2023 International Conference on Advanced Robotics and Mechatronics (ICARM)最新文献_第2页

Novel Path Following for a Four-Wheel Steering Vehicle Based on Model Predictive Control 基于模型预测控制的四轮转向车辆路径跟踪新方法

2023 International Conference on Advanced Robotics and Mechatronics (ICARM) Pub Date : 2023-07-08 DOI: 10.1109/ICARM58088.2023.10218925

Rongqi Gu, Tianhang Wang, Bo Zhang, Zhijun Li, Tianpeng Li, Guangyi Chen

引用次数: 0

Skeleton-based Multi-Feature Sharing Real-Time Action Recognition Network for Human-Robot Interaction 基于骨架的人机交互多特征共享实时动作识别网络

2023 International Conference on Advanced Robotics and Mechatronics (ICARM) Pub Date : 2023-07-08 DOI: 10.1109/ICARM58088.2023.10218912

Zhiwen Deng, Qing Gao, Xiang Yu, Zhaojie Ju, Junkang Chen

{"title":"Skeleton-based Multi-Feature Sharing Real-Time Action Recognition Network for Human-Robot Interaction","authors":"Zhiwen Deng, Qing Gao, Xiang Yu, Zhaojie Ju, Junkang Chen","doi":"10.1109/ICARM58088.2023.10218912","DOIUrl":"https://doi.org/10.1109/ICARM58088.2023.10218912","url":null,"abstract":"Human-Robot Interaction (HRI) is one of the directions that deserves to be studied, and it is used in various fields (e.g., emergency rescue, telemedicine, and astronaut assistance). Action-based HRI has been proven practical in many application scenarios (e.g., industrial teleoperation and telemedicine). Among these many applications, speed and accuracy are two common optimization goals for researchers. A skeleton-based multi-feature sharing real-time action recognition network (MSR-Net) has been proposed to ensure its high accuracy and speed. Three pairs of feature inputs are proposed to make the network input more informative, which contain: joint distance-joint distance motion (JD-JDM), angle-angle motion (A-AM), slow motion coordinates-fast motion coordinates (SMC-FMC). To ensure that features are fully extracted while reducing the number of model parameters, one-dimensional convolutional neural networks (1DCNN) are used to build multi-feature sharing two-stage feature extraction networks. As a result, MSR-Net outperforms state-of-the-art models in accuracy on the JHMDB (86.8%) and SHREC datasets (96.8% on coarse class and 93.8% on fine class). Application experiments were carried out on the HRI platform to demonstrate the effectiveness of MSR-Net in HRI. The video demonstration of the experimental results of the HRI application can be accessed on https://youtu.be/NzXrngh7BbQ.","PeriodicalId":220013,"journal":{"name":"2023 International Conference on Advanced Robotics and Mechatronics (ICARM)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123951269","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}

引用次数: 0

Yaw Stability Control of MPC Emergency Supplies Transportation Robot Based on Composite Filtering 基于复合滤波的MPC应急物资运输机器人偏航稳定性控制

2023 International Conference on Advanced Robotics and Mechatronics (ICARM) Pub Date : 2023-07-08 DOI: 10.1109/ICARM58088.2023.10218897

Yaqi Zhang, Minan Tang, Haiyan Zhang, Wenjuan Wang, Bo An, Yaguang Yan

{"title":"Yaw Stability Control of MPC Emergency Supplies Transportation Robot Based on Composite Filtering","authors":"Yaqi Zhang, Minan Tang, Haiyan Zhang, Wenjuan Wang, Bo An, Yaguang Yan","doi":"10.1109/ICARM58088.2023.10218897","DOIUrl":"https://doi.org/10.1109/ICARM58088.2023.10218897","url":null,"abstract":"The yaw stability control of the emergency supplies transportation robot is a key technology to realize the precision of supplies distribution. To ensure the yaw stability of the emergency supplies transportation robot during operation, this paper proposes a model predictive control (MPC) emergency supplies transportation robot yaw stability control method based on composite filtering. Firstly, the dynamics model and tire model of the emergency supplies transportation robot are established. Secondly, Kalman filtering is used to reduce the noise of the state variables of the robot system in the model part. Thirdly, the model predictive controller is designed for the yaw stability control of the emergency supplies transportation robot, and an extended state observer (ESO) is introduced to estimate the external disturbances. Finally, a Simulink/ CarSim co-simulation platform is built and simulation experiments are conducted under different road conditions. Through simulation, the proposed yaw stability control method of the MPC emergency supplies transportation robot based on composite filtering can make the emergency supplies transportation robot maintain good yaw stability.","PeriodicalId":220013,"journal":{"name":"2023 International Conference on Advanced Robotics and Mechatronics (ICARM)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127675436","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}

引用次数: 0

Design and Dynamic Simulation of Single-arm Inspection Robot System for Transmission Lines 输电线路单臂巡检机器人系统设计与动态仿真

2023 International Conference on Advanced Robotics and Mechatronics (ICARM) Pub Date : 2023-07-08 DOI: 10.1109/ICARM58088.2023.10218801

D. Zou, Lanlan Liu, Zhipeng Jiang, Bangwei Luo, Wusheng Quan

{"title":"Design and Dynamic Simulation of Single-arm Inspection Robot System for Transmission Lines","authors":"D. Zou, Lanlan Liu, Zhipeng Jiang, Bangwei Luo, Wusheng Quan","doi":"10.1109/ICARM58088.2023.10218801","DOIUrl":"https://doi.org/10.1109/ICARM58088.2023.10218801","url":null,"abstract":"Overhead transmission line energized maintenance is a necessary means to maintain the safe and stable operation of electric power, common energized operation tasks require manual tower operation, and inspection robots are gradually becoming a powerful tool as an alternative or auxiliary manual energized operation, but conventional inspection robots have problems such as difficulty in getting on and off the line, single operation function, weak intelligent behavior, etc. Therefore, this paper proposes a new method of intelligent cooperative operation between a large-load UAV and a power inspection robot, a transmission line single-arm inspection robot mechanical system has been designed, the Lagrangian method has been used to model and analyze, and the theoretical model basis for the drive selection of the robot arm joint has been established. On this basis, a virtual prototype model is established in ADMAS software, and the dynamics characteristics have been simulated and analyzed. Finally, an online operation experiment was carried out on the actual live line, the results show that the single-arm inspection robot mechanism designed in this paper meets the requirements of conventional live line operation inspection, it is easy to control and can be precisely positioned. The research in this paper can solve the bottleneck problem of robot practicality, which has important theoretical significance and practical application value for the safety, stability, and intelligent operation and maintenance management of power transmission lines.","PeriodicalId":220013,"journal":{"name":"2023 International Conference on Advanced Robotics and Mechatronics (ICARM)","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127743078","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}

引用次数: 0

Knee Joint Torque Prediction with Uncertainties by a Neuromusculoskeletal Solver-informed Gaussian Process Model 基于神经肌肉骨骼解算器的高斯过程模型的不确定膝关节力矩预测

2023 International Conference on Advanced Robotics and Mechatronics (ICARM) Pub Date : 2023-07-08 DOI: 10.1109/ICARM58088.2023.10218934

Longbin Zhang, Xiaochen Zhang, Xueyu Zhu, Ruoli Wang, E. Gutierrez-Farewik

{"title":"Knee Joint Torque Prediction with Uncertainties by a Neuromusculoskeletal Solver-informed Gaussian Process Model","authors":"Longbin Zhang, Xiaochen Zhang, Xueyu Zhu, Ruoli Wang, E. Gutierrez-Farewik","doi":"10.1109/ICARM58088.2023.10218934","DOIUrl":"https://doi.org/10.1109/ICARM58088.2023.10218934","url":null,"abstract":"Research interest in exoskeleton assistance strategies that incorporate the user's torque capacity is rapidly growing, yet uncertainty in predicted torque capacity can significantly impact the user-exoskeleton interface safety. In this paper, we estimated knee flexion/extension torques by using a neuromusculoskeletal (NMS) solver-informed Gaussian process (NMS-GP) model with muscle electromyography signals and joint kinematics as model inputs. The NMS-GP model combined the NMS and GP models by integrating valuable features from an NMS solver into a GP model. The NMSGP model was used to predict knee joint torque in daily activities with uncertainty quantification. The activities included slow walking, self-selected speed walking, fast walking, sit-to-stand, and stand-to-sit. Model performance, defined as low prediction error between the model's predicted torque and measured torques from inverse dynamics computations, of both the NMS-GP and NMS models was analyzed. We found that prediction error was significantly lower in NMS-GP models than in NMS models. We observed relatively high uncertainties in the predicted knee torque at the beginning of each movement, particularly in self-selected speed walking. High uncertainties were also found during terminal stance and swing in self-selected speed walking. Compared to other torque prediction methods, the proposed NMS-GP model not only provides an accurate joint torque prediction but also a measure of the uncertainty. Our study showed that the NMS-GP model has a large potential in control strategy design for rehabilitation exoskeletons and to enhance the overall user experience.","PeriodicalId":220013,"journal":{"name":"2023 International Conference on Advanced Robotics and Mechatronics (ICARM)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128077976","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}

引用次数: 0

Research on Violence Detection Algorithm based on Multi-UAV 基于多无人机的暴力检测算法研究

2023 International Conference on Advanced Robotics and Mechatronics (ICARM) Pub Date : 2023-07-08 DOI: 10.1109/ICARM58088.2023.10218951

Zhiqiang Zhu, Xinde Li, Lianli Zhu

{"title":"Research on Violence Detection Algorithm based on Multi-UAV","authors":"Zhiqiang Zhu, Xinde Li, Lianli Zhu","doi":"10.1109/ICARM58088.2023.10218951","DOIUrl":"https://doi.org/10.1109/ICARM58088.2023.10218951","url":null,"abstract":"Based on the 30-meter UAV aerial violence data, a multi-UAV violence detection algorithm based on target detection is proposed. In this paper, YOLOX algorithm is improved. Because the target pixel is small, the UFocus module is designed to upsample the feature image, and the channel attention module is cascaded after the UFocus. The DAM module is designed to improve spatial attention. The shallow features are extracted and cascaded with DAM modules, and multi-scale features are fused with the deep semantic features. A dual-threshold single-machine violence detection algorithm is proposed. When the number of violent actions detected in a violent video within three seconds meets the dual-threshold constraint, it is determined that violence has occurred. A violence detection algorithm based on multi-UAV information fusion is proposed. The confidence value of UAV is dynamically allocated, and the confidence and probability are fused to obtain the comprehensive results. The self-built violence detection data set is tested and trained. The experiment shows that the accuracy of the improved YOLOX algorithm is 1.56% higher than the original algorithm. The dual threshold detection violence detection algorithm can complete the detection task, with an average accuracy of 71%. Taking three UAVs as an example, the weighted fusion of multiple UAV information is carried out. When the probability threshold is 0.6, the accuracy rate reaches 89%, which is 25.4% higher than that of a single UAV.","PeriodicalId":220013,"journal":{"name":"2023 International Conference on Advanced Robotics and Mechatronics (ICARM)","volume":"96 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134065693","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}

引用次数: 0

Robust Subgraph Augmentation for Graph Convolutional Networks with Few Labeled Nodes 少标记节点图卷积网络的鲁棒子图增强

2023 International Conference on Advanced Robotics and Mechatronics (ICARM) Pub Date : 2023-07-08 DOI: 10.1109/ICARM58088.2023.10218877

Keyu Jin, Long Chen, Jiahui Yu, Zhimao Lu

{"title":"Robust Subgraph Augmentation for Graph Convolutional Networks with Few Labeled Nodes","authors":"Keyu Jin, Long Chen, Jiahui Yu, Zhimao Lu","doi":"10.1109/ICARM58088.2023.10218877","DOIUrl":"https://doi.org/10.1109/ICARM58088.2023.10218877","url":null,"abstract":"Graph Neural Networks (GNNs) have garnered significant attention owing to their remarkable capacity to extract representations from non-Euclidean data. Despite their success, the performance of prevalent GNNs degrades significantly when structural noise is introduced into the graph data. Besides, the reliance of GNNs on a considerable volume of labeled nodes presents challenges in dealing with the low-data regime where labeled nodes are scarce. This paper aims to address a challenging scenario in which structural noise and the low-data regime occur simultaneously. Specifically, we exploit the valuable information from the local topologies, i.e. subgraphs, of a graph as the augmented supervision signals for the extensive amounts of unlabeled nodes. Moreover, to alleviate the effects of structural noise, we remove potential noisy edges linking dissimilar nodes, generating robust subgraphs for the downstream node classification tasks. We conduct a series of experimental studies on canonical node classification tasks using three graph datasets. The results of our experimental analyses demonstrate that our approach can achieve state-of-the-art performance under structural noises and the low-data regime.","PeriodicalId":220013,"journal":{"name":"2023 International Conference on Advanced Robotics and Mechatronics (ICARM)","volume":"85 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134097665","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}

引用次数: 0

TT-LCD: Tensorized-Transformer based Loop Closure Detection for Robotic Visual SLAM on Edge TT-LCD:基于张拉变压器的机器人视觉SLAM边缘闭环检测

2023 International Conference on Advanced Robotics and Mechatronics (ICARM) Pub Date : 2023-07-08 DOI: 10.1109/ICARM58088.2023.10218828

Chenchen Ding, Hongwei Ren, Zhiru Guo, Minjie Bi, Changhai Man, Tingting Wang, Shuwei Li, Shaobo Luo, Rumin Zhang, Hao Yu

{"title":"TT-LCD: Tensorized-Transformer based Loop Closure Detection for Robotic Visual SLAM on Edge","authors":"Chenchen Ding, Hongwei Ren, Zhiru Guo, Minjie Bi, Changhai Man, Tingting Wang, Shuwei Li, Shaobo Luo, Rumin Zhang, Hao Yu","doi":"10.1109/ICARM58088.2023.10218828","DOIUrl":"https://doi.org/10.1109/ICARM58088.2023.10218828","url":null,"abstract":"Visual simultaneous localization and mapping (VSLAM) is one of the core technologies in autonomous driving, intelligent robots, metaverse and other fields. Besides, loop closure detection (LCD) is an essential component in VSLAM which can correct the drift and accumulated errors caused by the visual odometry (VO) front-end, and assist robot to build a globally consistent map. Over the years, several deep-learning methods have been proposed to address the task. However, the prior proposed neural network-based LCD models are heavy in model size, and difficult to be deployed on edge devices. In this paper, an LCD module based on the tensorized transformer model called TT-LCD is proposed. To obtain a tensorized transformer model with accuracy-complexity co-awareness which can be effectively deployed, we proposed a construction method for tensor compressed transformer model with tensor-train (TT) decomposition and a differential neural network architecture search (NAS) method for tensor rank selection. Experiments demonstrate that the TT-LCD realizes a model size 6.04 × smaller than uncompressed transformer model, 32.1 × smaller than the VGG model and achieves lower memory cost of about 134M on edge CPU with little loss of accuracy on pre-training dataset but even 2.13% higher average accuracy on NewCollege dataset compared with uncompressed DeiT-based model in LCD task.","PeriodicalId":220013,"journal":{"name":"2023 International Conference on Advanced Robotics and Mechatronics (ICARM)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131599302","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}

引用次数: 1

Design and Experimental Evaluation of a Hexapod Mobile Robot with C-Shaped Legs c型腿六足移动机器人的设计与实验评价

2023 International Conference on Advanced Robotics and Mechatronics (ICARM) Pub Date : 2023-07-08 DOI: 10.1109/ICARM58088.2023.10218915

Yujie Wu, Dangchao Li, Xia Dong, Xin Wang, Chunli Zheng, Aibin Zhu, Zheng Zhang, Xu Zhou, Yulin Zhang

引用次数: 0

Low-Frequency Structure-Borne Noise Identification Based on FastICA-WPA Algorithm 基于FastICA-WPA算法的低频结构噪声识别

2023 International Conference on Advanced Robotics and Mechatronics (ICARM) Pub Date : 2023-07-08 DOI: 10.1109/ICARM58088.2023.10218872

Qiang Liu, Jianxin Zhu

引用次数: 0