检索结果-内蒙古大学图书馆

An economical, Lego-like approach for real-time magnetic field mapping (MagMaps) using commercial magnetic sensors

IEEE Transactions on Instrumentation and Measurement 2022年 1-1页

作者： Ahmed, Awais Abbasi, Sarmad Ahmad Gharamaleki, Nader Latifi Kim, Jin-Young Choi, Hongsoo Department of Robotics and Mechatronics Engineering and DGIST-ETH Microrobot Research Center Daegu Gyeongbuk Institute of Science and Technology Daegu South Korea

Magnetic field mapping is tedious;a magnetometer probe collects magnetic field data in a point-by-point manner within a two-dimensional (2D) or three-dimensional (3D) space. Magnetometer arrays accelerate this process by replacing point-by-point mapping with plane-by-plane mapping. When mapping a large space, a motorized stage is additionally required;the limitations include power inefficiencies, large footprints, cost, and the absence of real-time data acquisition. Here, we introduce MagMaps, a modular Lego-like approach to magnetic field mapping that overcomes the limitations described above. MagMaps includes a set of physically identical modules termed “MagBricks” that can be stacked in all three axes (similar to Lego bricks);this covers the region of interest and eliminates the need for a motorized stage. Each MagBrick is an independent enslaved module with a unique address, having a microcontroller that continuously acquires magnetic field data from a magnetometer array. An additional brick termed the “MasterBrick” serves as a bridge between the computer and the MagBricks. The MasterBrick collects magnetic field data from uniquely addressed MagBricks and communicates them to a computer, where they are sorted and displayed in real-time. This modular Lego-like approach and the use of only off-the-shelf electronic components allows MagMaps to offer real-time magnetic field mapping that is portable, power-efficient, and economical for various 2D or 3D spaces. IEEE

关键词： Real time systems

来源：评论

学校读者我要写书评

暂无评论

Learning Skateboarding for Humanoid Robots through Massively Parallel Reinforcement Learning

arXiv

引用

arXiv 2024年

作者： Thibault, William Rajendran, Vidyasagar Melek, William Mombaur, Katja Department of Mechanical and Mechatronics Engineering University of Waterloo WaterlooONN2L 3G1 Canada The Department of Systems Design Engineering CERC Human-Centred Robotics and Machine Intelligence University of Waterloo Canada Karlsruhe Germany

Learning-based methods have proven useful at generating complex motions for robots, including humanoids. Reinforcement learning (RL) has been used to learn locomotion policies, some of which leverage a periodic reward formulation. This work extends the periodic reward formulation of locomotion to skateboarding for the REEM-C robot. Brax/MJX is used to implement the RL problem to achieve fast training. Initial results in simulation are presented with hardware experiments in progress. © 2024, CC BY.

关键词： Reinforcement learning

来源：评论

学校读者我要写书评

暂无评论

Kinematic Modeling of a 7-DOF Tendon-Like-Driven Robot Based on Optimization and Deep Learning

引用

Journal of Field robotics 2025年

作者： Chen, SaiXuan Mu, SaiHu Jiang, GuanWu Omar, Abdelaziz Zhu, Zina Niu, Fuzhou School of Mechanical and Automotive Engineering Shanghai University of Engineering Science Shanghai China School of Mechanical Engineering Tongji University Shanghai China School of Information Engineering Southwest University of Science and Technology Mianyang China Mechatronics and Robotics Department Egyptian Russian University Badr city Cairo Egypt School of Mechanical Engineering Suzhou University of Science and Technology Suzhou China

This paper proposes a novel 7-DOF tendon-like-driven redundant robot (TDR7) based on a weighted inverse kinematics (IK) optimization algorithm and a deep learning fine-tuning model. The robot features a modular design that enables highly flexible movements of the shoulder, elbow, and wrist joints. Its kinematic model is established using the Denavit-Hartenberg (D-H) parameter method. To address the complexity of solving IK for 7-DOF redundant robots, a weighted gradient projection method specialized for TDR7 (SWGPM-TDR7) is introduced. This algorithm integrates joint constraints, singularity avoidance, and minimum energy consumption into a multi-objective optimization framework, significantly improving joint motion continuity and trajectory planning efficiency while maintaining solution accuracy. To further accommodate complex trajectory planning requirements, a deep learning fine-tuning model (RWKV-TDR7) that combines recurrent networks with self-attention mechanisms is introduced. Through fine-tuning, RWKV-TDR7 achieves efficient trajectory fitting for TDR7, supports long-sequence outputs, and reduces computational complexity. Simulation and experimental validations demonstrate that the robot exhibits excellent performance in forward kinematics, inverse kinematics, and trajectory tracking in terms of accuracy, stability, and continuity. This work provides an effective solution for the design of high-performance robotic systems in medical and industrial applications. © 2025 Wiley Periodicals LLC.

关键词： Inverse kinematics

来源：评论

学校读者我要写书评

暂无评论

Modelling Traffic Scenarios via Markovian Opinion Dynamics

Modelling Traffic Scenarios via Markovian Opinion Dynamics

引用

International Conference on Intelligent Transportation

作者： Elisa Gaetan Laura Giarré Simona Sacone Paolo Falcone Carl-Johan Heiker Engineering Department ‘Enzo Ferrari’ University of Modena and Reggio Emilia Modena Italy Department of Informatics Bioengineering Robotics and Systems Engineering ‘DIBRIS’ University of Genova Italy Department of Electrical Engineering Mechatronics group Chalmers University of Technology Gothenburg Sweden

We address the question of whether opinion dynamics models can be exploited in novel scenarios, such as traffic flow on highway lanes. In this paper, we design a Markovian model and compare its predictions with those obtained from the widely recognized Cell Transmission Model (CTM) for the same traffic scenario. We identify potential challenges that may arise and propose strategies to address them. Furthermore, we present a concise demonstration showcasing the predictive capabilities of our proposed model through a small-scale example.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Explicit Model Predictive Control for Trajectory Tracking of Autonomous Vehicle

Explicit Model Predictive Control for Trajectory Tracking of...

引用

2023 China Automation Congress, CAC 2023

作者： Lai, Xiangkang Jiang, Haolong Liu, Qinyao Guo, Qian Wang, Xuchen School of Advanced Technology Xi'an Jiaotong Liverpool University Suzhou China School of Advanced Technology Xi'an Jiaotong Liverpool University Department of Mechatronics and Robotics Suzhou China Institute of Intelligent Manufacturing and Smart Transportation Suzhou City University Suzhou China School of Advanced Technology Xi'an Jiaotong Liverpool University Department of Electrical and Electronic Engineering Suzhou China

ISBN: (纸本)9798350303759

Autonomous vehicle has been attached more and more attention since it is considered as an effective solution to transportation problems. This paper focuses on the trajectory tracking control algorithms for autonomous vehicles. To improve the computational efficiency, a constrained explicit controller with offline optimization and online search is proposed based on the original model predictive control (MPC) algorithm. The joint simulation based on the Simulink and Carsim is designed to evaluate the performance of proposed explicit controller. The results show that compared with the original MPC controller, the explicit controller can significantly reduce optimization time and achieve relatively similar tracking performance. © 2023 IEEE.

关键词： Model predictive control

来源：评论

学校读者我要写书评

暂无评论

Optimal Stabilization of Periodic Orbits

引用

IFAC-PapersOnLine 2023年第2期56卷 7509-7515页

作者： Fabian Beck Noboru Sakamoto Institute of Robotics and Mechatronics German Aerospace Center (DLR) 82234 Wessling Germany Department of Mechanical Engineering and System Control Nanzan University Yamzato-cho 18 Showa-ku Nagoya 466-8673 Japan

In this contribution the optimal stabilization problem of periodic orbits is studied in a symplectic geometry setting. For this, the stable manifold theory for the point stabilization case is generalized to the case of periodic orbit stabilization. Sufficient conditions for the existence of a normally hyperbolic invariant manifold (NHIM) of the Hamiltonian system are derived. It is shown that the optimal control problem has a solution if the related periodic Riccati equation has a unique periodic solution. For the analysis of the stable and unstable manifold a coordinate transformation is used which is moving along the orbit. As an example, an optimal control problem is considered for a spring-mass oscillator system, which should be stabilized at a certain energy level.

关键词： Hamiltonian Dynamics Nonlinear Control Periodic Orbit Optimal Control

来源：评论

学校读者我要写书评

暂无评论

From Learning Agents to Agile Software: Reinforcement Learning's Transformative Role in Requirements engineering

From Learning Agents to Agile Software: Reinforcement Learni...

引用

IEEE Southeastcon

作者： Faraz Frank Parsa Amir Ali Amiri Moghadam Turaj Ashuri Department of Computer and Software Engineering Faculty of Artificial Inteligence Karaj Azad University Karaj Persian Department of Robotics and Mechatronics Engineering Southern Polytechnic College of Engineering and Engineering Technology Kennesaw State University Marietta GA USA Southern Polytechnic College of Engineering and Engineering Technology Kennesaw State University Marietta GA USA

This paper studies the trans formative role of Reinforcement Learning for Requirements engineering in the context of software development. The integration of Reinforcement Learning, with its adaptive decision-making capabilities, and Requirements engineering, focused on systematic requirement analysis, offers a promising interaction to address challenges in dynamic project environments. The paper discusses the potential benefits, including adaptive decision-making, optimization in uncertainty, and intelligent requirement prioritization. However, challenges such as complexity, interpretability, data availability, resource intensiveness, and ethical concerns are identified. The conclusion highlights the trans formative potential of this integration while emphasizing the importance of addressing challenges through interdisciplinary collaboration and responsible adoption in different environments. The paper serves as a broad study of the intersection of Reinforcement Learning and Requirements engineering, providing insights for practitioners, researchers, and stakeholders in the field of software development.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Automated Feedback in Software engineering: Enhancing Computational Thinking Process

Automated Feedback in Software Engineering: Enhancing Comput...

引用

IEEE Southeastcon

作者： Faraz Parsa Amir Ali Amiri Moghadam Turaj Ashuri Department of Computer and Software Engineering Faculty of Artificial Inteligence Karaj Azad University Karaj Iran Department of Robotics and Mechatronics Engineering Southern Polytechnic College of Engineering and Engineering Technology Kennesaw State University Marietta GA USA Southern Polytechnic College of Engineering and Engineering Technology Kennesaw State University Marietta GA USA

Computational thinking is the systematic approach of defining a problem and crafting its solution. It employs computer programming algorithms to address scientific, engineering, and mathematical challenges using programming languages. Feedback plays a pivotal role in the learning journey of computational thinking. It is widely recognized that offering timely feedback to students on their computational endeavors significantly contributes to their achievement and overall satisfaction with the course. This research explores the implementation of an automated feedback system designed to evaluate and offer early feedback on computer engineering projects. The aim is to integrate best practices and software tools related to computational thinking into the thinking and learning processes within an engineering curriculum. Preliminary findings suggest that the automated feedback system enhances students' computational skills and improves their performance in the course. We anticipate that the insights gained from this research will inform the enhancement of curricula and course evaluations across different computational thinking tasks, disciplines, and courses.

关键词：

来源：评论

学校读者我要写书评

暂无评论

A Study on Reduction of AC Copper Loss According to Pole/Slot Combination of EV Traction Motor

A Study on Reduction of AC Copper Loss According to Pole/Slo...

引用

IEEE Conference on Electromagnetic Field Computation

作者： Jin-Uk Choi Ki-Deok Lee Jae-Kwang Lee Jeong-Jong Lee Myung-Hwan Yoon Dong-Hoon Jeong Ju Lee Intelligent Mechatronics Research Center Korea Electronics Technology Institude Bucheon South Korea Department of Mechanical and Automotive Robotics Halla University Wonju South Korea Department of Electrical Engineering Hanyang University Seoul South Korea

ISBN: (数字)9798350348958

ISBN: (纸本)9798350348965

This paper is about reducing AC copper loss of an EV traction motor with a maximum speed of 21000 rpm. Recently, as a high-power density design method for traction motors for EVs, the advantages of high slot fill factor and short end turns of hairpin windings have emerged. However, when using hairpin windings, AC copper loss increases at higher speeds, greatly reducing efficiency and power density, so measures to reduce this loss are necessary. AC copper loss is largely divided into skin effect, proximity effect, and eddy current loss due to leakage magnetic flux, which all increase in proportion to the frequency of use. In this paper, the characteristics according to pole/slot combination were analyzed by comparing the AC copper loss and output characteristics at the rated and maximum speed operating points of the 8p/48s model and the 6p/36s model.

关键词： Stator cores Magnetic flux density Density measurement Magnetic cores Windings Traction motors Loss measurement

来源：评论

学校读者我要写书评

暂无评论

A Robust Control Technique for Pitch Control of an Aeropendulum

A Robust Control Technique for Pitch Control of an Aeropendu...

引用

robotics, Control and Automation engineering (RCAE), International Conference on

作者： M. Hassan Tanveer Charles Koduru Rupam Gupta Roy Girish V. Lakhekar Cary Chun Department of Robotics and Mechatronics Engineering Kennesaw State University Marietta GA United States Department of Electronics and Instrumentation Engineering National Institute of Technology Agartala Barjala Jirania Agartala Tripura India Department of Instrumentation Engineering College of Engineering Pune Maharashtra India

Pitch control of an aviation system presents a plethora of control complications, such as nonlinear effects, parameter uncertainties, disturbances, etc. In the face of parametric uncertainties and disturbances, as well as communication limits in an auditory medium, it is difficult to create efficient control algorithms that can accomplish precise path-following tasks and effective resilient control actions. This paper presents the Second Order Sliding Mode Control method for regulating the pitch angle in an aero-pendulum mechatronic system. The fundamental purpose of this study is to develop a reliable controller capable of minimising the system error between the regulated signal and the planned signal that corresponds to the pitch angle of the vehicle. By employing the proposed approach, both the prevalence of chattering and the control efficiency can be greatly improved. A comparison is given between the proposed model and the classical technique now in use, such as the classical Sliding Mode Controller.

关键词：

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：