检索结果-内蒙古大学图书馆

arXiv 2025年

作者： Huang, Zhiwei Li, Jiaqi Zhong, Ping Fan, Rui The Department of Control Science & Engineering The College of Electronics & Information Engineering Tongji University Shanghai201804 China The School of Computer Science and Engineering Central South University Hunan Changsha410083 China The National Key Laboratory of Science and Technology on Automatic Target Recognition National University of Defense Technology Hunan Changsha410073 China The Department of Control Science & Engineering The College of Electronics & Information Engineering Shanghai Research Institute for Intelligent Autonomous Systems The State Key Laboratory of Intelligent Autonomous Systems Frontiers Science Center for Intelligent Autonomous Systems Tongji University Shanghai201804 China The National Key Laboratory of Human-Machine Hybrid Augmented Intelligence Institute of Artificial Intelligence and Robotics Xi’an Jiaotong University Shaanxi Xi’an710049 China

LiDAR-camera extrinsic calibration (LCEC) is the core for data fusion in computer vision. Existing methods typically rely on customized calibration targets or fixed scene types, lacking the flexibility to handle variations in sensor data and environmental contexts. This paper introduces EdO-LCEC, the first environment-driven, online calibration approach that achieves human-like adaptability. Inspired by the human perceptual system, EdO-LCEC incorporates a generalizable scene discriminator to actively interpret environmental conditions, creating multiple virtual cameras that capture detailed spatial and textural information. To overcome cross-modal feature matching challenges between LiDAR and camera, we propose dual-path correspondence matching (DPCM), which leverages both structural and textural consistency to achieve reliable 3D-2D correspondences. Our approach formulates the calibration process as a spatial-temporal joint optimization problem, utilizing global constraints from multiple views and scenes to improve accuracy, particularly in sparse or partially overlapping sensor views. Extensive experiments on real-world datasets demonstrate that EdO-LCEC achieves state-of-the-art performance, providing reliable and precise calibration across diverse, challenging environments. Copyright © 2025, The Authors. All rights reserved.

关键词： Spatio-temporal data

来源：评论

学校读者我要写书评

暂无评论

Deformation Pattern Shape Sensing for Visuotactile Endoscope

Deformation Pattern Shape Sensing for Visuotactile Endoscope

引用

2024 IEEE International Conference on Real-Time Computing and robotics, RCAR 2024

作者： Yu, Yanzhe Tian, Yuan Cui, Shaowei Wang, Yupeng Wang, Rui Wang, Shuo Beijing University of Science and Technology Beijing100083 China The University of Sheffield Department of Automatic Control and Systems Engineering Sheffield United Kingdom Institute of Automation Chinese Academy of Sciences State Key Laboratory of Multimodal Artificial Intelligence Systems Beijing100190 China University of Chinese Academy of Sciences School of Artificial Intelligence Beijing100049 China Center for Excellence in Brain Science and Intelligence Technology Chinese Academy of Sciences Shanghai200031 China

ISBN: (纸本)9798350372601

The integration of visuotactile sensor technology with endoscopy enables the provision of tactile information for minimally invasive surgeries and other operations. This paper proposes a real-time sensing framework for contact deformation pattern shape, providing a foundation for precise perception in miniaturized visuotactile sensors. Specifically, we first construct a Deformation Pattern shape Descriptor (DPSD) and then track the key points in the descriptor using optical flow to obtain contact deformation shape information. Through extensive qualitative and quantitative experiments, our proposed algorithm achieves an average perception accuracy of around 83.81% for contact pattern shapes. It demonstrates consistent perception accuracy across various contact force magnitudes, directions, and scenarios, highlighting its robustness. Additionally, compared to traditional marker-level methods, it achieves a notable 46.5% improvement in displacement field perception accuracy. This research elevates tactile perception to the dimension of contact pattern shape sensing and has the potential for application in miniaturized visual tactile sensors. © 2024 IEEE.

关键词： Endoscopy

来源：评论

学校读者我要写书评

暂无评论

Deep Domain Adaptation Regression for Force Calibration of Optical Tactile Sensors

arXiv

引用

arXiv 2024年

作者： Chen, Zhuo Ou, Ni Jiang, Jiaqi Luo, Shan Robot Perception Lab Centre for Robotics Research Department of Engineering King’s College London LondonWC2R 2LS United Kingdom State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology Beijing100081 China

Optical tactile sensors provide robots with rich force information for robot grasping in unstructured environments. The fast and accurate calibration of three-dimensional contact forces holds significance for new sensors and existing tactile sensors which may have incurred damage or aging. However, the conventional neural-network-based force calibration method necessitates a large volume of force-labeled tactile images to minimize force prediction errors, with the need for accurate Force/Torque measurement tools as well as a time-consuming data collection process. To address this challenge, we propose a novel deep domain-adaptation force calibration method, designed to transfer the force prediction ability from a calibrated optical tactile sensor to uncalibrated ones with various combinations of domain gaps, including marker presence, illumination condition, and elastomer modulus. Experimental results show the effectiveness of the proposed unsupervised force calibration method, with lowest force prediction errors of 0.102N (3.4% in full force range) for normal force, and 0.095N (6.3%) and 0.062N (4.1%) for shear forces along the x-axis and y-axis, respectively. This study presents a promising, general force calibration methodology for optical tactile sensors. Copyright © 2024, The Authors. All rights reserved.

关键词： Forecasting

来源：评论

学校读者我要写书评

暂无评论

Data-Driven Learning and control with Event-Triggered Measurements

引用

IEEE Transactions on Automatic control 2025年

作者： Feng, Shilun Shi, Dawei Chen, Tongwen Shi, Ling Beijing Institute of Technology State Key Laboratory of Intelligent Control and Decision of Complex Systems MIIT Key Laboratory of Servo Motion System Drive and Control School of Automation Beijing100081 China University of Alberta Department of Electrical and Computer Engineering EdmontonABT6G 1H9 Canada Hong Kong University of Science and Technology Department of Electronic and Computer Engineering Clear Water Bay Kowloon Hong Kong

Event-triggered control has attracted considerable attention for its effectiveness in resource-restricted applications. To make event-triggered control as an end-to-end solution, a key issue is how to effectively learn unknown system dynamics from event-triggered measurements and consequently, develop a learning-based event-triggered controller. Existing works learn system dynamics based on periodic time-triggered measurements, and it is yet to know how to learn a controller with performance guarantee based on event-triggered measurements. To address this issue, we consider the problem of learning an event-triggered state feedback controller for an unknown linear system based on event-triggered state measurements in this work. In particular, we first analyze the event-triggered measurements within a set-membership framework. We prove that the estimation error belongs to a bounded ellipsoid determined by the historical measurements and the event-triggering condition. Subsequently, we demonstrate that all admissible systems compatible with the collected data samples can be explicitly represented in the form of quadratic matrix inequalities using the state estimates. With the acquired set of admissible systems, a co-design problem for the data-driven controller and event-triggering condition is solved using the linear matrix inequality technique, with guaranteed closed-loop stability and L2-gain performance. Finally, numerical examples and comparisons are provided to illustrate the effectiveness of the proposed event-triggered learning and control approach. © 1963-2012 IEEE.

关键词： networked control systems

来源：评论

学校读者我要写书评

暂无评论

TransForce: Transferable Force Prediction for Vision-based Tactile Sensors with Sequential Image Translation

arXiv

引用

arXiv 2024年

作者： Chen, Zhuo Ou, Ni Zhang, Xuyang Luo, Shan The Robot Perception Lab Centre for Robotics Research Department of Engineering King's College London LondonWC2R 2LS United Kingdom The State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology Beijing100081 China

Vision-based tactile sensors (VBTSs) provide high-resolution tactile images crucial for robot in-hand manipulation. However, force sensing in VBTSs is underutilized due to the costly and time-intensive process of acquiring paired tactile images and force labels. In this study, we introduce a transferable force prediction model, TransForce, designed to leverage collected image-force paired data for new sensors under varying illumination colors and marker patterns while improving the accuracy of predicted forces, especially in the shear direction. Our model effectively achieves translation of tactile images from the source domain to the target domain, ensuring that the generated tactile images reflect the illumination colors and marker patterns of the new sensors while accurately aligning the elastomer deformation observed in existing sensors, which is beneficial to force prediction of new sensors. As such, a recurrent force prediction model trained with generated sequential tactile images and existing force labels is employed to estimate higher-accuracy forces for new sensors with lowest average errors of 0.69N (5.8% in full work range) in x-axis, 0.70N (5.8%) in y-axis, and 1.11N (6.9%) in z-axis compared with models trained with single images. The experimental results also reveal that pure marker modality is more helpful than the RGB modality in improving the accuracy of force in the shear direction, while the RGB modality show better performance in the normal direction. Copyright © 2024, The Authors. All rights reserved.

关键词： RGB color model

来源：评论

学校读者我要写书评

暂无评论

Complex Fusion Structure Slow Dissociation Simulation Prediction Method

Complex Fusion Structure Slow Dissociation Simulation Predic...

引用

Chinese Automation Congress (CAC)

作者： Dongsheng Zhang Yigeng Wang Wanyi Huang Naval Architecture & Ocean Engineering Institute China Shipbuilding NDRI Engineering Co. Ltd Shanghai China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China School and Hospital of Stomatology China Medical University Shenyang China Liaoning Provincial Key Laboratory of Oral Diseases China Medical University Shenyang China

ISBN: (数字)9798350368604

ISBN: (纸本)9798350368611

Human skeletal implants, as a category of critically important medical consumables, are designed to remain inside the body for long periods. Titanium or titanium alloys are commonly chosen as the primary construction materials. Recently, the academic community has explored an innovative approach to implant construction that uses titanium as the base framework and zinc as the filling material to create an interconnected composite structure. In this structure, zinc gradually dissolves over the lifetime of the implant, promoting bone growth into the pores formed after its dissolution. Given the continuous dissociation of zinc, the physical and chemical properties of the implant exhibit a slow and continuous change over its lifecycle. However, there is currently no effective method to precisely predict and assess the state changes of such complex structures over long periods of time. This study focuses on the typical application scenarios of human skeletal implants, and verifies the accuracy of short-term steady-state numerical calculation models through rigorous experimental methods. Based on this, we propose a complex fusion structure slow dissociation reverse simulation prediction method based on short-term steady-state calculation results. This method aims to simulate the steady-state performance of implants in the short term, and reverse deduce the structural changes and performance evolution caused by zinc dissociation during long-term use, thereby providing a more scientific basis and support for the design and evaluation of medical implants.

关键词： Titanium alloys Implants Prediction methods Market research Filling Steady-state Numerical models Forecasting Zinc Periodic structures

来源：评论

学校读者我要写书评

暂无评论

Cooperative Reward Shaping for Multi-Agent Pathfinding

SSRN

引用

SSRN 2025年

作者： Song, Zhenyu Zheng, Ronghao Zhang, Senlin Liu, Meiqin Zhejiang University China College of Electrical Engineering Zhejiang University Hangzhou310027 China State Key Laboratory of Industrial Control Technology Zhejiang University Hangzhou310027 China Artificial Intelligence and Robotics Xi’an Jiaotong University Xi’an710049 China

Multi-agent pathfinding primarily aims to plan efficient and conflict-free paths for all agents. Reinforcement learning has been demonstrated as a promising approach to address the multi-agent pathfinding problem by learning decentralized policies in partially observable environments. A critical challenge when applying reinforcement learning to solve multi-agent pathfinding is designing an appropriate reward function that enables agents to avoid collision among themselves under partial observation. This work proposes a reward shaping method to facilitate cooperative collision avoidance. Specifically, the method introduces a metric to evaluate the impact of an agent’s actions on its neighboring agents and integrates this metric into the reward function. This design prevents agents from competing with each other by maximizing their own cumulative rewards, thus facilitating cooperative collision avoidance. This method is utilized solely within the training stage and improves the success rate of multi-agent pathfinding tasks without increasing the computational load during network inference. The experimental results show that the proposed method improves the success rate of MAPF tasks for the baseline algorithm by up to 20%, achieving comparable performance as state-of-the-art algorithms with significantly lower computational load. © 2025, The Authors. All rights reserved.

关键词： Reinforcement learning

来源：评论

学校读者我要写书评

暂无评论

Extended state Observer Based Fault-Tolerant Predictive control for a Four-Mecanum Wheels Mobile Robot

Extended State Observer Based Fault-Tolerant Predictive Cont...

引用

IEEE International Conference on Cyber Technology in Automation, control, and Intelligent systems

作者： Binghao Yang Dongliang Wang Ziling Wen Wu Wei Wenji Li Zhun Fan Key Lab of Digital Signal and Image Processing of Guangdong Province Shantou University Guangdong China School of Department of Electronic and Information Engineering Shantou University Guangdong China Key Laboratory of Autonomous Systems and Networked Control Ministry of Education Guangzhou Guangdong China School of Automation Science and Engineering South China University of Technology Guangzhou Guangdong China

ISBN: (数字)9798331506056

ISBN: (纸本)9798331506063

The application of unmanned vehicles in industrial cargo transportation is becoming increasingly widespread, particularly playing a significant role in transporting heavy-duty goods. However, when performing such tasks, whether in single-vehicle transportation or multi-vehicle collaborative transportation, the occurrence of wheel failures can potentially lead to serious safety accidents. Therefore, this paper proposes a fault-tolerant control scheme, establishing a kinematic model considering disturbances and failures, and adopts model predictive control for trajectory tracking. Additionally, an extended state observer is introduced to observe system states and counteract disturbances. To address potential failure issues, a controller reconstruction strategy is proposed. Finally, the effectiveness and superiority of the controller is validated through numerical simulation and comparative experiment.

关键词： Fault tolerance Trajectory tracking Fault tolerant systems Wheels Transportation Kinematics Predictive models Safety state estimation Predictive control

来源：评论

学校读者我要写书评

暂无评论

Roller-Quadrotor: A Novel Hybrid Terrestrial/Aerial Quadrotor with Unicycle-Driven and Rotor-Assisted Turning

arXiv

引用

arXiv 2023年

作者： Zheng, Zhi Wang, Jin Wu, Yuze Cai, Qifeng Yu, Huan Zhang, Ruibin Tu, Jie Meng, Jun Lu, Guodong Gao, Fei The State Key Laboratory of Fluid Power and Mechatronic Systems School of Mechanical Engineering Zhejiang University Hangzhou310027 China Robotics Institute of Zhejiang University Hangzhou310027 China Robotics Research Center of Yuyao City Ningbo315400 China The State Key Laboratory of Industrial Control Technology Zhejiang University Hangzhou310027 China Huzhou Institute of Zhejiang University Huzhou313000 China Center for Data Mining and Systems Biology College of Electrical Engineering Zhejiang University Hangzhou310027 China

The Roller-Quadrotor is a novel quadrotor that combines the maneuverability of aerial drones with the endurance of ground vehicles. This work focuses on the design, modeling, and experimental validation of the Roller-Quadrotor. Flight capabilities are achieved through a quadrotor configuration, with four thrust-providing actuators. Additionally, rolling motion is facilitated by a unicycle-driven and rotor-assisted turning structure. By utilizing terrestrial locomotion, the vehicle can overcome rolling and turning resistance, thereby conserving energy compared to its flight mode. This innovative approach not only tackles the inherent challenges of traditional rotorcraft but also enables the vehicle to navigate through narrow gaps and overcome obstacles by taking advantage of its aerial mobility. We develop comprehensive models and controllers for the Roller-Quadrotor and validate their performance through experiments. The results demonstrate its seamless transition between aerial and terrestrial locomotion, as well as its ability to safely navigate through gaps half the size of its diameter. Moreover, the terrestrial range of the vehicle is approximately 2.8 times greater, while the operating time is about 41.2 times longer compared to its aerial capabilities. These findings underscore the feasibility and effectiveness of the proposed structure and control mechanisms for efficient navigation through challenging terrains while conserving energy. Copyright © 2023, The Authors. All rights reserved.

关键词： Antennas

来源：评论

学校读者我要写书评

暂无评论

An Algorithm for Solving the Pose of Bio 3D Printing based on Neural Network

An Algorithm for Solving the Pose of Bio 3D Printing based o...

引用

第34届中国控制与决策会议

作者： Jian Liu Zili Song Huixuan Zhu Hang Yuan School of Information and Control Engineering Shenyang Jianzhu University State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences

Obtaining the pose state information of the printing nozzle in real time and performing error compensation is an important means to improve the accuracy of biological 3D *** pose solving methods such as Newton iteration method and Analysis method have problems such as difficulty in selecting the initial value and slow calculation *** solve the above problems,a biological 3D printing pose solution algorithm based on the Elman neural network optimized by genetic algorithm is ***,the kinematics model of the biological 3D printing platform is established,then the GA-Elman neural network is established and the inverse solution of the platform is used as a training sample,and the pose information is solved by the method of network learning,and finally the accuracy of the algorithm is verified by *** simulation results show that the algorithm has high calculation accuracy and fast solution speed,and can quickly and accurately solve the pose of biological 3D printing.

关键词： Biological 3D printing Pose solving Neural Network Real time

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：