检索结果-内蒙古大学图书馆

A memory-based BCI approach for training of executive function in ASD

Brain Stimulation 2023年第1期16卷 264-265页

作者： Dias, Camila Sousa, Teresa Cruz, Aniana Costa, Diana Castelhano, João Pires, Gabriel Castelo-Branco, Miguel CIBIT – Coimbra Institute for Biomedical Imaging and Translational Research University of Coimbra Portugal ICNAS - Institute for Nuclear Sciences Applied to Health University of Coimbra Portugal FMUC - Faculty of Medicine University of Coimbra Portugal ISR - Institute of Systems and Robotics University of Coimbra Portugal Polytechnic Institute of Tomar Department of Engineering Portugal

来源：评论

学校读者我要写书评

暂无评论

Tiny-PULP-Dronets: Squeezing Neural Networks for Faster and Lighter Inference on Multi-Tasking Autonomous Nano-Drones

arXiv

引用

arXiv 2024年

作者： Lamberti, Lorenzo Niculescu, Vlad Barcis, Michal Bellone, Lorenzo Natalizio, Enrico Benini, Luca Palossi, Daniele Department of Electrical Electronic and Information Engineering University of Bologna Italy Integrated Systems Laboratory ETH Zürich Switzerland Autonomous Robotics Research Center Technology Innovation Institute United Arab Emirates Dalle Molle Institute for Artificial Intelligence USI SUPSI Switzerland

Pocket-sized autonomous nano-drones can revolutionize many robotic use cases, such as visual inspection in narrow, constrained spaces and ensure safer human-robot interaction due to their tiny form factor and weight - i.e., tens of grams. This compelling vision is challenged by the high level of intelligence needed aboard, which clashes against the limited computational and storage resources available on PULP (parallel-ultra-low-power) MCU class navigation and mission controllers that can be hosted aboard. This work moves from PULP-Dronet, a State-of-the-Art convolutional neural network for autonomous navigation on nano-drones. We introduce Tiny-PULP-Dronet: a novel methodology to squeeze by more than one order of magnitude model size (50× fewer parameters), and number of operations (27× less multiply-and-accumulate) required to run inference with similar flight performance as PULP-Dronet. This massive reduction paves the way towards affordable multitasking on nano-drones, a fundamental requirement for achieving high-level intelligence. Copyright © 2024, The Authors. All rights reserved.

关键词： Drones

来源：评论

学校读者我要写书评

暂无评论

Multi-contact Stochastic Predictive Control for Legged Robots with Contact Locations Uncertainty

arXiv

引用

arXiv 2023年

作者： Gazar, Ahmad Khadiv, Majid Del Prete, Andrea Righetti, Ludovic Max Planck Institute for Intelligent Systems Tuebingen Germany Munich Institute of Robotics and Machine Intelligence Technical University of Munich Germany Industrial Engineering Department University of Trento Italy Tandon School of Engineering New York University New York United States

Trajectory optimization under uncertainties is a challenging problem for robots in contact with the environment. Such uncertainties are inevitable due to estimation errors, control imperfections, and model mismatches between planning models used for control and the real robot dynamics. This induces control policies that could violate the contact location constraints by making contact at unintended locations, leading to unsafe motion plans. This work addresses the problem of robust kino-dynamic whole-body trajectory optimization using stochastic nonlinear model predictive control (SNMPC) by considering additive uncertainties on the model dynamics subject to contact location chance constraints as a function of the robot’s full kinematics. We demonstrate the benefit of using SNMPC over classic nonlinear MPC (NMPC) for whole-body trajectory optimization in terms of contact location constraint satisfaction (safety). We run extensive Monte-Carlo simulations for a quadruped robot performing agile trotting and bounding motions over small stepping stones, where contact location satisfaction becomes critical. Our results show that SNMPC can perform all motions safely with 100% success rate, while NMPC failed 48.3% of all motions. © 2023, CC BY.

关键词： Stochastic systems

来源：评论

学校读者我要写书评

暂无评论

Terrain Classification Using Inside-Wheel Cameras Based on Wheel-Terrain Interaction Characteristics

Terrain Classification Using Inside-Wheel Cameras Based on W...

引用

IEEE International Conference on robotics and Biomimetics

作者： Longteng Hu Feng Xue Chen Yao Yunzhou Li Jin Wei Peichen Wang Zheng Zhu Zhenzhong Jia Department of Mechanical and Energy Engineering Shenzhen Key Laboratory of Biomimetic Robotics and Intelligent Systems Southern University of Science and Technology (SUSTech) Shenzhen China Harbin of Institute of Technology (HIT) Harbin China

The wheeled rover is widely used in off-road planetary exploration tasks nowadays. However, complex operating environment like soft deformable terrains on the planet surface demands the high performance of rover. In order to reduce danger, environmental perception technologies need to be used on the rover. Terrain classification is a critical method in environmental perception. In this research, a wheel-vision-based terrain classification method is proposed. This method uses wheel-terrain interaction parameters obtained from inside-wheel cameras which are strongly related to the terrain as input. We use single-wheel testbed to collect and process data to form a dataset. The data is obtained under different slip ratios and different terrains. Then, we train four terrain classification models using machine learning algorithms and analyze their performance. From the results, all performance criteria of the models achieve over 95%, with DT being the optimal method. The feasibility of our method in the case of fewer training samples and the rationality of dataset selection are also verified through the results of different training set sizes and the ablation experiment.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Industrial Wireless Network Access Selection Based on Multilevel Fuzzy Neural Network

Industrial Wireless Network Access Selection Based on Multil...

引用

Chinese Control and Decision Conference, CCDC

作者： Yan Xu Zhijun Gao Sichao Zhang School of Electrical and Control Engineering Shenyang Jianzhu University Shenyang China State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China

ISBN: (数字)9798350387780

ISBN: (纸本)9798350387797

In order to solve the issues in the heterogeneous industrial wireless network access selection such as delay and reliability, this paper present an industrial wireless network access selection based on multilevel fuzzy neural network. The algorithm divides the input attributes into three categories: network attributes, terminal attributes, and environment attributes. It synchronously inputs them into the fuzzy neural network to obtain the candidate network scores, which effectively reduces the number of fuzzy rules and reduces the algorithm complexity. Furthermore, this paper also consider the influence of the industrial environment on network selection and quantitatively reduce the number of switching and blocking rate. The simulation experimental results show that this algorithm is able to achieve fast network access selection in noisy and occluded industrial heterogeneous wireless networks, and the blocking rate can remain low in the presence of dense terminals.

关键词： Wireless networks Neural networks Switches Mean square error methods Interference Fuzzy neural networks Delays

来源：评论

学校读者我要写书评

暂无评论

Exploring Neural Networks for Forward Kinematics of the Robotic Arm with Different Length Configurations: A Comparative Analysis

Exploring Neural Networks for Forward Kinematics of the Robo...

引用

Interdisciplinary Approaches in Technology and Management for Social Innovation (IATMSI), IEEE Conference on

作者： Rania Bouzid Jyotindra Narayan Hassène Gritli Higher Institute of Information and Communication Technologies University of Carthage RISC Laboratory (LR16ES07) Borj Cedria Tunisia Department of Mechanical Engineering Mechatronics and Robotics Laboratory Indian Institute of Technology Guwahati Guwahati Assam India Laboratory of Robotics Informatics and Complex Systems (RISC Lab - LR16ES07) National Engineering School of Tunis University of Tunis El Manar Tunis Tunisia

Our work investigates the utilization of Artificial Neural Networks (ANNs) to address the complexities associated with Forward Kinematics (FK) problems within the field of robotics. We undertake an extensive comparative analysis to assess how ANNs perform under different circumstances with robotic arms of varying lengths and impact the overall system’s functionality. The training, testing, and validation of ANNs are carried out using MATLAB for a simulated 2-DoF serial robotic arm involving three distinct datasets: fixed step size, random step size, and sinusoidal step size. Three training optimizers, namely Levenberg Marquardt (LM), Bayesian Regularization (BR), and Stochastic Conjugate Gradient (SCG), are considered within the ANN architecture. Based on Mean Square Error (MSE) values, the numerical findings reveal the potential of ANN in estimating forward kinematic solutions of complex robotic manipulators with different arm lengths and reducing computational complexity.

关键词：

来源：评论

学校读者我要写书评

暂无评论

End-to-End Reinforcement Learning for Torque Based Variable Height Hopping

arXiv

引用

arXiv 2023年

作者： Soni, Raghav Harnack, Daniel Isermann, Hauke Fushimi, Sotaro Kumar, Shivesh Kirchner, Frank Department of Electronics Engineering Indian Institute of Technology Banaras Hindu University Varanasi India DFKI GmbH Robotics Innovation Center Bremen Germany Undergraduate Course Program of Mechanical and Systems Engineering Kyoto University Kyoto Japan

Legged locomotion is arguably the most suited and versatile mode to deal with natural or unstructured terrains. Intensive research into dynamic walking and running controllers has recently yielded great advances, both in the optimal control and reinforcement learning (RL) literature. Hopping is a challenging dynamic task involving a flight phase and has the potential to increase the traversability of legged robots. Model based control for hopping typically relies on accurate detection of different jump phases, such as lift-off or touch down, and using different controllers for each phase. In this paper, we present a end-to-end RL based torque controller that learns to implicitly detect the relevant jump phases, removing the need to provide manual heuristics for state detection. We also extend a method for simulation to reality transfer of the learned controller to contact rich dynamic tasks, resulting in successful deployment on the robot after training without parameter tuning. © 2023, CC BY-NC-SA.

关键词： Reinforcement learning

来源：评论

学校读者我要写书评

暂无评论

Comparative analysis of monocular slam algorithms using tum and euroc benchmarks 15th

Comparative analysis of monocular slam algorithms using tum ...

引用

15th International Conference on Electromechanics and robotics Zavalishin’s Readings, ERZR 2020

作者： Mingachev, Eldar Lavrenov, Roman Magid, Evgeni Svinin, Mikhail Intelligent Robotics Department Higher Institute for Information Technology and Intelligent Systems Kazan Federal University Kazan Russia College of Information Science and Engineering Ritsumeikan University Kyoto Japan

ISBN: (纸本)9789811555794

Stable and robust path planning and movement in ground mobile robots require a combination of accuracy and low latency in their state estimation. However, state estimation algorithms must provide these qualities under the computational and power constraints of embedded hardware. Simultaneous localization and mapping (SLAM) algorithms are the best choices for state estimation in these scenarios, in addition to their ability to operate without external localization from motion capture or global positioning systems. Moreover, a single-camera setup is the most common solution for robotic platforms, which reduces our domain of interest to the specific SLAM algorithms type—monocular SLAM. Yet, it is still not clear from the existing literature, which monocular SLAM algorithms perform well under the accuracy, latency, and computational constraints of a ground mobile robot with onboard state estimation. This paper evaluates an array of the most recent publicly available monocular SLAM methods: ORB-SLAM2, DSO, and LDSO. The evaluation considers the pose estimation accuracy (alignment error, absolute trajectory error, and relative pose error) while processing the TUM Mono and EuRoC datasets on the specific hardware platform with a balanced amount of computational resources and power consumption. We present our complete results as a benchmark for the research community. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2021.

关键词： State estimation

来源：评论

学校读者我要写书评

暂无评论

Design and Simulation of a Helical Microrobot for Maximum Speed Enhancement by Physical Surface Modification

Design and Simulation of a Helical Microrobot for Maximum Sp...

引用

IEEE International Conference on Real-time Computing and robotics (RCAR)

作者： Siyu Guo Maolin Wang Huaping Wang Shihao Zhong Yukang Qiu Yaozhen Hou Qing Shi Toshio Fukuda School of Mechatronical Engineering Intelligent Robotics Institute Beijing Institute of Technology Beijing China Key Laboratory of Biomimetic Robots and Systems (Beijing Institute of Technology) Ministry of Education Beijing China School of Medical Technology Beijing Institute of Technology Beijing China Beijing Advanced Innovation Center for Intelligent Robots and Systems Beijing Institute of Technology Beijing China

Magnetic helical microrobots have great potential in biomedical applications. However, improving their motion performance in the complex and variable in vivo fluid environment remains challenging. Previous researches mainly focus on optimizing the geometric parameter, the evolutionary structure design, and chemical modifications of the robots, with limited attention given to the impact of physical surface modifications on propulsion performance. To address this issue, we design the helical microrobot with different surface physical modifications, including dimpled and raised surfaces, to evaluate their effects on swimming performance. With ANSYS Fluent, we simulated their swimming process in water and found that microrobots with physically modified surfaces experience less resistance and exhibit a larger step-out frequency while swimming. Moreover, our findings suggest that helical microrobots with dimpled surfaces demonstrate superior swimming performance due to their larger gas-liquid interface area compared to those with raised surfaces.

关键词：

来源：评论

学校读者我要写书评

暂无评论

UAV Path Planning Based on Simultaneous Optimization of Monitoring Frequency and Security

UAV Path Planning Based on Simultaneous Optimization of Moni...

引用

第34届中国控制与决策会议

作者： Yifei Shu Yang Chen Mian Hu Huaiyu Wu Xingang Zhao Institute of Robotics and Intelligent Systems Wuhan University of Science and Technology Engineering Research Center for Metallurgical Automation and Measurement Technology of Ministry of Education State Key Laboratory of Robotics Shenyang Institute of AutomationChinese Academy of Sciences

UAVs have great potential when applied to persistent monitoring,but there are still problems such as difficulty in ensuring the monitoring frequency and easy leakage of monitoring path ***,it is necessary to increase the UAV monitoring frequency of targets and the randomness of monitoring paths as much as possible on the premise of covering all monitoring *** response to the above problems,this paper studies the UAV path planning problem of simultaneous optimization of monitoring frequency and path *** the evaluation of monitoring frequency and path security based on monitoring overdue time and path entropy,a mathematical model for UAV path planning is *** improved ant colony algorithm based on the monitoring overdue time(Overdue-aware Ant Colony Optimization,OACO) is designed,and finally the UAV flight trajectory with high monitoring frequency and the high monitoring path security is *** simulation results show that the method proposed in this paper can effectively improve the monitoring frequency of each monitoring node to be accessed,improve the security of the UAV monitoring path,which is of great significance for enhancing monitoring security and preventing intrusion.

关键词： UAV persistent monitoring path planning monitoring frequency overdue time security

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：