligent prosthetics is the verification and analysis of the proposed prosthetic motion planning and control methods. In this paper, it is proposed that using a humanoid walking robot as the subject can effectively test the interaction dynamics between the prosthesis and the human body. This method also avoids the risk of injury to amputee patients when participating in the test before the control method is mature. Specifically, the anthropomorphic walking of bipedal walking robots is first realized, and a testbed that fully simulates the straight leg walking is obtained. The right leg (below the thigh) of the bipedal robot is then replaced with an intelligent prosthesis. When testing the planning and control methods of intelligent prosthetics, prosthetic controllers run independently. The bipedal walking robot, except for the part below the right thigh, normally performs the "humanoid motion controller". Effective intelligent prosthetic control methods will make the prosthesis-"human" coupling system produce smooth walking movements, while ineffective intelligent prosthetic control will cause the coupling system to fall due to strong interference.

关键词： verification intelligent prosthesis anthropomorphic walking virtual constraint

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Temporal Alignment of Multi-Dimensional Asynchronous Data for Digital Twin Evolutionary analysis 6

Temporal Alignment of Multi-Dimensional Asynchronous Data fo...

引用

6th international conference on robotics, Intelligent Control and Artificial intelligence, RICAI 2024

作者： Fang, Chenglong Sun, Jinlong Liu, Gaohe Zhang, Jiaji Gui, Shuqiang Wang, Qiankun School of Communications and Information Engineering Nanjing University of Posts and Telecommunications Nanjing China State Grid Dingxi Power Supply Company Nanjing China School of Civil Engineering and Architecture Wuhan University of Technology Wuhan China MCC Wukan Engineering Technology Co. Ltd Wuhan China

ISBN: (纸本)9798331541699

Digital twin technology is widely used in smart industries and other fields. However, analyzing its evolution in complex scenarios faces challenges in collecting and merging data, particularly in achieving precise data time alignment. Existing methods often struggle with diverse data types and frequencies. This paper introduces a new method for aligning multi-dimensional asynchronous data in digital twin evolution analysis. This approach ensures time alignment and frequency consistency through techniques such as filling null values, intelligent interpolation, and resampling. Key contributions include BiLSTM-based interpolation and flexible adjustment of data granularity. These advancements effectively address the challenge of data time alignment in digital twin evolution analysis, thereby improving data quality and alignment accuracy. The proposed method supports reliable data processing for tasks such as anomaly detection, accelerated evolution, and decision-making. Experimental results demonstrate its capability to recover data with severely damaged features, thereby advancing digital twin evolution analysis in complex scenarios. © 2024 IEEE.

关键词： Spatio-temporal data

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Online Driving Style analysis Based on Genetic Algorithm and CatBoost 4

Online Driving Style Analysis Based on Genetic Algorithm and...

引用

4th international conference on Artificial intelligence, robotics, and Communication, ICAIRC 2024

作者： Yu, Haowei Zou, Lin Wei, Yiying Xiong, Zhiyuan Wuhan University of Technology Faculty of Mechanical and Electrical Engineering Wuhan China

ISBN: (纸本)9798331531225

Accurate driving behavior analysis can not only greatly improve driving safety and driver comfort, but also facilitate the development of trajectory planning, abnormal driving detection and other applications. The previous driving style analysis required the complete timing data of the driver, which could not be extracted in real time. This paper presents an online driving style analysis method, which is mainly divided into two parts. The first part is driving data segmentation and clustering based on K-means and genetic algorithm. Different subsequences are obtained by sliding window segmentation. The total KL divergence within the cluster is taken as the objective function, and the sub-sequence clustering results are obtained by genetic algorithm. Then, according to the final clustering results, the driving style of drivers is measured from three dimensions: statistical index, cospin similarity and KL divergence. The second part is the online driving primitive extraction model. According to the clustering results (labeled data) obtained in the first part, different machine learning models are trained, and the performance of random forest, KNN, SVM and CatBoost models is compared. Through the trained machine learning model, we are able to extract driving primitives in real time. The experimental results show that the first part can extract driving primitive and analyze driving style, and the second part CatBoost achieves better results than other machine learning models, with prediction accuracy of 0. 8, recall rate of 0. 82 and f1_score of 0. 81. © 2024 IEEE.

关键词： Genetic algorithms

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Vibration analysis and Test of Working Arm of the Anchor Drilling Robot 17th

Vibration Analysis and Test of Working Arm of the Anchor Dri...

引用

17th international conference on Intelligent robotics and Applications

作者： Zhou, Xu You, Qihang Wang, Xin Zhang, Licai An, Siyuan Zhu, Aibin Northwestern Polytech Univ Sch Mech Engn Xian Shaanxi Peoples R China Shanxi Tiandi Coal Min Machinery Co Ltd Taiyuan Shanxi Peoples R China Changan Univ Sch Construct Machinery Xian Shaanxi Peoples R China Xi An Jiao Tong Univ Sch Mech Engn Xian Shaanxi Peoples R China

ISBN: (纸本)9789819607709;9789819607716

Aiming at the problems of complex and harsh working environments and low reliability of the working arm of the anchor drilling robot, the dynamic characteristics of the working arm are studied based on the dynamic simulation analysis and vibration test analysis. In view of the influence of working load and deformation on the rigidity of the working arm, the static finite element analysis is implemented by simulating the actual working conditions. The stress and strain distribution of the working arm under the roof anchor drilling condition is derived, and on this basis, the modal analysis of the working arm with pre-stress is carried out. The six orders of vibration mode and the corresponding inherent frequencies are obtained. A vibration test system of the working arm is set up to achieve the three-dimensional vibration accelerations of the working arm under the roof anchor drilling condition. The fast Fourier transform of the vibration acceleration signals is conducted to obtain the vibration spectrum. The dynamic characteristics of the working arm are analyzed through the vibration frequency and the inherent frequency, which is of great reference value for improving the reliability of the working arm.

关键词： Working arm Anchor drilling robot Vibration analysis

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Automated Biofloc Technology for Fish Farming with GSM based Monitoring System 3

Automated Biofloc Technology for Fish Farming with GSM based...

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3rd IEEE international conference on robotics, Automation, Artificial-intelligence and Internet-of-Things, RAAICON 2024

作者： Hassain, Md Mehedi Gani, Muhammad Osman Rahman, Abdur Hasnat, S.M. Rahbar Abdullah International Islamic University Chittagong Dept. of Electrical & Electronics Engineering Chittagong Bangladesh East Delta University Dept. of Electrical & Electronics Engineering Chittagong Bangladesh

ISBN: (纸本)9798331534400

Biofloc technology mitigates aquaculture's environmental impact by using microbial flocs to convert organic waste into nutrient rich feed. To enhance water quality management, our research focuses on a GSM based monitoring system for real time data collection and analysis. The system integrates pH, temperature, and ultrasonic sensors with an Arduino Uno microcontroller, GSM module, servo, and pump motors to monitor and regulate water quality. The system measures timely and crucial data on water quality, including parameters such as temperature, pH levels, and the state of the feeding box. The pH and temperature sensors provide analog readings, while the ultrasonic sensor monitors feeding box levels. Food management is controlled by a servo motor that operates the feeding box, and a pump motor maintains water quality. The system uses temperature and pH sensors for rapid hazard detection, minimizing ammonia and nitrite buildup risks. The GSM module enables real time data connectivity, allowing users to track and control system operations remotely. This study empowers fish farmers and hobbyists with real-time water quality data, promoting informed decision-making to enhance aquatic health and productivity. It offers valuable insights to the broader aquaculture community. © 2024 IEEE.

关键词： Decision making

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Incentivizing Participation in SplitFed Learning: Convergence analysis and Model Versioning 44

Incentivizing Participation in SplitFed Learning: Convergenc...

引用

44th IEEE international conference on Distributed Computing Systems (ICDCS)

作者： Han, Pengchao Huang, Chao Shi, Xingyan Huang, Jianwei Liu, Xin Guangdong Univ Technol Sch Informat Engn Guangzhou Peoples R China Univ Calif Davis Dept Comp Sci Davis CA USA Chinese Univ Hong Kong Sch Data Sci Shenzhen Peoples R China Chinese Univ Hong Kong Sch Sci & Engn Shenzhen Inst Artificial Intelligence & Robot Soc Shenzhen Peoples R China

ISBN: (纸本)9798350386066;9798350386059

In SplitFed learning (SFL), a global model is split into two segments, where distributed clients train the first segment in a federated manner and a main server trains the other. Existing studies focus on algorithm development but ignore the important issue of incentives, without which self-interested clients may be unwilling to participate. We fill this gap by presenting a first incentive study in SFL. One challenge is that the design requires an understanding of how clients' participation affects the model performance. To this end, we provide a first convergence analysis for SFL considering partial client participation to guide the mechanism design. Another challenge is that monetary payment may not be viable for large distributed systems. To this end, we propose a model-versioning mechanism where the main server assigns different versions of models (of different qualities) to clients as incentives. The design is further complicated by clients' multi-dimensional private information. To this end, we design the model-versioning mechanism so that it decouples clients' decisions and admits a weakly dominant strategy at equilibrium. We prove that our mechanism is feasible, effective, and incentive compatible. Experimental results show that our mechanism greatly improves client participation and model accuracy compared to a benchmark.

关键词： Federated learning

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Meshing Statics and Modification analysis of Spur Gear Based On ABAQUS 5

Meshing Statics and Modification Analysis of Spur Gear Based...

引用

5th international conference on robotics, Intelligent Control and Artificial intelligence, RICAI 2023

作者： Zhou, Shengmao Yin, Xin Hu, Hongshuai Yang, Guanglu Bai, Shuchao Zhang, Dehai School of Mechanical and Electrical Engineering Zhengzhou University of Light Industry Henan Province Zhengzhou City China China Tobacco Henan Industrial Co. LTD. Henan Province Zhengzhou City China

ISBN: (纸本)9798350357950

Gear transmission is an important transmission mode, which has the advantages of high transmission efficiency, simple production and high transmission speed, and is widely used in aviation, ships, high-speed rail and other fields. However, due to the influence of factors such as manufacturing accuracy, installation accuracy and complex working conditions, gear often produces large vibration deformation in the process of meshing movement, which will not only produce noise, but also have a huge impact on the accuracy and service life of the machine, in order to weaken the impact of countries put forward a series of practice methods. In this paper, based on ABAQUS finite element analysis, the stress and strain analysis of gear transmission is carried out, and the corresponding modification method is proposed. © 2023 IEEE.

关键词： abaqus gear modification stress-strain analysis

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Towards Symbiotic Creativity: A Methodological Approach to Compare Human and AI Robotic Dance Creations 32

Towards Symbiotic Creativity: A Methodological Approach to C...

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32nd international Joint conference on Artificial intelligence (IJCAI)

作者： De Filippo, Allegra Giuliani, Luca Mancini, Eleonora Borghesi, Andrea Mello, Paola Milano, Michela Univ Bologna DISI Bologna Italy

ISBN: (纸本)9781956792034

Artificial intelligence (AI) has gradually attracted attention in the field of artistic creation, resulting in a debate on the evaluation of AI artistic outputs. However, there is a lack of common criteria for objective artistic evaluation both of human and AI creations. This is a frequent issue in the field of dance, where different performance metrics focus either on evaluating human or computational skills separately. This work proposes a methodological approach for the artistic evaluation of both AI and human artistic creations in the field of robotic dance. First, we define a series of common initial constraints to create robotic dance choreographies in a balanced initial setting, in collaboration with a group of human dancers and choreographer. Then, we compare both creation processes through a human audience evaluation. Finally, we investigate which choreography aspects (e.g., the music genre) have the largest impact on the evaluation, and we provide useful guidelines and future research directions for the analysis of interconnections between AI and human dance creation.

关键词： robotics

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Fault Diagnosis of Quadruped Robot Joint Modules Based on TDIC and Random Forest 5

Fault Diagnosis of Quadruped Robot Joint Modules Based on TD...

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5th international conference on Sensing, Measurement and Data Analytics in the Era of Artificial intelligence, ICSMD 2024

作者： Chen, Yufan Fan, Beibei Xiong, Xin Shi, Mapping School of Mechatronic Engineering and Automation Shanghai University Shanghai China Shanghai Key Laboratory of Intelligent Manufacturing and Robotics Shanghai China

ISBN: (纸本)9798331529192

As robotics technology advances, quadruped robots are increasingly instrumental in diverse applications, including rescue operations and healthcare. However, the intricate operating conditions expose the components within the joint modules of these robots to alternating and impact loads. Consequently, research into signal processing and fault diagnosis techniques for planetary gearboxes in joint modules holds significant engineering importance. Given the challenges associated with fault signal extraction from planetary gearboxes, this study proposes a novel fault feature extraction method based on Time-Dependent Intrinsic Correlation (TDIC), integrated with a random forest classifier for fault classification. This approach leverages signal frequency analysis to adaptively extract segments characterized by high correlation among different physical field signals as fault features. The random forest model is utilized for fault classification and its performance is compared against CNN, KNN, and XGBoost models. Experimental results validate the superior fault classification efficacy of the proposed method. © 2024 IEEE.

关键词： Multipurpose robots

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