检索结果-内蒙古大学图书馆

Robo-vision! 3D mesh generation of a scene for a robot for planar and non-planar complex objects

Multimedia Tools and Applications 2023年第27期82卷 42641-42659页

作者： Agarwal, Swapna Maity, Soumyadip Barua, Hrishav Bakul Bhowmick, Brojeshwar Robotics & Autonomous Systems group TCS Research Kolkata India

This paper presents a novel architecture to generate a world model in terms of mesh from a continuous image stream with depth information extracted from a robot’s ego-vision camera. We propose two algorithms for planar and non-planar mesh generation. A Cartesian grid-based mesh fitting algorithm is proposed for mesh generation of planar objects. For mesh generation of non-planar objects, we propose a Self Organization Map based algorithm. The proposed algorithm better approaches the boundary and overall shape of the objects compared to State-Of-the-Art (SOA). Extensive experiments done on three public datasets show that our method surpasses SOA both qualitatively and quantitatively. © 2023, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.

关键词： Mesh generation

来源：评论

学校读者我要写书评

暂无评论

Learning-Based Subcategory Ground Segmentation Model for LiDAR Point Cloud

Learning-Based Subcategory Ground Segmentation Model for LiD...

引用

2024 IEEE International Conference on robotics and Biomimetics, ROBIO 2024

作者： Zhao, Guoyang Ma, Fulong Qi, Weiqing Liu, Ming Ma, Jun Robotics and Autonomous Systems Thrust Guangzhou China

ISBN: (纸本)9781665481090

Ground segmentation based on LiDAR point clouds is one of the crucial tasks in 3D perception, directly impacting the recognition of traversable areas for mobile robots. Current mainstream methods rely on manually designed features and parameter tuning, requiring adjustments for different environments. This approach is not only time-consuming but also results in unstable robustness. This paper proposes a model named GroundSeg, which uses deep learning to automatically learn and extract distinguishing ground features. It not only accurately segments the overall ground but also performs semantic segmentation of ground subcategories. In our ground segmentation model, we introduce cylindrical voxelization to match the physical characteristics of LiDAR point clouds. We then propose a Channel-Plane Extraction (CPE) Module to ex-tract both local and global distinguishing features of the ground in three-dimensional voxels. Finally, we incorporate a class-balanced loss group to achieve precise ground segmentation and subcategory classification. Experimental results show that our proposed model has significant advantages in the integrity of ground segmentation and outperforms existing traditional and learning-based methods in F-l score. This is the first work to consider refined category ground segmentation, making it more meaningful for practical robotic applications. All qualitative and quantitative evaluation experiments were conducted on the standard SemanticKITTI dataset. © 2024 IEEE.

关键词： Semantic Segmentation

来源：评论

学校读者我要写书评

暂无评论

CrackSegMamba: A Lightweight Mamba Model for Crack Segmentation

CrackSegMamba: A Lightweight Mamba Model for Crack Segmentat...

引用

2024 IEEE International Conference on robotics and Biomimetics, ROBIO 2024

作者： Qi, Weiqing Ma, Fulong Zhao, Guoyang Liu, Ming Ma, Jun Robotics and Autonomous Systems Thrust Guangzhou511453 China

ISBN: (纸本)9781665481090

Crack localization and segmentation are essential for infrastructure maintenance and safety assessments, enabling timely repairs and preventing structural failures. Despite advancements in deep learning, crack segmentation remains challenging due to the need for real-time performance and computational efficiency. Existing methods often rely on large, resource-intensive models, limiting their practical deployment. We introduce CrackSegMamba, a novel model featuring Channel-wise Parallel Mamba (CPM) Modules, which achieves state-of-the-art performance with fewer than 0.23 million parameters and just 0.7 GFLOPs. CrackSegMamba reduces computational cost by 40-fold and parameter count by nearly 100-fold compared to existing models, while maintaining comparable accuracy. These features make CrackSegMamba ideal for real-time applications. Additionally, we present Crack20000, an annotated dataset of 20,000 concrete crack images to support further research and validation. Evaluations on the Crack500 [1] and Crack20000 datasets demonstrate that CrackSegMamba delivers comparable accuracy to leading methods, with significantly reduced computational requirements. Project page is available at: https://***/view/cracksegmamba. © 2024 IEEE.

关键词： Image segmentation

来源：评论

学校读者我要写书评

暂无评论

An Integrated Setup for Sequential Hybrid Laser Beam Micromachining (LBMM) and Micro-EDM for Machining Micro-hole Arrays with Automated Tool Localization

引用

International Journal of Precision Engineering and Manufacturing 2025年 1-18页

作者： Azhar, Wan Ahmad Bin Wan Saleh, Tanveer Autonomous Systems and Robotics Research Unit Department of Mechatronics Engineering International Islamic University Malaysia Jalan Gombak Kuala Lumpur53100 Malaysia

Micro holes array has significant applications in the field of aerospace and turbo machinery, industrial filtration, microfluidic devices, biomedical engineering, and so on. There are various ways to manufacture micro holes arrays. In order to have a cost-effective, yet precise and efficient process for the fabrication of micro holes array, an integrated setup has been introduced in this paper to combine Laser Beam Micro Machining (LBMM) and micro-EDM (μEDM). This approach uses LBMM for quick material removal and µEDM for precise finishing. However, one of the main challenges in hybrid LBMM-µEDM is the localization of LBMM micro holes for accurate positioning of μEDM electrode. In this present study, an integrated setup with automated hole localization has been presented to improve the hybrid LBMM-μEDM process in terms of alignment accuracy and machining rate. The microscope camera that is mounted on the μEDM stage scans and captures images of LBMM holes. Then, the images were stitched and processed using image processing techniques to get the center coordinate of the LBMM micro holes. Finally, the operator validated the coordinates and G-code was automatically generated for the µEDM process to perform the fine finishing. The result indicated that the alignment accuracy is within 15 μm. Furthermore, the newly developed automation strategies for the hybrid LBMM-μEDM process show significant improvement in machining time with 5 × faster than the pure μEDM process, and better performances in overcut, taper angle, and electrode wear. Furthermore, the hybrid process was found to be 1.6 × more energy efficient as compared to the pure µEDM process. Overall, the newly developed integrated system was found to be highly effective for producing micro holes array. © The Author(s), under exclusive licence to Korean Society for Precision Engineering 2025.

关键词： Precision engineering

来源：评论

学校读者我要写书评

暂无评论

On the Collaborative Object Transportation Using Leader Follower Approach

On the Collaborative Object Transportation Using Leader Foll...

引用

2023 IEEE International Conference on systems, Man, and Cybernetics, SMC 2023

作者： Ghosh, Sumanta Nath, Subhajit Sortee, Sarvesh Kumar, Lokesh Bera, Titas Robotics and Autonomous Systems Group TCS Research India

ISBN: (纸本)9798350337020

In this paper we address the multi-agent collab-orative object transportation problem in a partially known environment with obstacles under a specified goal condition. We propose a leader follower approach for two mobile manipulators collaboratively transporting an object along specified desired trajectories. The proposed approach treats the mobile manipulation system as two independent subsystems: a mobile platform and a manipulator arm and uses their kinematics model for trajectory tracking. In this work we considered that the mobile platform is subject to non-holonomic constraints, with a manipulator carrying a rigid load. The desired trajectories of the end points of the load are obtained from Probabilistic RoadMap-based planning approach. Our method combines Proportional Navigation Guidance-based approach with a proposed Stop-and-Sync algorithm to reach sufficiently close to the desired trajectory;the deviation due to the non-holonomic constraints being compensated by the manipulator arm. Concurrently, a leader follower approach for computing inverse kinematics solution for the position of the end-effector of the manipulator arm is proposed to maintain the load rigidity. Further, we compare the proposed approach with other approaches to analyse the efficacy of our algorithm. © 2023 IEEE.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Bilevel Multi-Armed Bandit-Based Hierarchical Reinforcement Learning for Interaction-Aware Self-Driving At Unsignalized Intersections

引用

IEEE Transactions on Vehicular Technology 2025年第6期74卷 8824-8838页

作者： Peng, Zengqi Wang, Yubin Zheng, Lei Ma, Jun Robotics and Autonomous Systems Thrust Guangzhou511453 China The Hong Kong University of Science and Technology Division of Emerging Interdisciplinary Areas Hong Kong Hong Kong

In this work, we present BiM-ACPPO, a bilevel multi-armed bandit-based hierarchical reinforcement learning framework for interaction-aware decision-making and planning at unsignalized intersections. Essentially, it proactively takes the uncertainties associated with surrounding vehicles (SVs) into consideration, which encompass those stemming from the driver's intention, interactive behaviors, and the varying number of SVs. Intermediate decision variables are introduced to enable the high-level RL policy to provide an interaction-aware reference, for guiding low-level model predictive control (MPC) and further enhancing the generalization ability of the proposed framework. By leveraging the structured nature of self-driving at unsignalized intersections, the training problem of the RL policy is modeled as a bilevel curriculum learning task, which is addressed by the proposed Exp3.S-based BiMAB algorithm. It is noteworthy that the training curricula are dynamically adjusted, thereby facilitating the sample efficiency of the RL training process. Comparative experiments are conducted in the high-fidelity CARLA simulator, and the results indicate that our approach achieves superior performance compared to all baseline methods. Furthermore, experimental results in two new urban driving scenarios clearly demonstrate the commendable generalization performance of the proposed method. © 1967-2012 IEEE.

关键词： Reinforcement learning

来源：评论

学校读者我要写书评

暂无评论

Characterizing Heterogeneous Car-Following Behaviors of Human Drivers in Mixed Traffic 4

Characterizing Heterogeneous Car-Following Behaviors of Huma...

引用

4th IEEE International Conference on Human-Machine systems, ICHMS 2024

作者： Sun, Meng Huang, Chunxi He, Dengbo Thrust Of Robotics And Autonomous Systems Guangzhou China Thrust Of Intelligent Transportation Guangzhou China

ISBN: (纸本)9798350315790

With an increasing number of autonomous vehicles (AVs) being tested and deployed on public roads, the sharing of the road between human-driven vehicles (HVs) and AVs will become inevitable. However, there is a lack of research on the interactions between HVs and AVs, particularly in terms of how HVs behave differently when following AVs compared to following HVs, and how this potential difference affects traffic safety and stability. To fill this gap, we utilized the Lyft dataset to investigate the variances between HV-following-AV and HV-following-HV scenarios. Hierarchical clustering was used to classify the driving styles of the following vehicles in all following events. Then, driving volatility measures and surrogate safety measures, i.e., speed volatility and reciprocal time-to-collision (reTTC) value, were used to compare the outcomes of different car-following events. The clustering results showed that human drivers exhibited four different car-following styles in the mixed traffic and when following AVs and HVs, drivers may exhibit different following styles. Compared to the leading HV, the leading AV resulted in a smaller TTC (i.e., a larger reTTC), regardless of the driving styles of the following HVs. When driving at low speeds, drivers had lower speed volatility when following AVs, indicating more stable traffic;while at high speed, when drivers were not sensitive to changes in the speed of the vehicle ahead, the leading AVs led to larger speed volatility. Future AV control algorithms should take the styles of the following HV into consideration to better optimize traffic stability and improve the safety of mixed traffic. © 2024 IEEE.

关键词： Cluster analysis

来源：评论

学校读者我要写书评

暂无评论

Person Segmentation and Action Classification for Multi-Channel Hemisphere Field of View LiDAR Sensors

Person Segmentation and Action Classification for Multi-Chan...

引用

2025 IEEE/SICE International Symposium on System Integration, SII 2025

作者： Seliunina, Svetlana Otelepko, Artem Memmesheimer, Raphael Behnke, Sven University of Bonn Autonomous Intelligent Systems Group Computer Science Institute VI - Intelligent Systems and Robotics Lamarr Institute for Machine Learning and Artificial Intelligence Center for Robotics Germany

ISBN: (纸本)9798331531614

Robots need to perceive persons in their surroundings for safety and to interact with them. In this paper, we present a person segmentation and action classification approach that operates on 3D scans of hemisphere field of view LiDAR sensors. We recorded a data set with an Ouster OSDome-64 sensor consisting of scenes where persons perform three different actions and annotated it. We propose a method based on a MaskDINO model to detect and segment persons and to recognize their actions from combined spherical projected multi-channel representations of the LiDAR data with an additional positional encoding. Our approach demonstrates good performance for the person segmentation task and further performs well for the estimation of the person action states walking, waving, and sitting. An ablation study provides insights about the individual channel contributions for the person segmentation task. The trained models, code and dataset are made publicly available. © 2025 IEEE.

关键词： Signal encoding

来源：评论

学校读者我要写书评

暂无评论

Overshoot Reduction Inspired Recurrent RBF Neural Network Controller Design for PMSM 32

Overshoot Reduction Inspired Recurrent RBF Neural Network Co...

引用

32nd IEEE International Symposium on Industrial Electronics, ISIE 2023

作者： Yin, Zhenxiao Zhao, Hang Robotics and Autonomous Systems Robotics and Autonomous Systems Guangzhou China The Hong Kong University of Science and Technology Department of Electronic & Computer Engineering Hong Kong Hong Kong

ISBN: (纸本)9798350399714

With the rapid development of computer science, neural network (NN) has received widespread attention. However, it is mainly used as a black box in identification and prediction, which is highly complicated. Its explainability should be mentioned when it is used in real applications. So, this paper derives the explainable control scheme to make sure its theoretical rigorousness. Then a straightforward explanation of the neural network controller using a block diagram is given to help researchers to reproduce the method. Since the detailed design of the neural network should concern the principle of permanent magnet synchronous motor (PMSM), this analyses the real PMSM system and finds the control performance characteristic, especially in spontaneous disturbances. Unlike the black-box neural network, the recurrent radial basis function neural network (RRBF) controller method is proposed, guided by overshoot. Because various PMSMs have various performances of speed changing, three key functions of RRBF are proposed to check which variant is the most suitable for reducing the overshoot. Finally, the RRBF method is implemented in STM32, and its effectiveness in the experiment is checked. © 2023 IEEE.

关键词： Permanent magnets

来源：评论

学校读者我要写书评

暂无评论

A Comparison of Prompt Engineering Techniques for Task Planning and Execution in Service robotics 23

A Comparison of Prompt Engineering Techniques for Task Plann...

引用

23rd IEEE-RAS International Conference on Humanoid Robots, Humanoids 2024

作者： Bode, Jonas Pätzold, Bastian Memmesheimer, Raphael Behnke, Sven Computer Science Institute Vi - Intelligent Systems and Robotics Lamarr Institute for Machine Learning and Artificial Intelligence Center for Robotics University of Bonn Autonomous Intelligent Systems group Germany

ISBN: (纸本)9798350373578

Recent advances in Large Language Models (LLMs) have been instrumental in autonomous robot control and human-robot interaction by leveraging their vast general knowledge and capabilities to understand and reason across a wide range of tasks and scenarios. Previous works have investigated various prompt engineering techniques for improving the performance of LLMs to accomplish tasks, while others have proposed methods that utilize LLMs to plan and execute tasks based on the available functionalities of a given robot platform. In this work, we consider both lines of research by comparing prompt engineering techniques and combinations thereof within the application of high-level task planning and execution in service robotics. We define a diverse set of tasks and a simple set of functionalities in simulation, and measure task completion accuracy and execution time for several state-of-the-art models. We make our code, including all prompts, available at https://***/AIS-Bonn/Prompt-Engineering. © 2024 IEEE.

关键词： Human robot interaction

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：