Pub Date : 2023-07-01DOI: 10.1109/CACRE58689.2023.10208536
Fuchun Liu, Zeyong Liu, Xiangyang Li, Dong Jiang
This paper addresses the active alignment problem in manufacturing solid-state LiDAR systems and focuses on image processing and alignment algorithms within a visual laser auto-collimation platform. By extracting features from laser spot images, a non-linear discrete optimization is applied to determine the optimal position of the laser emitter, minimizing the laser beam divergence angle. To overcome the challenge of inaccurate size extraction of Fraunhofer diffraction patterns, Gaussian filtering, adaptive thresholding, and circle fitting based on distance transformation are employed to estimate the spot size. Active alignment algorithms are implemented using improved hill climbing, genetic, and curve fitting algorithms. Experimental comparisons demonstrate that the curve fitting-based active alignment algorithm achieves better efficiency and stability, with an average adjustment count of 29.35 and a variance of 97.50.
{"title":"Laser Active Alignment Algorithm based on Spot Features and Curve Fitting","authors":"Fuchun Liu, Zeyong Liu, Xiangyang Li, Dong Jiang","doi":"10.1109/CACRE58689.2023.10208536","DOIUrl":"https://doi.org/10.1109/CACRE58689.2023.10208536","url":null,"abstract":"This paper addresses the active alignment problem in manufacturing solid-state LiDAR systems and focuses on image processing and alignment algorithms within a visual laser auto-collimation platform. By extracting features from laser spot images, a non-linear discrete optimization is applied to determine the optimal position of the laser emitter, minimizing the laser beam divergence angle. To overcome the challenge of inaccurate size extraction of Fraunhofer diffraction patterns, Gaussian filtering, adaptive thresholding, and circle fitting based on distance transformation are employed to estimate the spot size. Active alignment algorithms are implemented using improved hill climbing, genetic, and curve fitting algorithms. Experimental comparisons demonstrate that the curve fitting-based active alignment algorithm achieves better efficiency and stability, with an average adjustment count of 29.35 and a variance of 97.50.","PeriodicalId":447007,"journal":{"name":"2023 8th International Conference on Automation, Control and Robotics Engineering (CACRE)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133986325","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}
Pub Date : 2023-07-01DOI: 10.1109/CACRE58689.2023.10208327
Yuanlin Yang, Wei Meng
With the help of 5G network technology, the physical system (PS) can communicate with its virtual system (VS) in real-time. This high-speed communication is particularly advantageous for robots such as Quadrotors which operate over large distances. Digital twin (DT) technology concerns the relationship between PS and VS. In the VS, simulation technology allows states of virtual objects to be fully captured, and further input schemes can be designed to simulate additional states. Therefore, simulation results are utilized to enhance the decision-making capabilities of physical objects. In this paper, the VS serves as an online decision-making center, providing auxiliary decision-making services to physical objects taking into account of communication delays during the interaction process between PS and VS. Two types of experiments are conducted to test the proposed auxiliary decision-making strategy with VS participation. Using the Quadrotor as a physical object, two type experiments are conducted to verify the proposed strategy, including virtual simulation experiment and physical machine testing. The experimental results demonstrate that the Quadrotor in PS can successfully accomplish its mission under the guidance of the VS. Moreover, successful outdoor testing of the physical machine with 5G network has been conducted.
{"title":"Auxiliary Decision-Making Strategy for Physical Quadrotor by Actively Interacting with Virtual System","authors":"Yuanlin Yang, Wei Meng","doi":"10.1109/CACRE58689.2023.10208327","DOIUrl":"https://doi.org/10.1109/CACRE58689.2023.10208327","url":null,"abstract":"With the help of 5G network technology, the physical system (PS) can communicate with its virtual system (VS) in real-time. This high-speed communication is particularly advantageous for robots such as Quadrotors which operate over large distances. Digital twin (DT) technology concerns the relationship between PS and VS. In the VS, simulation technology allows states of virtual objects to be fully captured, and further input schemes can be designed to simulate additional states. Therefore, simulation results are utilized to enhance the decision-making capabilities of physical objects. In this paper, the VS serves as an online decision-making center, providing auxiliary decision-making services to physical objects taking into account of communication delays during the interaction process between PS and VS. Two types of experiments are conducted to test the proposed auxiliary decision-making strategy with VS participation. Using the Quadrotor as a physical object, two type experiments are conducted to verify the proposed strategy, including virtual simulation experiment and physical machine testing. The experimental results demonstrate that the Quadrotor in PS can successfully accomplish its mission under the guidance of the VS. Moreover, successful outdoor testing of the physical machine with 5G network has been conducted.","PeriodicalId":447007,"journal":{"name":"2023 8th International Conference on Automation, Control and Robotics Engineering (CACRE)","volume":"151 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132754497","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}
Pub Date : 2023-07-01DOI: 10.1109/CACRE58689.2023.10209022
Alok Kumar, A. Kelkar
In many complex dynamical system analyses, it is essential to understand the dynamic behavior of the states as accurately as possible. Considering the uncertain environment, it is important to be able to predict how the uncertainties in the inputs will propagate in the system dynamics and will affect the system’s performance. Such information provides an important analysis for systems’ operation and stability analysis. This paper proposes an approach for uncertainty propagation analysis using the Koopman operator theory for uncertain inputs for the dynamical systems. The uncertain input can be characterized by the probability distribution function (PDF). For linear dynamical systems, uncertainty propagation analysis is obtained using an analytical expression for the first and second moment, i.e., mean and variance. This paper extends the same concept to linear dynamical systems using the Koopman operator theory, which involves the computation of the Koopman eigenfunctions. The efficacy of the proposed approach is demonstrated using linear quarter car dynamics simulations showing the mean and variance propagation of the states. A comparison is provided between our proposed approach with the Monte Carlo simulations for computing mean and variance propagation for bench-marking the efficacy of the approach.
{"title":"Uncertainty Propagation in Dynamical Systems Using Koopman Eigenfunctions","authors":"Alok Kumar, A. Kelkar","doi":"10.1109/CACRE58689.2023.10209022","DOIUrl":"https://doi.org/10.1109/CACRE58689.2023.10209022","url":null,"abstract":"In many complex dynamical system analyses, it is essential to understand the dynamic behavior of the states as accurately as possible. Considering the uncertain environment, it is important to be able to predict how the uncertainties in the inputs will propagate in the system dynamics and will affect the system’s performance. Such information provides an important analysis for systems’ operation and stability analysis. This paper proposes an approach for uncertainty propagation analysis using the Koopman operator theory for uncertain inputs for the dynamical systems. The uncertain input can be characterized by the probability distribution function (PDF). For linear dynamical systems, uncertainty propagation analysis is obtained using an analytical expression for the first and second moment, i.e., mean and variance. This paper extends the same concept to linear dynamical systems using the Koopman operator theory, which involves the computation of the Koopman eigenfunctions. The efficacy of the proposed approach is demonstrated using linear quarter car dynamics simulations showing the mean and variance propagation of the states. A comparison is provided between our proposed approach with the Monte Carlo simulations for computing mean and variance propagation for bench-marking the efficacy of the approach.","PeriodicalId":447007,"journal":{"name":"2023 8th International Conference on Automation, Control and Robotics Engineering (CACRE)","volume":"13 18","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133204308","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}
Pub Date : 2023-07-01DOI: 10.1109/CACRE58689.2023.10209034
Yuqi Zhu, S. Dian, Xingxing You, Xuke Zhong, Yuxing Xiong, Hailong Hu
This work presents a proposed controller based on a generalized linear extended state observer (GLESO) for continuum robots (CR) facing unmatched uncertainties in trajectory tracking. The complex structure of CRs makes accurate modeling difficult, especially when operating in unknown environments. Internal and external uncertainties further impact the control performance, particularly the unmatched uncertainties. To address this, the GLESO is employed to observe and compensate for the unmatched uncertainties. Additionally, a tailored slide mode controller (SMC) is introduced to achieve stabilized control. Numerical simulations are conducted to validate the effectiveness of the proposed method.
{"title":"Generalized Linear Extended State Observer based Trajectory Tracking Control for Continuum Robots with Unmatched Uncertainties","authors":"Yuqi Zhu, S. Dian, Xingxing You, Xuke Zhong, Yuxing Xiong, Hailong Hu","doi":"10.1109/CACRE58689.2023.10209034","DOIUrl":"https://doi.org/10.1109/CACRE58689.2023.10209034","url":null,"abstract":"This work presents a proposed controller based on a generalized linear extended state observer (GLESO) for continuum robots (CR) facing unmatched uncertainties in trajectory tracking. The complex structure of CRs makes accurate modeling difficult, especially when operating in unknown environments. Internal and external uncertainties further impact the control performance, particularly the unmatched uncertainties. To address this, the GLESO is employed to observe and compensate for the unmatched uncertainties. Additionally, a tailored slide mode controller (SMC) is introduced to achieve stabilized control. Numerical simulations are conducted to validate the effectiveness of the proposed method.","PeriodicalId":447007,"journal":{"name":"2023 8th International Conference on Automation, Control and Robotics Engineering (CACRE)","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132564902","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}
Pub Date : 2023-07-01DOI: 10.1109/CACRE58689.2023.10208685
Yiming Zhong, Caoyang Yu, Junjun Cao, Chunhu Liu, L. Lian
This paper presents a comprehensive approach to augment the control performance of unmanned surface vehicles (USVs), addressing two core issues: dynamics modeling and control of USVs. To bolster the precision of dynamics modeling, the paper introduces a parameter identification algorithm based on the nonlinear multi-innovation least-squares method (NMILS). NMILS helps mitigate the noise influence and enhances the precision of the dynamics modeling. To further reinforce control performance, finite-time sliding mode control (FTSMC) is employed. FTSMC effectively counteracts the influence of identification errors, offering enhanced robustness against uncertainties and disturbances. The proposed techniques are validated on the Cybership I model. Simulation results revealed highly accurate parameter identification, with identified values for key parameters m11, m22, and m33 closely matching the true values. Moreover, motion prediction with these identified parameters yielded minor errors, the largest spread being in eu with a maximum value of 0.047m/s. The effectiveness of the FTSMC control strategy was demonstrated through a path-following simulation. Notably, the maximum errors for xe and ye did not exceed 0.006m and 0.15m respectively, reinforcing the precision of the proposed approach.
{"title":"Modeling and Control of Unmanned Surface Vehicles: An Integrated Approach","authors":"Yiming Zhong, Caoyang Yu, Junjun Cao, Chunhu Liu, L. Lian","doi":"10.1109/CACRE58689.2023.10208685","DOIUrl":"https://doi.org/10.1109/CACRE58689.2023.10208685","url":null,"abstract":"This paper presents a comprehensive approach to augment the control performance of unmanned surface vehicles (USVs), addressing two core issues: dynamics modeling and control of USVs. To bolster the precision of dynamics modeling, the paper introduces a parameter identification algorithm based on the nonlinear multi-innovation least-squares method (NMILS). NMILS helps mitigate the noise influence and enhances the precision of the dynamics modeling. To further reinforce control performance, finite-time sliding mode control (FTSMC) is employed. FTSMC effectively counteracts the influence of identification errors, offering enhanced robustness against uncertainties and disturbances. The proposed techniques are validated on the Cybership I model. Simulation results revealed highly accurate parameter identification, with identified values for key parameters m11, m22, and m33 closely matching the true values. Moreover, motion prediction with these identified parameters yielded minor errors, the largest spread being in eu with a maximum value of 0.047m/s. The effectiveness of the FTSMC control strategy was demonstrated through a path-following simulation. Notably, the maximum errors for xe and ye did not exceed 0.006m and 0.15m respectively, reinforcing the precision of the proposed approach.","PeriodicalId":447007,"journal":{"name":"2023 8th International Conference on Automation, Control and Robotics Engineering (CACRE)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116169646","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}
The human hand helps to perform most of our complex and fine movements because of its complex skeletal-muscular system and rich sensory. At the same time, the complex hand system is one of the reasons why rehabilitation of hand dysfunction after stroke is tricky. Virtual reality-based rehabilitation provides a new approach to hand function rehabilitation by mapping the patient’s movements into a rich virtual reality system and providing synergistic stimulation of visual, auditory and haptic senses to improve the patient’s motivation for rehabilitation, promote brain function reorganization and accelerate hand function rehabilitation. So the synergistic approach of multiple senses is very important. In this article, we designed a visually synergistic approach to flexible exoskeleton hand control with the aim of increasing the sense of active participation. We built a model of human-machine coupled motion, combined with a target grasping gesture obtained based on a virtual reality scene, and the target gesture is executed in the virtual system while controlling the synchronized motion of the exoskeleton hand. The results show that the motion of the virtual hand predicted by the human-computer coupling model is synchronized with the motion of the exoskeleton hand.
{"title":"Primary Research of a Multi-sensor Inspired Compliant Control of an Soft Hand Exoskeleton towards to Enhancing Active Participation based on VR System","authors":"Shujing Zhu, Hexiang Chen, Qiaoling Meng, Hongliu Yu","doi":"10.1109/CACRE58689.2023.10208912","DOIUrl":"https://doi.org/10.1109/CACRE58689.2023.10208912","url":null,"abstract":"The human hand helps to perform most of our complex and fine movements because of its complex skeletal-muscular system and rich sensory. At the same time, the complex hand system is one of the reasons why rehabilitation of hand dysfunction after stroke is tricky. Virtual reality-based rehabilitation provides a new approach to hand function rehabilitation by mapping the patient’s movements into a rich virtual reality system and providing synergistic stimulation of visual, auditory and haptic senses to improve the patient’s motivation for rehabilitation, promote brain function reorganization and accelerate hand function rehabilitation. So the synergistic approach of multiple senses is very important. In this article, we designed a visually synergistic approach to flexible exoskeleton hand control with the aim of increasing the sense of active participation. We built a model of human-machine coupled motion, combined with a target grasping gesture obtained based on a virtual reality scene, and the target gesture is executed in the virtual system while controlling the synchronized motion of the exoskeleton hand. The results show that the motion of the virtual hand predicted by the human-computer coupling model is synchronized with the motion of the exoskeleton hand.","PeriodicalId":447007,"journal":{"name":"2023 8th International Conference on Automation, Control and Robotics Engineering (CACRE)","volume":"215 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116455879","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}
Pub Date : 2023-07-01DOI: 10.1109/CACRE58689.2023.10208587
Ming Yao, Yunzhou Su, Zhufeng Shao, Ye Huo
With the rapid development and wide application of industrial robots (IRs), it inevitably brings huge energy consumption (EC), which has become an important part of manufacturing EC. Therefore, the EC optimization of IRs has become the key to the green transformation and upgrading of the manufacturing industry, and it is of great significance for the realization of "carbon neutrality" and "carbon peaking". Therefore, this paper focuses on the energy evaluation and optimization of IR, and realizes the power and EC evaluation and motion parameter optimization of its trajectories based on data-driven method. First, the convolutional neural network (CNN) and Transformer models are combined to build the energy model of IR, and then accurate modeling of its power and EC is realized based on the deep learning algorithms. Based on the above energy model, the exhaustive method and genetic algorithm (GA) are used to find the optimal motion parameters and obtain the optimal trajectory with the least EC. Finally, the experimental results show that the proposed method can achieve more than 98% and 99% of the power and EC modeling of IR, respectively. The optimization of the trajectory motion parameters of IR is realized through exhaustive method and GA, and the maximum optimization potential on the test dataset can reach 52.77%, which verifies the effectiveness and accuracy of the proposed method.
{"title":"Data-driven Energy Evaluation and Optimization Method for Industrial Robots","authors":"Ming Yao, Yunzhou Su, Zhufeng Shao, Ye Huo","doi":"10.1109/CACRE58689.2023.10208587","DOIUrl":"https://doi.org/10.1109/CACRE58689.2023.10208587","url":null,"abstract":"With the rapid development and wide application of industrial robots (IRs), it inevitably brings huge energy consumption (EC), which has become an important part of manufacturing EC. Therefore, the EC optimization of IRs has become the key to the green transformation and upgrading of the manufacturing industry, and it is of great significance for the realization of \"carbon neutrality\" and \"carbon peaking\". Therefore, this paper focuses on the energy evaluation and optimization of IR, and realizes the power and EC evaluation and motion parameter optimization of its trajectories based on data-driven method. First, the convolutional neural network (CNN) and Transformer models are combined to build the energy model of IR, and then accurate modeling of its power and EC is realized based on the deep learning algorithms. Based on the above energy model, the exhaustive method and genetic algorithm (GA) are used to find the optimal motion parameters and obtain the optimal trajectory with the least EC. Finally, the experimental results show that the proposed method can achieve more than 98% and 99% of the power and EC modeling of IR, respectively. The optimization of the trajectory motion parameters of IR is realized through exhaustive method and GA, and the maximum optimization potential on the test dataset can reach 52.77%, which verifies the effectiveness and accuracy of the proposed method.","PeriodicalId":447007,"journal":{"name":"2023 8th International Conference on Automation, Control and Robotics Engineering (CACRE)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115063452","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}
Pub Date : 2023-07-01DOI: 10.1109/CACRE58689.2023.10208793
Efrain Mendez-Flores, Thomas Kallmann, Joseph Garcia, Brianna Mena, Naji Tarabay, Camilo Velez
Aquatic Robots have a critical role to enhance oceanography studies, enable search and rescue scenarios, and basically enable performing tasks that without them, would be too dangerous or even impossible for humans alone. Among the different types of Aquatic prototypes, robots with laser-following features offer enhanced precision, adaptability, simplified guidance, object tracking, and research opportunities due to their suitability for multiple applications. Thereby, this paper explores the design and implementation of an Autonomous Aquatic Robot, capable of following a laser beam through an arrange of multiple RGB sensors feeding an embedded Artificial Neural Network (ANN), optimally trained through a metaheuristic algorithm (Earthquake Optimization Algorithm) to create a laser-following robot. Experimental results validate how Artificial Intelligence (AI) can be applied to generate a control structure for a laser-following robot, with over 99% of accuracy to generate activation signals by the laser presence detection, to provide a reliable signal for the autonomous prototype.
{"title":"Autonomous Aquatic Laser-Following Robot Through RGB Sensors and Optimized Artificial Neural Networks","authors":"Efrain Mendez-Flores, Thomas Kallmann, Joseph Garcia, Brianna Mena, Naji Tarabay, Camilo Velez","doi":"10.1109/CACRE58689.2023.10208793","DOIUrl":"https://doi.org/10.1109/CACRE58689.2023.10208793","url":null,"abstract":"Aquatic Robots have a critical role to enhance oceanography studies, enable search and rescue scenarios, and basically enable performing tasks that without them, would be too dangerous or even impossible for humans alone. Among the different types of Aquatic prototypes, robots with laser-following features offer enhanced precision, adaptability, simplified guidance, object tracking, and research opportunities due to their suitability for multiple applications. Thereby, this paper explores the design and implementation of an Autonomous Aquatic Robot, capable of following a laser beam through an arrange of multiple RGB sensors feeding an embedded Artificial Neural Network (ANN), optimally trained through a metaheuristic algorithm (Earthquake Optimization Algorithm) to create a laser-following robot. Experimental results validate how Artificial Intelligence (AI) can be applied to generate a control structure for a laser-following robot, with over 99% of accuracy to generate activation signals by the laser presence detection, to provide a reliable signal for the autonomous prototype.","PeriodicalId":447007,"journal":{"name":"2023 8th International Conference on Automation, Control and Robotics Engineering (CACRE)","volume":"65 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128385616","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}
Pub Date : 2023-07-01DOI: 10.1109/CACRE58689.2023.10208124
Yingze Lin, Liang Han, J. Liu
With the continuous development of tennis tournaments, the Tennis Ball Boy (TBB) mechanism has been gradually improved, the Eagle-Eye Vision System has been maturely applied in tennis tournaments, and TBB has been moving towards intelligence. In this paper, the concept of an intelligent TBB robot system is proposed, and a TBB robot based on a quadrotor Unmanned Aerial Vehicle (UAV) is developed to address the problems of long working hours, high intensity and the safety hazards of standing for TBB in tennis tournaments. Based on the modular design method, the intelligent TBB robot includes robot hardware design, visual tennis ball object detection, visual localization and navigation, and overall robot control system design. The tennis ball clamping mechanism is designed based on a symmetric single Degree-Of-Freedom (DOF) pawl mechanism. The tennis ball object detection system is designed with the YOLOX deep learning object detection framework, and this model is deployed through the OpenVINO platform, which enables the robot to detect tennis balls in real-time. The visual localization system based on the VINS-FUSION framework is constructed with a binocular vision fusion IMU. On this basis, a SE(3) positional controller, a 3D A* path planning algorithm and Minimum Snap trajectory optimization are developed to enable the robot to have navigation and obstacle avoidance functions. An advanced decision control system based on the Finite State Machines (FSM) is designed for the Robot Operating System (ROS) platform. Finally, the experiment verifies the reliability of each module of the robot, and this paper can provide a basis for further research.
随着网球赛事的不断发展，网球球童(tennis Ball Boy, TBB)机制逐渐完善，鹰眼视觉系统在网球赛事中的应用也日趋成熟，网球球童也逐渐走向智能化。本文提出了智能TBB机器人系统的概念，并针对网球比赛中TBB站位工作时间长、强度大、安全隐患大的问题，研制了基于四旋翼无人机的TBB机器人。基于模块化设计方法，智能TBB机器人包括机器人硬件设计、视觉网球目标检测、视觉定位与导航、机器人整体控制系统设计。网球夹紧机构是基于对称单自由度爪形机构设计的。网球目标检测系统采用YOLOX深度学习目标检测框架进行设计，该模型通过OpenVINO平台进行部署，使机器人能够实时检测网球。利用双目视觉融合IMU构建了基于VINS-FUSION框架的视觉定位系统。在此基础上，开发了SE(3)位置控制器、3D a *路径规划算法和Minimum Snap轨迹优化，使机器人具有导航和避障功能。针对机器人操作系统(ROS)平台，设计了一种基于有限状态机(FSM)的高级决策控制系统。最后，通过实验验证了机器人各模块的可靠性，为本文的进一步研究提供了依据。
{"title":"Design and Implementation of Tennis Ball Boy Robot Based on a Quadrotor UAV","authors":"Yingze Lin, Liang Han, J. Liu","doi":"10.1109/CACRE58689.2023.10208124","DOIUrl":"https://doi.org/10.1109/CACRE58689.2023.10208124","url":null,"abstract":"With the continuous development of tennis tournaments, the Tennis Ball Boy (TBB) mechanism has been gradually improved, the Eagle-Eye Vision System has been maturely applied in tennis tournaments, and TBB has been moving towards intelligence. In this paper, the concept of an intelligent TBB robot system is proposed, and a TBB robot based on a quadrotor Unmanned Aerial Vehicle (UAV) is developed to address the problems of long working hours, high intensity and the safety hazards of standing for TBB in tennis tournaments. Based on the modular design method, the intelligent TBB robot includes robot hardware design, visual tennis ball object detection, visual localization and navigation, and overall robot control system design. The tennis ball clamping mechanism is designed based on a symmetric single Degree-Of-Freedom (DOF) pawl mechanism. The tennis ball object detection system is designed with the YOLOX deep learning object detection framework, and this model is deployed through the OpenVINO platform, which enables the robot to detect tennis balls in real-time. The visual localization system based on the VINS-FUSION framework is constructed with a binocular vision fusion IMU. On this basis, a SE(3) positional controller, a 3D A* path planning algorithm and Minimum Snap trajectory optimization are developed to enable the robot to have navigation and obstacle avoidance functions. An advanced decision control system based on the Finite State Machines (FSM) is designed for the Robot Operating System (ROS) platform. Finally, the experiment verifies the reliability of each module of the robot, and this paper can provide a basis for further research.","PeriodicalId":447007,"journal":{"name":"2023 8th International Conference on Automation, Control and Robotics Engineering (CACRE)","volume":"2022 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127597983","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}
Pub Date : 2023-07-01DOI: 10.1109/CACRE58689.2023.10208719
Tianheng Ma, Shumin Chen, Liang Ruan, Yuan-xin Xu
The widespread use of Autonomous Underwater Vehicles (AUVs) highlights the need for autonomous docking, during which accurate pose estimation and navigation play a vital role. This paper proposes a multi-sensor fusion navigation framework based on the factor graph optimization method, integrating tightly-coupled visual information from the light array to provide high-accuracy and high-frequency relative pose estimations between AUV and its mobile dock at the terminal docking stage. Simulation results demonstrate that the proposed algorithm outperforms PnP and achieves smaller RMSE in relative attitude and translation estimations. Furthermore, the experiments show that the proposed algorithm provides smoother estimation results and that it has the potential to be deployed in embedded applications.
{"title":"A Vision-Integrated Navigation Method in AUV Terminal Mobile Docking Based on Factor Graph Optimization","authors":"Tianheng Ma, Shumin Chen, Liang Ruan, Yuan-xin Xu","doi":"10.1109/CACRE58689.2023.10208719","DOIUrl":"https://doi.org/10.1109/CACRE58689.2023.10208719","url":null,"abstract":"The widespread use of Autonomous Underwater Vehicles (AUVs) highlights the need for autonomous docking, during which accurate pose estimation and navigation play a vital role. This paper proposes a multi-sensor fusion navigation framework based on the factor graph optimization method, integrating tightly-coupled visual information from the light array to provide high-accuracy and high-frequency relative pose estimations between AUV and its mobile dock at the terminal docking stage. Simulation results demonstrate that the proposed algorithm outperforms PnP and achieves smaller RMSE in relative attitude and translation estimations. Furthermore, the experiments show that the proposed algorithm provides smoother estimation results and that it has the potential to be deployed in embedded applications.","PeriodicalId":447007,"journal":{"name":"2023 8th International Conference on Automation, Control and Robotics Engineering (CACRE)","volume":"383 3","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120891226","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}
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