检索结果-内蒙古大学图书馆

arXiv 2023年

作者： Li, Haojia Wang, Haokun Feng, Chen Gao, Fei Zhou, Boyu Shen, Shaojie School of Artificial Intelligence Sun Yat-Sen University Zhuhai China Department of Electronic and Computer Engineering Hong Kong University of Science and Technology Hong Kong State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and Control Zhejiang University Hangzhou China Huzhou Institute Zhejiang University Huzhou China

The robotics community is increasingly interested in autonomous aerial transportation. Unmanned aerial vehicles with suspended payloads have advantages over other systems, including mechanical simplicity and agility, but pose great challenges in planning and control. To realize fully autonomous aerial transportation, this paper presents a systematic solution to address these difficulties. First, we present a real-time planning method that generates smooth trajectories considering the time-varying shape and non-linear dynamics of the system, ensuring whole-body safety and dynamic feasibility. Additionally, an adaptive NMPC with a hierarchical disturbance compensation strategy is designed to overcome unknown external perturbations and inaccurate model parameters. Extensive experiments show that our method is capable of generating high-quality trajectories online, even in highly constrained environments, and tracking aggressive flight trajectories accurately, even under significant uncertainty. We plan to release our code to benefit the community. © 2023, CC BY-NC-ND.

关键词： Trajectories

来源：评论

学校读者我要写书评

暂无评论

PredRecon: A Prediction-boosted Planning Framework for Fast and High-quality Autonomous Aerial Reconstruction

arXiv

引用

arXiv 2023年

作者： Feng, Chen Li, Haojia Gao, Fei Zhou, Boyu Shen, Shaojie School of Artificial Intelligence Sun Yat-Sen University Zhuhai China Department of Electronic and Computer Engineering The Hong Kong University of Science and Technology Hong Kong State Key Laboratory of Industrail Control Technology Institute of Cyber-Systems and Control Zhejiang University Hangzhou China Huzhou Institute Zhejiang University Huzhou China

Autonomous UAV path planning for 3D reconstruction has been actively studied in various applications for high-quality 3D models. However, most existing works have adopted explore-then-exploit, prior-based or exploration-based strategies, demonstrating inefficiency with repeated flight and low autonomy. In this paper, we propose PredRecon, a prediction-boosted planning framework that can autonomously generate paths for high 3D reconstruction quality. We obtain inspiration from humans can roughly infer the complete construction structure from partial observation. Hence, we devise a surface prediction module (SPM) to predict the coarse complete surfaces of the target from the current partial reconstruction. Then, the uncovered surfaces are produced by online volumetric mapping waiting for observation by UAV. Lastly, a hierarchical planner plans motions for 3D reconstruction, which sequentially finds efficient global coverage paths, plans local paths for maximizing the performance of Multi-View Stereo (MVS), and generates smooth trajectories for image-pose pairs acquisition. We conduct benchmarks in the realistic simulator, which validates the performance of PredRecon compared with the classical and state-of-the-art methods. The open-source code is released at https://***/HKUST-Aerial-robotics/PredRecon. Copyright © 2023, 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

PredRecon: A Prediction-boosted Planning Framework for Fast and High-quality Autonomous Aerial Reconstruction

PredRecon: A Prediction-boosted Planning Framework for Fast ...

引用

IEEE International Conference on robotics and Automation (ICRA)

作者： Chen Feng Haojia Li Fei Gao Boyu Zhou Shaojie Shen Department of Electronic and Computer Engineering The Hong Kong University of Science and Technology Hong Kong China State Key Laboratory of Industrail Control Technology Institute of Cyber-Systems and Control Zhejiang University Hangzhou China Huzhou Institute Zhejiang University Huzhou China School of Artificial Intelligence Sun Yat-Sen University Zhuhai China

关键词：

来源：评论

学校读者我要写书评

暂无评论

An Efficient Trajectory Planner for Car-like Robots on Uneven Terrain

arXiv

引用

arXiv 2023年

作者： Xu, Long Chai, Kaixin Han, Zhichao Liu, Hong Xu, Chao Cao, Yanjun Gao, Fei State Key Laboratory of Industrial Control Technology Zhejiang University Hangzhou310027 China Huzhou Institute of Zhejiang University Huzhou313000 China Institute of Artificial Intelligence and Robotics Xi'an Jiaotong University Shaanxi Xi'An710049 China School of information and electrical engineering Hangzhou City University Hangzhou310015 China

Autonomous navigation of ground robots on uneven terrain is being considered in more and more tasks. However, uneven terrain will bring two problems to motion planning: how to assess the traversability of the terrain and how to cope with the dynamics model of the robot associated with the terrain. The trajectories generated by existing methods are often too conservative or cannot be tracked well by the controller since the second problem is not well solved. In this paper, we propose terrain pose mapping to describe the impact of terrain on the robot. With this mapping, we can obtain the SE(3) state of the robot on uneven terrain for a given state in SE(2). Then, based on it, we present a trajectory optimization framework for car-like robots on uneven terrain that can consider both of the above problems. The trajectories generated by our method conform to the dynamics model of the system without being overly conservative and yet able to be tracked well by the controller. We perform simulations and real-world experiments to validate the efficiency and trajectory quality of our algorithm. Copyright © 2023, The Authors. All rights reserved.

关键词： Trajectories

来源：评论

学校读者我要写书评

暂无评论

A Detection Method for Densely Distributed Coal and Gangue with Uneven Particle Based on Deeplabv3+

SSRN

引用

SSRN 2024年

作者： Wang, Xi Guo, Yongcun Hu, Kun Jia, Xiaofen Gang, Cheng School of Mechanical Engineering Anhui University of Science and Technology Huainan232001 China State Key Laboratory of Mining Response and Disaster Prevention and Control in Deep Coal Mines Anhui University of Science and Technology Huainan232001 China School of Artificial Intelligence Anhui University of Science and Technology Huainan232001 China School of New Energy and Intelligent networked Automobile Anhui University of Science and Technology Hefei230000 China

A detection network for densely distributed coal and gangue with uneven particle size is proposed based on DeepLabV3+. Firstly, group convolution and 1×1 convolution are used in the encoder to reduce the model parameters, and deformable convolution is introduced to enhance the feature extraction capability for irregularly shaped targets. Then, two shallow feature maps and CA are introduced into the decoder, to enhance the network's focus on the edge detailed information of the adhesion target and the small target location information. Finally, relying on the self-collected multi-condition coal and gangue dataset, the method's effectiveness is demonstrated through comparative validation and test experiments, with an average F1-score of 0.983 and a detection speed of 32.5 FPS. The technique can be adapted to the poor working environment in coal mine production, and realizes the low-cost and high-efficiency identification and localization of coal and gangue. © 2024, The Authors. All rights reserved.

关键词： Coal

来源：评论

学校读者我要写书评

暂无评论

Composite Robust controller Design for Robotic Arm Trajectory Tracking under Parametric Uncertainties

Composite Robust Controller Design for Robotic Arm Trajector...

引用

IEEE International Conference on robotics and Biomimetics

作者： Umair Javaid Michael Basin Muhammad Niaz Khan Robotic Institute Ningbo University of Technology Zhejiang China School of Robotics Ningbo University of Technology Zhejiang China School of Physical and Mathematical Sciences Autonomous University of Nuevo Leon San Nicolas de los Garza Mexico State Key Laboratory of Tribology Institute of Manufacturing Engineering Lab of Precision/Ultra-Precision Manufacturing Equipments and Control Tsinghua University Beijing China

ISBN: (数字)9798331509644

ISBN: (纸本)9798331509651

Robotic arms are critical for industrial automation. However, it requires a fast and accurate trajectory-tracking response despite the presence of system parametric uncertainties and time-dependent external disturbances. This paper addresses the robotic arm trajectory-tracking problem using a second- order sliding mode observer (SOSMO)-based integral sliding mode control (ISMC) scheme. Initially, we propose a SOSMO design to estimate total system perturbations. The observer estimation errors converge to a small tunable region around zero in finite time. Later, exploiting the SOSMO estimates, a robust ISMC is designed to improve the trajectory tracing performance of the system. We employ the Lyapunove stability theory to prove the convergence of observer estimation and closed-loop system state error to zero in finite time. Finally, comparative numerical simulation results validate the effectiveness and robust performance of the proposed composite control algorithm.

关键词： Uncertainty Trajectory tracking Service robots Perturbation methods Observers Manipulators Stability analysis Trajectory Closed loop systems Convergence

来源：评论

学校读者我要写书评

暂无评论

What will robots be like in the future?

引用

National Science Review 2019年第5期6卷 1059-1061页

作者： Yanfeng Lu Weijie Zhao the State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences NSR

Robots are changing our lives:sweeping robots patrol our living rooms; interactive robots accompany our children; industrial robots assemble vehicles; rescue robots search and save lives in catastrophes; medical robots perform surgeries in *** better understand robots’challenges and impact, National Science Review (NSR) interviewed Professor Toshio Fukuda, who is one of the world’s most representative robotics experts and has developed a number of bionic robots and micro/nano-robots.

关键词： NSR China What will robots be like in the future

来源：评论

学校读者我要写书评

暂无评论

Fully Robotized 3D Ultrasound Image Acquisition for Artery

Fully Robotized 3D Ultrasound Image Acquisition for Artery

引用

IEEE International Conference on robotics and Automation (ICRA)

作者： Mingcong Chen Yuanrui Huang Jian Chen Tongxi Zhou Jiuan Chen Hongbin Liu State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Centre for Artificial Intelligence and Robotics Hong Kong Institute of Science and Innovation Chinese Academy of Sciences Hong Kong School of Artificial Intelligence University of Chinese Academy of Sciences Beijing China School of Biomedical Engineering and Imaging Sciences King's College London London UK

Current imaging of the artery relies primarily on computed tomography angiography (CTA), which requires contrast injections and exposure to radiation. In this paper, we present a method for fully autonomous artery 3D image acquisition using a linear ultrasound (US) probe and a 6 DoFs robot arm with a 3D camera. Robotic vessel acquisition can minimize tissue deformation and permit the reproduction of scans. Additionally, the robotic-based acquisition can provide more precise vessel position data that can be utilized for 3D reconstruction as a preoperative image. The first scanning point is determined by the 3D camera using a neural network for leg area estimation. A visual servo algorithm adjusts the in-plane motions using a cross-sectional vessel segmentation produced by a neural network with a UNet structure, while a US confidence map regulates the in-plane rotation. The robot is equipped with impedance control to maintain a constant and safe scan. Experiments on a leg phantom and a volunteer indicate that the robot can follow the vessel and modify its position to provide a sharper US image. The average error of phantom scanning in y-axis and z-axis are 0.2536mm and 0.2928mm, respectively, while the root means square error (RMSE) of contact force in the volunteer experiment is 0.2664N. In addition, a 3D vessel reconstruction demonstrates the possibility of robotic US acquisition as a preoperative image.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Enhanced Decentralized Autonomous Aerial Robot Teams with Group Planning

arXiv

引用

arXiv 2022年

作者： Hou, Jialiang Zhou, Xin Gan, Zhongxue Gao, Fei Academy for Engineering and Technology Fudan University Shanghai200433 China State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and Control Zhejiang University Hangzhou310027 China Huzhou Institute of Zhejiang University Huzhou313000 China

Designing autonomous aerial robot team systems remains a grand challenge in robotics. Existing works in this field can be categorized as centralized and decentralized. Centralized methods suffer from scale dilemmas, while decentralized ones often lead to poor planning quality. In this paper, we propose an enhanced decentralized autonomous aerial robot team system with group planning. According to the spatial distribution of agents, the system dynamically divides the team into several groups and isolated agents. For conflicts within each group, we propose a novel coordination mechanism named group planning. The group planning consists of efficient multi-agent pathfinding (MAPF) and trajectory joint optimization, which can significantly improve planning quality and success rate. We demonstrate through simulations and real-world experiments that our method not only has applicability for a large-scale team but also has top-level planning quality. © 2022, CC BY-NC-ND.

关键词： Motion planning

来源：评论

学校读者我要写书评

暂无评论

Optimization of Simulation Parameters of Input Shaper Based on Genetic Algorithm

Optimization of Simulation Parameters of Input Shaper Based ...

引用

Advanced Technologies in Intelligent control, Environment, Computing & Communication Engineering (ICATIECE), International Conference on

作者： Tao Yi Quanshen Pei Deying Li Shugong Wei Danping Jia Hualiang Zhang Hunan University of Information Changsha China School of Information Science and Engineering Shenyang University of Technology Shenyang China College of Physics and Electronic Engineering Guangxi Normal University for Nationalities Chongzuo China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang Institute of Automation Chinese Academy of Sciences Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China

ISBN: (纸本)9781665493970

In the motion control system, input shaper is often used to suppress the residual oscillation of high-precision positioning system, but the selection of input shaper parameters is difficult. In view of the difficulty of selecting input shaper parameters, this paper proposes to use genetic algorithm to select the parameters of input shaper. Firstly, the input shaper is designed in the light of the three-loop mathematical model of motor; Secondly, because the genetic algorithm directly optimizes the output of the motor and the algorithm can reduce the influence of the deviation of generator parameters on the parameter selection of the input shaper to a certain extent, the parameters of the input shaper are selected by the genetic algorithm to optimize the output of the motor; In the finish, a comparative experiment between a system with input shaper and a system with simple PID control is carried out. The results show that the optimized system can obtain higher robustness and smaller tracking deviation.

关键词： Vibrations Tracking Mathematical models Robustness Decoding Rigidity Motion control

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：