检索结果-内蒙古大学图书馆

IEEE International Conference on robotics and Automation (ICRA)

作者： Yi Feng Bohuan Xue Ming Liu Qijun Chen Rui Fan Robotics & Artificial Intelligence Laboratory (RAIL) the State Key Laboratory of Intelligent Autonomous Systems and Frontiers Science Center for Intelligent Autonomous Systems the College of Electronic & Information Engineering Tongji University Shanghai P. R. China Department of Computer Science & Engineering the Hong Kong University of Science and Technology (Guangzhou) Hong Kong SAR P. R. China Robotics & Autonomous Systems Thrust of the Systems Hub the Hong Kong University of Science and Technol-ogy (Guangzhou) Nansha Guangzhou P. R. China

Surface normal holds significant importance in visual environmental perception, serving as a source of rich geometric information. However, the state-of-the-art (SoTA) surface normal estimators (SNEs) generally suffer from an unsatisfactory trade-off between efficiency and accuracy. To resolve this dilemma, this paper first presents a superfast depth-to-normal translator (D2NT), which can directly translate depth images into surface normal maps without calculating 3D coordinates. We then propose a discontinuity-aware gradient (DAG) filter, which adaptively generates gradient convolution kernels to improve depth gradient estimation. Finally, we propose a surface normal refinement module that can easily be integrated into any depth-to-normal SNEs, substantially improving the surface normal estimation accuracy. Our proposed algorithm demonstrates the best accuracy among all other existing real-time SNEs and achieves the SoTA trade-off between efficiency and accuracy.

关键词：

来源：评论

学校读者我要写书评

暂无评论

A 3-Step Optimization Framework with Hybrid Models for a Humanoid Robot's Jump Motion

arXiv

引用

arXiv 2025年

作者： Qi, Haoxiang Yu, Zhangguo Chen, Xuechao Liu, Yaliang Yi, Chuanku Dong, Chencheng Meng, Fei Huang, Qiang The Intelligent Robotics Institute School of Mechatronical Engineering Beijing Institute of Technology Beijing100081 China The International Joint Research Laboratory of Biomimetic Robots and Systems Ministry of Education Beijing100081 China The National Key Lab of Autonomous Intelligent Unmanned Systems Beijing100081 China

High dynamic jump motions are challenging tasks for humanoid robots to achieve environment adaptation and obstacle crossing. The trajectory optimization is a practical method to achieve high-dynamic and explosive jumping. This paper proposes a 3-step trajectory optimization framework for generating a jump motion for a humanoid robot. To improve iteration speed and achieve ideal performance, the framework comprises three sub-optimizations. The first optimization incorporates momentum, inertia, and center of pressure (CoP), treating the robot as a static reaction momentum pendulum (SRMP) model to generate corresponding trajectories. The second optimization maps these trajectories to joint space using effective Quadratic Programming (QP) solvers. Finally, the third optimization generates whole-body joint trajectories utilizing trajectories generated by previous parts. With the combined consideration of momentum and inertia, the robot achieves agile forward jump motions. A simulation and experiments (Fig. 1) of forward jump with a distance of 1.0 m and 0.5 m height are presented in this paper, validating the applicability of the proposed framework. Note to Practitioners-The motivation of this paper stems from the need to improve jumping performance of humanoid robots. By comprehensively considering factors such as robot posture, centroidal angular momentum, and landing foot placement, the algorithm enhances the robot's ability to navigate complex environments. This capability is crucial for applications that require overcoming obstacles, such as in search and rescue or inspection tasks. Improved jumping ability can significantly boost environmental adaptability, allowing robots to perform effectively in diverse conditions, and it also represents an exploration of the high-dynamic motion capabilities of humanoid robots. Future research will focus on integrating visual and perceptual information to enhance decision-making. Copyright © 2025, The Authors. All rights reserve

关键词： Anthropomorphic robots

来源：评论

学校读者我要写书评

暂无评论

Fuzzy Based Steering Control of a Multi-Joint AUV

Fuzzy Based Steering Control of a Multi-Joint AUV

引用

Control Conference (ANZCC), Australian and New Zealand

作者： Zakarya Omar Ke-Xian Liu Chao Ren Qing-Hao Meng Institute of Robotics and Autonomous Systems Tianjin Key Laboratory of Intelligent Un-manned Swarm Technology and System School of Electrical and Information Engineering Tianjin University Tianjin China Faculty of Engineering Sana'a University Sana'a Yemen

The multi-joint structure of our autonomous Underwater Vehicle (AUV) enhances its maneuverability, allowing it to navigate in the underwater environment with greater flexibility. However, this added maneuverability poses challenges to the steering process. When the multi-joint AUV (MJ-AUV) performs steering maneuvers, its joints undergo rotation, leading to a change in the orientation of the cabins with respect to the overall forward heading of the vehicle. As a result, this change in orientation affects the values of the hydrodynamic reactions, including Coriolis and damping, experienced by the cabins. The dynamic interaction between the joints' rotation and the resulting change in hydrodynamic forces significantly impacts the steering performance and stability of the MJ-AUV. Understanding and addressing these effects are crucial for the development of effective control strategies that ensure precise and reliable steering in various underwater environments. Overcoming the difficulties posed by joint rotation during steering can lead to advancements in MJ-AUV navigation and expand their potential applications in complex underwater missions. This research proposes a fuzzy-based control with sliding mode control (SMC) approach for the steering of an MJAUV. The developed fuzzy-based SMC control algorithm is validated through extensive MATLAB simulations. The results demonstrate improved tracking performance and robustness in comparison to the SMC control method. Moreover, the proposed approach shows superior trajectory tracking accuracy while mitigating undesired chattering effects associated with standard SMC techniques.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Modeling and planar trajectory tracking control of an MJ-AUV

Modeling and planar trajectory tracking control of an MJ-AUV

引用

第42届中国控制会议

作者： Zakarya Omar Ke-Xian Liu Chao Ren Qing-Hao Meng Institute of Robotics and Autonomous Systems Tianjin Key Laboratory of Intelligent Unmanned Swarm Technology and SystemSchool of Electrical and Information EngineeringTianjin University Faculty of Engineering Sana'a University

A Multi-Joint autonomous Underwater Vehicle(MJ-AUV) is designed and equipped with multiple movable segments or joints that allow for greater maneuverability and flexibility in the *** joints allow the MJ-AUV to change its shape,orientation,and direction of movement,so it can access tight spaces or navigate in complex underwater environments,making it useful for a variety of tasks in the deep sea,such as surveillance,exploration,and ***,the multiple joint structure of the MJ-AUV complicates the dynamics of the ***,the joints' rotation causes misalignment of the cabins,causing deviations in the desired forces and *** address these issues,this study focuses on the 2-dimensional(2 D) modeling as well as the trajectory tracking controller of the *** this setting,the proposed controller utilizes a hierarchically structured robust nonlinear back-stepping and sliding-mode ***,this controller is simulated under various uncertainties and disturbances and the results show that it presents a global finite-time convergence to a bounded neighborhood of the origin for both position and velocity tracking errors,demonstrating its effectiveness and robustness.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Evaluation of a Weather Plugin in Gazebo: A Case-Study of a Wind Influence on PX4-Based UAV Performance 9th

Evaluation of a Weather Plugin in Gazebo: A Case-Study of a ...

引用

9th International Conference on Interactive Collaborative robotics, ICR 2024

作者： Imamov, Niyaz Abbyasov, Bulat Tsoy, Tatyana Martínez-García, Edgar A. Magid, Evgeni Laboratory of Intelligent Robotic Systems Intelligent Robotics Department Institute of Information Technology and Intelligent Systems Kazan Federal University 35 Kremlyovskaya St. Kazan420111 Russia Tikhonov Moscow Institute of Electronics and Mathematics HSE University Tallinn Street 34 Moscow Russia Institute of Engineering and Technology Department of Industrial Engineering and Manufacturing Autonomous University of Ciudad Juarez Manuel Díaz H. No. 518-B Zona Pronaf Condominio Chihuahua Cuidad Juárez32315 Mexico

ISBN: (纸本)9783031713590

Unmanned aerial vehicles (UAVs) are utilized in a wide range of real-world applications including search and rescue missions, 3D mapping, building inspection and reconstruction. In a real-world environment, severe weather conditions significantly impact UAV operations. Wind is one of the most dangerous weather factors that can destabilize and even destroy a UAV. Preparing UAV flight algorithms for real-world conditions in order to minimize risks of damage and malfunctioning is a crucial part of a UAV system development. This paper analyses a wind influence on UAV virtual model performance within the Gazebo simulator. The paper focuses on gazebo_wind_plugin package used for creating a windy virtual environment. PX4-LIRS package is used for simulating a UAV within the Gazebo. Three types of experiments were run to evaluate capabilities of the plugin to simulate typical issues that arise in real-world scenarios: a UAV wind resistance, a wind effect on a UAV tilt angle and on a flight velocity. Virtual experiments demonstrated that gazebo_wind_plugin could serve for PX4 UAV flight scenarios modeling in Gazebo simulation with a satisfactory level of realism. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Unmanned aerial vehicles (UAV)

来源：评论

学校读者我要写书评

暂无评论

Saliency-SLAM: saliency prediction for visual SLAM

Saliency-SLAM: saliency prediction for visual SLAM

引用

Tianjin University-IET Electrical & Information Engineering Doctoral Forum (TJU IET 2023)

作者： S. Jin Q. Meng Institute of Robotics and Autonomous Systems Tianjin Key Laboratory of Intelligent Unmanned Swarm Technology and System School of Electrical and Information Engineering Tianjin University Tianjin People's Republic of China

This paper proposes a novel approach for visual simultaneous localization and mapping (vSLAM), called Saliency-SLAM. This method effectively emulates the visual attention mechanism by integrating a saliency prediction model. In contrast to conventional vSLAM methods, which treat all feature points as equally significant, salient feature points are given greater importance in Saliency-SLAM. Therefore, we construct a novel saliency dataset specifically for vSLAM task to train a saliency prediction model by integrating multi-level visual information. Then, we propose to use the salient value of predicted result as the weight of significance for the feature points during the optimization process. Exhaustive experiments have been conducted on the KITTI dataset, demonstrating that our proposed method outperforms existing approaches in terms of localization accuracy.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Towards Open-Source and Modular Space systems with ATMOS

arXiv

引用

arXiv 2025年

作者： Roque, Pedro Phodapol, Sujet Krantz, Elias Lim, Jaeyoung Verhagen, Joris Jiang, Frank J. Dörner, David Mao, Huina Tibert, Gunnar Siegwart, Roland Stenius, Ivan Tumova, Jana Fuglesang, Christer Dimarogonas, Dimos V. Division of Decision and Control Systems KTH Royal Institute of Technology Stockholm Sweden School of Engineering Sciences KTH Royal Institute of Technology Stockholm Sweden Autonomous Systems Laboratory ETH Zürich Zürich Switzerland Division of Robotics Perception and Learning KTH Royal Institute of Technology Stockholm Sweden

In the near future, autonomous space systems will compose many of the deployed spacecraft. Their tasks will involve autonomous rendezvous and proximity operations with large structures, such as inspections, assembly, and maintenance of orbiting space stations, as well as human-assistance tasks over shared workspaces. To promote replicable and reliable scientific results for autonomous control of spacecraft, we present the design of a space robotics laboratory based on open-source and modular software and hardware. The simulation software provides a software-in-the-loop architecture that seamlessly transfers simulated results to the hardware. Our results provide an insight into such a system, including comparisons of hardware and software results, as well as control and planning methodologies for controlling free-flying platforms. Copyright © 2025, The Authors. All rights reserved.

关键词： Space stations

来源：评论

学校读者我要写书评

暂无评论

E-Nose-Based Cross-Domain Recognition of Combustion-Supporting Agents via M-BFFNet

E-Nose-Based Cross-Domain Recognition of Combustion-Supporti...

引用

Chinese Control Conference (CCC)

作者： De-Xiu Wang Qing-Hao Meng Rui-Xue Han Hong-Yue Li Hui-Rang Hou Tianjin Key Laboratory of Process Measurement and Control Institute of Robotics and Autonomous Systems School of Electrical and Information Engineering Tianjin University Tianjin China Tianjin Navigation Instruments Research Institute Tianjin China

Identification of the type of combustion-supporting agents (CSAs) by an electronic nose (e-nose) is severely limited due to the absence of untested gas concentration in the e-nose training set. In order to solve this problem, this study designs an e-nose for classifying four CSAs (Diesel, Gasoline, Ethanol and Thinner), and builds cross-concentrations data set. This study uses Gramian Angular Field method that converts one-dimensional time series data to two-dimensional data, and proposes an algorithm named the Multi-Branch Feature Fusion Network (M-BFFNet). This algorithm passes the one-dimensional and two-dimensional data through two different networks and obtains two types of features. First, the algorithm can strength the one-dimensional raw data, integrate the advantages of different networks, and fuse the characteristics of different networks. Second, it can learn the characteristics of volatile gas with specific concentrations to identify the unknown concentrations. Last, a feature fusion module is designed to improve the algorithm ability of learning odor fingerprint. In order to verify the superiority of the algorithm, this study tests the recognition performance of the e-nose based systems and compares the proposed M-BFFNet with traditional algorithms. The results show that the proposed M-BFFNet improves the identification accuracy compared to other algorithms. According to the analysis of this work, the M-BFFNet can be used to identify CSAs with unknown concentrations.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Simplifying Robot Grasping in Manufacturing with a Teaching Approach based on a Novel User Grasp Metric

引用

Procedia Computer Science 2024年 232卷 1961-1971页

作者： Matteo Pantano Vladislav Klass Qiaoyue Yang Akhil Sathuluri Daniel Regulin Lucas Janisch Markus Zimmermann Dongheui Lee Technology Department Siemens Aktiengesellschaft D-81739 Munich Germany Human-Centered Assistive Robotics Technical University of Munich D-80333 Munich Germany Laboratory for Product Development and Lightweight Design Technical University of Munich D-85748 Garching Germany Autonomous Systems Technische Universität Wien AT-1040 Vienna Austria Institute of Robotics and Mechatronics German Aerospace Center D-82234 Wessling Germany

The manufacturing industry is undergoing rapid evolution, necessitating flexible and adaptable robots. However, configuring such machines requires technical experts, which are hard to find, especially for small and medium enterprises. Therefore, the process needs to be simplified by allowing non-experts to configure robots. During such configuration, one key aspect is the definition of objects’ grasping poses. The literature proposes deep learning techniques to compute grasping poses automatically and facilitate the process. Nevertheless, practical implementation for inexperienced factory operators can be challenging, especially if task-specific knowledge and constraints should be considered. To overcome this barrier, we propose an approach that facilitates teaching such poses. Our method, employing a novel user grasp metric, combines the operator's initial grasp guess given by a 3D spatial device with a state-of-the-art deep learning algorithm, thus returning reliable grasping poses but simultaneously close to the operator's initial guess. We compare this approach against commercial grasping pose definition interfaces through a user test involving 28 participants and against state-of-the-art deep learning grasp estimators. The results demonstrate a significant improvement in system usability (+24%) and a reduced workload (-16%). Furthermore, our experiments reveal an increased grasp success rate when utilizing the user grasp metric, surpassing state-of-the-art deep learning grasping estimators.

关键词： operator empowerment spatial interaction robotic grasping usability small medium enterprises cobots

来源：评论

学校读者我要写书评

暂无评论

SAD-TIME: a Spatiotemporal-fused network for depression detection with Automated multi-scale Depth-wise and TIME-interval-related common feature extractor

arXiv

引用

arXiv 2024年

作者： Wang, Han-Guang Hou, Hui-Rang Jin, Li-Cheng Xu, Chen-Yang Zhang, Zhong-Yi Meng, Qing-Hao Zhang, Yong-Hui Tianjin Key Laboratory of Process Measurement and Control Institute of Robotics and Autonomous Systems School of Electrical and Information Engineering Tianjin University Tianjin300072 China Department of Psychiatry Tianjin Anding Hospital Mental Health Center Tianjin Medical University China

Background and Objective: Depression is a severe mental disorder, and accurate diagnosis is pivotal to the cure and rehabilitation of people with depression. However, the current questionnaire-based diagnostic methods could bring subjective biases and may be denied by subjects. In search of a more objective means of diagnosis, researchers have begun to experiment with deep learning-based methods for identifying depressive disorders in recent years. Methods: In this study, a novel Spatiotemporal-fused network with Automated multi-scale Depth-wise and TIME-interval-related common feature extractor (SAD-TIME) is proposed. SAD-TIME incorporates an automated nodes’ common features extractor (CFE), a spatial sector (SpS), a modified temporal sector (TeS), and a domain adversarial learner (DAL). The CFE includes a multiscale depth-wise 1D-convolutional neural network and a time-interval embedding generator, where the unique information of each channel is preserved. The SpS fuses the functional connectivity with the distance-based connectivity containing spatial position of EEG electrodes. A multi-head-attention graph convolutional network is also applied in the SpS to fuse the features from different EEG channels. The TeS is based on long short-term memory and graph transformer networks, where the temporal information of different time-windows is fused. Moreover, the DAL is used after the SpS to obtain the domain-invariant feature. Results: Experimental results under tenfold cross-validation show that the proposed SAD-TIME method achieves 92.00% and 94.00% depression classification accuracies on two datasets, respectively, in cross-subject mode. Conclusion: SAD-TIME is a robust depression detection model, where the automatedly-generated features, the SpS and the TeS assist the classification performance with the fusion of the innate spatiotemporal information in the EEG signals. Copyright © 2024, The Authors. All rights reserved.

关键词： Convolutional neural networks

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：