Ji-yang Yu, Dan Huang, Jinyang Li, Wenjie Li, Xianjie Wang, Xiaolong Shi
{"title":"Parallel and Accelerated Feature Extraction of Manipulative Scene of Space Dim Target","authors":"Ji-yang Yu, Dan Huang, Jinyang Li, Wenjie Li, Xianjie Wang, Xiaolong Shi","doi":"10.1109/ICCAR57134.2023.10151744","DOIUrl":"https://doi.org/10.1109/ICCAR57134.2023.10151744","url":null,"abstract":"Aiming at the problems of difficult feature extraction and high real-time requirement for weak targets in space manipulation scenes, this paper designed a parallel stream HOG feature computing architecture based on multi-cache interaction, and adopted cell stream splitting and multi-angle interval parallel computing methods to improve the degree of parallelism. The whole architecture adopts 16-bit fixed-point base calculation, transcendental function combined with polynomial expansion and table lookup method to improve the calculation accuracy. 16 detection windows at the same time, the use of parallel computing, effectively improve the response to more than $mathbf{1024times 1024}$ pixels high-definition camera real-time computing applications. After testing the data with low signal-to-noise ratio, the error from theoretical calculation is less than 3%. The experimental verification shows that compared with previous designs, the proposed method occupies the same number of resources except Block RAM, and the computational efficiency is increased by at least 57.2%.","PeriodicalId":347150,"journal":{"name":"2023 9th International Conference on Control, Automation and Robotics (ICCAR)","volume":"181 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124286459","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Yubing Wang, Weijia Wang, Boyang Zhang, Jingye Peng, Luo Han
{"title":"Review on the Research Status of Intelligent Level Classification","authors":"Yubing Wang, Weijia Wang, Boyang Zhang, Jingye Peng, Luo Han","doi":"10.1109/ICCAR57134.2023.10151731","DOIUrl":"https://doi.org/10.1109/ICCAR57134.2023.10151731","url":null,"abstract":"The intelligent level grading standard plays a basic, supporting and leading role in the development of artificial intelligence. Based on the development status of artificial intelligence, this paper combs and summarizes the classification standards and evaluation methods of intelligent level. Firstly, the basic concept of artificial intelligence, the classification of intelligent level and the significance of classification are discussed. Secondly, taking different application fields of artificial intelligence as the research object, this paper focuses on the classification of intelligent level, typical characteristics and evaluation methods in the fields of unmanned system, network, industrial automation instruments and intelligent products. Finally, the development prospect of intelligent level classification and evaluation is given, which provides a new research direction for intelligent level classification and evaluation.","PeriodicalId":347150,"journal":{"name":"2023 9th International Conference on Control, Automation and Robotics (ICCAR)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116528392","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Reliability Analysis and Cloud-aided Health Management for Electric Locomotive Vehicle Circuit Board","authors":"Bing Shang, Zhuoyun Li, Zhi Qi","doi":"10.1109/ICCAR57134.2023.10151717","DOIUrl":"https://doi.org/10.1109/ICCAR57134.2023.10151717","url":null,"abstract":"This work proposes a method for predicting the life of a circuit board based on circuit board reliability analysis and cloud-aided temperature. Firstly, a digital prototype of the circuit board for the circuit locomotive is established, the operating conditions of the circuit locomotive are collected, and thermal simulations are performed based on the characteristics of the working conditions. Next, the Failure Mode Mechanism and Effects Analysis (FMEA) method is used to conduct failure mechanism analysis on the circuit board to analyze its underlying failure physical model for reliability. Based on the physical failure model, the circuit board's reliability analysis and life prediction are performed according to the thermal, and the weak points in the design are identified. Finally, a thermocouple sensor is used to collect the temperature of the weak point of the circuit board, which is uploaded to the server through the 5G module for real-time monitoring of the circuit board's status. The circuit board's thermal simulation and vibration simulation analysis identified four high-temperature areas in the circuit board, which are the primary mode of circuit board failure caused by solder joint cracking, easily affected by temperature cycle conditions. By adding a temperature sensor to the weak point, real-time collection and detection of the circuit board's temperature are achieved. Compared with traditional reliability analysis methods, this method can realize real-time monitoring of weak points and provide a circuit board product improvement plan.","PeriodicalId":347150,"journal":{"name":"2023 9th International Conference on Control, Automation and Robotics (ICCAR)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122490991","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Task Allocation Method for Multiple Unmanned Marine Vehicles Cooperative Formation","authors":"Jie Wu, Zikang Hao, Zhenning Z Liu, Yanyan Li","doi":"10.1109/ICCAR57134.2023.10151719","DOIUrl":"https://doi.org/10.1109/ICCAR57134.2023.10151719","url":null,"abstract":"The cluster operation of unmanned marine vehicle (UMV) has become an important trend in the future with the development of marine industry. Nevertheless, the existing methods have several problems such as delayed task allocation, slow convergence and tendency to fall into local optimization. Therefore, a new task allocation method is proposed to control oil pollution, which closely combines the tour planning process with the task allocation process. Firstly, Hungarian Algorithm (HA) is used to establish Multi-UMV cost matrix. Secondly, Ant Colony Optimization (ACO) is used to solve the tour planning problems. Finally, it is feasible to get the result of the shortest closed-loop itinerant path. The simulation results show that the total track length is reduced by 15.13%, and the average running time is reduced by 46.57%, which can be used to improve the rationality of task allocation.","PeriodicalId":347150,"journal":{"name":"2023 9th International Conference on Control, Automation and Robotics (ICCAR)","volume":"63 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123376258","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Global Information Attention Based Dual-Pathway Network for Oxidized Slag Segmentation of Metal Ingot Images","authors":"Degang Xu, Ao Zhang, Xuming Liu, Jie Wu","doi":"10.1109/ICCAR57134.2023.10151743","DOIUrl":"https://doi.org/10.1109/ICCAR57134.2023.10151743","url":null,"abstract":"The content of oxidized slag on the surface of metal ingot is the key to judge whether the metal ingot is qualified. However, it is still a challenge to determine the covering area of oxidized slag on the surface of metal ingot. In this paper, we proposed a novel Global Information Attention based dual-pathway Network (GANet) consists of context and edge pathways to segment oxidized slag on the metal ingot surface image. Specifically, to suppress the interference of background on oxidized slag segmentation, we propose novel Fusion Attention Module (FAM) and Global Position Attention Module (GPA), which can effectively aggregate global semantic information and improve segmentation performance. Meanwhile, we designed the edge pathway and Edge Perception Module (EPM) to extract the boundary information of the oxidized slag. The experimental results show that the performance of the GANet is better than the existing segmentation methods which proves the effectiveness of the proposed method and provides a research idea for the automation of metal casting process.","PeriodicalId":347150,"journal":{"name":"2023 9th International Conference on Control, Automation and Robotics (ICCAR)","volume":"118 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114210273","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Multi-Time-Stage Collaborative Task Assignment for Heterogeneous UAVs Using CBBA","authors":"Wenfei Wang, L. Ru, M. Lv, B. Lu","doi":"10.1109/ICCAR57134.2023.10151699","DOIUrl":"https://doi.org/10.1109/ICCAR57134.2023.10151699","url":null,"abstract":"Aiming at the cooperative task assignment problem of heterogeneous multiple UAVs in different time stages of cooperative operation, firstly, the cooperative multitask assignment model was established by comprehensively considering the extension of constraint conditions. Secondly, considering the heterogeneous cooperative matching execution relationship of multiple UAVs in different stages of various tasks, the consensus-based bundle algorithm (CBBA) was extended. A multistage cooperative task assignment algorithm for heterogeneous multi-UAVs (heterogeneity - synergy consensus-based bundle algorithm, HS-CBBA) was proposed to realize the constraint relationship that different target tasks are coordinated executed by various heterogeneous UAVs at different execution time stages. Finally, the feasibility and effectiveness of the HS-CBBA algorithm in solving the multistage cooperative task assignment problem of heterogeneous multi-UAV execution are verified by experimental simulation.","PeriodicalId":347150,"journal":{"name":"2023 9th International Conference on Control, Automation and Robotics (ICCAR)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126554499","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Prescribed Performance Global Consensus Control of Non-Affine Multi-Agent Networks","authors":"Ningli Wang, Xiaolin Wang, Wenjie Tian, Lei Zhang","doi":"10.1109/ICCAR57134.2023.10151721","DOIUrl":"https://doi.org/10.1109/ICCAR57134.2023.10151721","url":null,"abstract":"This work studies the prescribed performance global consensus control problem for non-affine nonlinear multi-agent networks whose topologies are directed switching. The core characteristic of the presented method lies in the introduction of a new piecewise differentiable function, which not only renders the consensus errors zero at each switching time instant, but against the unexpected controller action at switching time instant. Based on this, a low-complexity reconstructed mechanism was devised for each agent which achieves fully distributed manner. The consensus errors can be regulated to a prespecified arbitrary small residual set. Simulations are performed to validate the effectiveness of the acquired results.","PeriodicalId":347150,"journal":{"name":"2023 9th International Conference on Control, Automation and Robotics (ICCAR)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134156293","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Motor Fault Diagnosis of a Brushless DC Motor Using Fast Kurtogram on Convolutional Neural Network","authors":"Joselito A. Flores, C. Ostia","doi":"10.1109/ICCAR57134.2023.10151730","DOIUrl":"https://doi.org/10.1109/ICCAR57134.2023.10151730","url":null,"abstract":"DC motors are widely applied as reliable industrial machines. However, it may fail due to some defects, unfitting operations, or mechanical wear. Motor maintenance is necessary. To achieve this, detection of a probable problem such as a broken motor part before progressive problems occur. Detection of faults from a motor is the new trend to classify broken components of a motor. In this study, 2DCNN is classifying BLDC motor faults is used and determining its performance. By integrating the Fast Kurtogram algorithm as feature extraction, healthy and faulty signals can be converted into an image for the 2DCNN fault diagnostic algorithm. The fault-finding model was developed, and it classified healthy motor faults such as bearing, winding, and rotor faults with an overall accuracy of 83 percent. The superior performance of the 2DCNN model is evident compared to 1DCNN.","PeriodicalId":347150,"journal":{"name":"2023 9th International Conference on Control, Automation and Robotics (ICCAR)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133503437","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Yurou Chen, Ji-yang Yu, Liancheng Shen, Zhenyang Lin, Zhiyong Liu
{"title":"Vision-Based High-Precision Assembly with Force Feedback","authors":"Yurou Chen, Ji-yang Yu, Liancheng Shen, Zhenyang Lin, Zhiyong Liu","doi":"10.1109/ICCAR57134.2023.10151762","DOIUrl":"https://doi.org/10.1109/ICCAR57134.2023.10151762","url":null,"abstract":"Assembling objects in unstructured scenarios re-quires accurate 3D position estimation, which presents a sig-nificant challenge in achieving high-precision manipulation. This paper proposes a method to reduce positioning errors in high-precision assembly problems by combining visual and force feedback. Our approach leverages the strengths of both sensors by analyzing visual positioning characteristics and using force feedback to locate the target position during inaccuracies. We evaluate our approach through experiments of inserting a nut onto a screw without threading, conducted in both simulation and real-world scenarios. Our results demonstrate an improvement in the assembly success rate compared to previous methods.","PeriodicalId":347150,"journal":{"name":"2023 9th International Conference on Control, Automation and Robotics (ICCAR)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129483012","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Tool Path Interpolation Method in Five-Axis CNC Machining","authors":"Jinjie Wang, Cong Geng, Dapeng Geng, Han Zhang","doi":"10.1109/ICCAR57134.2023.10151741","DOIUrl":"https://doi.org/10.1109/ICCAR57134.2023.10151741","url":null,"abstract":"Problems of program-redundancy and speed-discontinuity can be aroused in linear interpolation, which may have an effect on machining efficiency. In order to avoid these kinds of problems, a tool path interpolation method suitable for five-axis Computer Numerical Control (CNC) machining is presented in this paper. The machining part is divided into continuous blocks and discontinuous blocks. Tool positions and tool orientations in the continuous blocks are fitted respectively. The parametric relationship between tool orientations and tool positions are analyzed, which makes real-time interpolation of tool path be possible. Results show that the method can maintain continuity of the velocity and acceleration of rotation axes and enhance machining efficiency.","PeriodicalId":347150,"journal":{"name":"2023 9th International Conference on Control, Automation and Robotics (ICCAR)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129621350","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}