Proceedings of the 2023 3rd International Conference on Robotics and Control Engineering最新文献_第2页

SLAM Augmented Reality Based Interaction Method for Hand Rehabilitation Training 基于SLAM增强现实的手部康复训练交互方法

Proceedings of the 2023 3rd International Conference on Robotics and Control Engineering Pub Date : 2023-05-12 DOI: 10.1145/3598151.3598437

Jia Liu, Qiyao Gu, Dapeng Chen

{"title":"SLAM Augmented Reality Based Interaction Method for Hand Rehabilitation Training","authors":"Jia Liu, Qiyao Gu, Dapeng Chen","doi":"10.1145/3598151.3598437","DOIUrl":"https://doi.org/10.1145/3598151.3598437","url":null,"abstract":"The current hand rehabilitation training implemented through augmented reality technology has shown the potential to enhance user engagement. However, it falls short in realizing the virtual and realistic occlusion effect, or in producing realistic edge processing of virtual and realistic occlusion. This fragmentation between virtual objects and the real world poses a significant challenge. In light of this, this paper proposes a method that utilizes SLAM to achieve more accurate and realistic voxel occlusion and interaction effects during hand rehabilitation training. The method begins with acquiring dense point cloud data, which is voxelized by SLAM with dynamic removal. Corresponding objects are then segmented using OPTICS clustering for voxel edge constraint. Next, a second thread is initiated to reconstruct the dense point cloud prediction, leveraging local map semantic information combined with the edge SDF algorithm for the input 3D point cloud. By combining the predicted point cloud with the voxel segmented edges, the edge points are updated, and new edge surfaces are fitted to improve the accuracy and shapeliness of the 3D segmented object edges. The feasibility and accuracy of the algorithm are verified using datasets and real-time experiments. Finally, the paper presents an interactive system for hand rehabilitation training with virtual and real occlusion.","PeriodicalId":398644,"journal":{"name":"Proceedings of the 2023 3rd International Conference on Robotics and Control Engineering","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116210099","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

A k-means based multi-AUV hydroacoustic sensor network data acquisition algorithm 一种基于k均值的多auv水声传感器网络数据采集算法

Proceedings of the 2023 3rd International Conference on Robotics and Control Engineering Pub Date : 2023-05-12 DOI: 10.1145/3598151.3598157

Haoxuan Song, Mingzhi Chen

引用次数: 0

Real-time Gait Phase Estimation Based on Multi-source Flexible Sensors Fusion 基于多源柔性传感器融合的实时步态相位估计

Proceedings of the 2023 3rd International Conference on Robotics and Control Engineering Pub Date : 2023-05-12 DOI: 10.1145/3598151.3598223

Xinyan Zhao, Rongkai Liu, Tingting Ma, Hao Li, Quanjun Song

{"title":"Real-time Gait Phase Estimation Based on Multi-source Flexible Sensors Fusion","authors":"Xinyan Zhao, Rongkai Liu, Tingting Ma, Hao Li, Quanjun Song","doi":"10.1145/3598151.3598223","DOIUrl":"https://doi.org/10.1145/3598151.3598223","url":null,"abstract":"The real-time gait phase of human lower extremity is the foundation for wearable robots to provide precise and complex assistance strategies in human-robot interaction. In addition to strengths in estimation performance, it is crucial to make the devices portable and user-friendly that can drive the adoption in the unstructured environments. In this paper, we present an online continuous gait phase estimation system based on multi-source flexible sensors that address this issue. Specifically, we utilize two soft bend sensors mounted around the hip joint and a set of flexible pressure sensors mounted on the bottom of the foot to track the real-time motion of the lower limbs. The adaptive nonlinear frequency oscillators (ANFOs) are used to couple with the captured motion to generate a sequential, linearly growing gait phase. Moreover, heel strike events are detected to calculate phase shift and synchronize the phase with practical action. A uniform walking experiment validates the performance of the proposed method. The experiment results demonstrate that our approach could provide accurate gait phase information and has the potential to improve the interaction transparency of exoskeleton robots in the future.","PeriodicalId":398644,"journal":{"name":"Proceedings of the 2023 3rd International Conference on Robotics and Control Engineering","volume":"73 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123290906","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

3D Object Detection Based on Neighborhood Graph Search in Dense Scenes 基于邻域图搜索的密集场景三维目标检测

Proceedings of the 2023 3rd International Conference on Robotics and Control Engineering Pub Date : 2023-05-12 DOI: 10.1145/3598151.3598182

L. Chen, Zhiling Wang, Hanqi Wang, Pengfei Zhou

{"title":"3D Object Detection Based on Neighborhood Graph Search in Dense Scenes","authors":"L. Chen, Zhiling Wang, Hanqi Wang, Pengfei Zhou","doi":"10.1145/3598151.3598182","DOIUrl":"https://doi.org/10.1145/3598151.3598182","url":null,"abstract":"In the field of robotics and autonomous driving, achieving accurate 3D object detection is crucial for the perception of complex traffic environments. Most current research uses deep learning methods to extract object features from point clouds or images. However, these approaches often do not fully utilize the mutual positional information between objects, resulting in low detection accuracy in dense scenes. To address this issue, this paper proposes a frustum point cloud 3D target detection algorithm based on the fusion of camera and LiDAR data. We establish global connectivity of objects based on the degree of overlap between camera detection frames. Then, we design a neighborhood graph search algorithm based on constraint satisfaction to match the camera target detection results with LiDAR clustering results. Finally, the category and distance information of obstacles are displayed in bird’s eye view (BEV). Evaluated on the KITTI benchmarks, our method achieves an average precision (AP) of 88.38% on the easy level, 87.64% on the moderate level, and 80.10% on the hard level in BEV detection. Compared to F-ConvNet, our method shows improvements of 5.49% on the moderate level and 7.33% on the hard level, significantly enhancing recognition accuracy in dense scenes.","PeriodicalId":398644,"journal":{"name":"Proceedings of the 2023 3rd International Conference on Robotics and Control Engineering","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130234633","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

Subpaving-Map: Fast Terrain Mapping for Outdoor Scenes based on Set-membership Theory 基于集隶属度理论的室外场景快速地形映射

Proceedings of the 2023 3rd International Conference on Robotics and Control Engineering Pub Date : 2023-05-12 DOI: 10.1145/3598151.3598436

Zeqing Chang, Bo Zhou, Nanxing Zheng, Fang Fang, K. Qian

引用次数: 0

Research on Autonomous Navigation of Two Wheel-leg Robot in Indoor Dynamic Environment 室内动态环境下两轮腿机器人自主导航研究

Proceedings of the 2023 3rd International Conference on Robotics and Control Engineering Pub Date : 2023-05-12 DOI: 10.1145/3598151.3598183

Xinzhi Ma, H. Lai, Qiongyang Wen, Xuejun Zhu, Aidi Yang, Haifu Li

{"title":"Research on Autonomous Navigation of Two Wheel-leg Robot in Indoor Dynamic Environment","authors":"Xinzhi Ma, H. Lai, Qiongyang Wen, Xuejun Zhu, Aidi Yang, Haifu Li","doi":"10.1145/3598151.3598183","DOIUrl":"https://doi.org/10.1145/3598151.3598183","url":null,"abstract":"The object of this paper is the autonomous navigation control system of the two wheel-leg robot in indoor dynamic environment. To give full play to the kinematic ability of the two wheel-leg robot, the terrain adaptation ability of the leg structure and the control ability of the upper layer autonomous navigation system, the multi-mode control method of the robot and the path planning and autonomous navigation in indoor environment are studied in this paper. Firstly, based on the simulation physics platform, the kinematic transfer relationship of distributed model was proposed, the kinematic model of the wheel-leg subsystem and the two wheel-leg system was established, and the full-drive dynamic model with the wheel-leg-torso interaction force as the end output force was established. Then, a distributed control framework with torso postures as task space was proposed to plan the torso force and joint torque of the body in layers. The proposed walking and jumping motion planner of the two wheel-leg system and the multi-mode state machine are integrated with the control frame to realize the wheeled walking and jumping smooth control of the sagittal plane wheel-leg coordination. Finally, the ROS software framework based RGB-D visual sensor SLAM local environment awareness system is used to convert the point cloud map into an octree map, and then the oblique projection principle is converted into a two-dimensional raster map. A * algorithm and TEB algorithm are respectively used for global and local path planning. Finally, the autonomous navigation ability of the two wheel-leg robot in indoor dynamic environment is realized.","PeriodicalId":398644,"journal":{"name":"Proceedings of the 2023 3rd International Conference on Robotics and Control Engineering","volume":"73 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117318955","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

Feature Tracking Control of Input-constrained VS Manipulators through ADP 基于ADP的输入约束VS机器人特征跟踪控制

Proceedings of the 2023 3rd International Conference on Robotics and Control Engineering Pub Date : 2023-05-12 DOI: 10.1145/3598151.3598185

Xiaolin Ren, Haoyu Yan, B. Ma

引用次数: 0

Design of Welding Robot Control System based on Visual Recognition Technology 基于视觉识别技术的焊接机器人控制系统设计

Proceedings of the 2023 3rd International Conference on Robotics and Control Engineering Pub Date : 2023-05-12 DOI: 10.1145/3598151.3598188

Yu Han, Xu Han, Xiaoqian Guo, Lingbo Yang, Tinghang Guo, Zhuanping Qin, Zhuangzhuang Zhao

引用次数: 0

Visual Prediction based Teleoperation Control 基于视觉预测的遥操作控制

Proceedings of the 2023 3rd International Conference on Robotics and Control Engineering Pub Date : 2023-05-12 DOI: 10.1145/3598151.3598155

Yichen Zhong, Y. Pu, Ting Wang

引用次数: 0

Planar Problem Motion Stabilization Using the Rotational Motion and the Light Pressure Forces at the Collinear Libration Point 利用旋转运动和共线振动点的轻压力稳定平面问题运动

Proceedings of the 2023 3rd International Conference on Robotics and Control Engineering Pub Date : 2023-05-12 DOI: 10.1145/3598151.3598156

D. Shymanchuk

引用次数: 0