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检索条件"任意字段=5th International Conference on Robotics and Automation Systems, Robotics 2010"

共 1356 条记录，以下是211-220 订阅

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Consensus-Based Multi-UAV Partition Rendezvous in Formation

Consensus-Based Multi-UAV Partition Rendezvous in Formation

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robotics, Intelligent Control and Artificial Intelligence (RICAI), international conference on

作者： ZhaoJun Wu Yongfu Li Hang Zhao Key Laboratory of Intelligent Air Ground Cooperative Control for Universities in Chongqing College of Automation Chongqing University of Posts and Telecommunications Chongqing China

A multi-UAV zonal assembly control algorithm based on consistency theory is proposed to safely and quickly assemble UAV swarms into a specified formation within a certain range area. the near-staging area is divided into several partitions, and UAVs in different zones are queued to travel in a straight line toward the assigned target staging point. through the implementation of formation assembly within sub-areas, this paper successfully resolves the trade-off between the assembly time and the control expenditure. Considering the position difference, collision factors and yaw angle between adjacent drones, the position controller and yaw controller are designed respectively. the stability of the proposed formation controller is verified using Lyapunov theory. Finally, numerical simulation verifies the effectiveness of the controller.

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Heterogeneous Multi-UAV Mission Planning Considering Obstacle Avoidance and UAV Motion Model

Heterogeneous Multi-UAV Mission Planning Considering Obstacl...

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robotics and Computer Vision (ICRCV), international conference on

作者： Shu Shang Guoqing Qi Andong Sheng Yinya Li School of Automation Nanjing University of Science and Technology Nanjing China

Distributed task assignment algorithm is the key algorithm to solve multi-agent task assignment problem. In this paper, heterogeneous UAVs cooperative search and combat task is taken as the background. First, a multi-UAV task assignment model is established by comprehensively considering the constraints of UAV load resources, task time window and task type. Aiming at the obstacle threat in the task scenario, the UAV motion model is considered to improve the mobility and obstacle avoidance ability of the UAV in the assignment model. Second, UAV maneuver trajectory and path in the Consensus-Based Bundle Algorithm (CBBA) are improved by integrating dynamic window algorithm (DWA). Finally, the proposed algorithm is verfied which can improve the ability of multi-UAV task assignment in complex environment through numerical simulation.

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Energy management strategies for hybrid ships and Unmanned Underwater Vehicles 5

Energy management strategies for hybrid ships and Unmanned U...

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2022 5th international conference on Power Electronics and Control Engineering, ICPECE 2022

作者： Zhang, Mengyao Gu, Haitao Guo, Jianhua School of Chemical Process Automation Shenyang University of Technology China State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences China

Both ships and unmanned underwater vehicles (UUVs) have played a great role in the human exploration of the ocean and the investigation of marine resources. their endurance of them is limited by the onboard energy storage, and the benefits of hybrid ships and UUVs in terms of energy conservation and emission reduction technologies are increasingly clear. the secret to attaining energy conservation while maintaining power performance is energy management. the management of energy for hybrid ships and UUVs are summarized in this work. First, this article includes the state of the art in energy management techniques for autonomous maritime vehicles and hybrid ships. and summarizes the hybrid energy management objectives for different purposes. Second, it analyses the latest progress of hybrid energy management strategies at the present stage and compares the benefits and drawbacks of existing energy management strategies in a comprehensive and in-depth manner. Finally, the paper summarizes their shortcomings and provides an outlook on the future development of hybrid energy management strategies. © Published under licence by IOP Publishing Ltd.

关键词： Energy management

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Overview of selected teleoperation positioning systems for controlling a robot arm operating in Remote Centre of Motion (RCM) mode

Overview of selected teleoperation positioning systems for c...

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international conference on Methods and Models in automation and robotics (MMAR)

作者： Roman Trochimczuk Adam Wolniakowski Zhuoqi Cheng Sławomir Romaniuk Radosław Tomaszewski Faculty of Electrical Engineering Białystok University of Technology Białystok Poland Mærsk Mc-Kinney Møller Instituttet University of Southern Denmark Odense Denmark Doctoral school of Bialystok Univesity of Technology Białystok University of Technology Białystok Poland

ISBN: (数字)9798350362343

ISBN: (纸本)9798350362350

this paper describes partial results of ongoing research at the Department of Automatic Control and robotics Faculty of Electrical Engineering, Bialystok University of Technology, Poland, in the field of application of industrial robots for the improvement of robotic surgical procedures by the doctors, analogous to procedures performed on expensive surgical systems class of the Da Vinci system from the Intuitive Surgical Company. Selected issues related to force feedback teleoperation are discussed. the problem of positioning the surgical instrument (the tool of a surgical robot) in remote centre of motion mode was defined. Developed applications controlling the UR5 industrial cobot from company Universal Robots in teleoperation mode were discussed: definition of application problems on the industrial cobot platform, used and custom-built subsystems for positioning and learning by demonstration.

关键词： Training Medical robotics Service robots Surgery Companies Collaborative robots Planning

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An improved deep-learning monocular visual SLAM method based on local features 5

An improved deep-learning monocular visual SLAM method based...

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5th international conference on Computer Information Science and Artificial Intelligence, CISAI 2022

作者： Yu, Rui Long, Chenhai Ma, Guoliang Guo, Jian Xu, Lisong Guo, Zhaoli School of Energy and Power Engineering Nanjing University of Science and Technology Nanjing210094 China State Grid Hunan Electric Power Company Limited Research Institute Hunan410004 China School of Automation Nanjing University of Science and Technology Nanjing210094 China

ISBN: (纸本)9781510662520

To improve the tracking performance of the Simultaneous Localization and Mapping (SLAM) system, this paper presents a monocular visual SLAM method based on deep learning second order similarity of local features. the local features are generated into descriptors from patches around key points in a frame using a deep neural network. It is applied to tracking, relocalization, and loop closure module to enhance data association. We also train a visual bag of words model to adapt to the local descriptors. Additionally, we use two adaptive strategies to improve the proposed method, one strategy refines key points detection with illumination intensity, and the other strategy reduces the possibility of tracking lost based on the ratio of outliers’ number in feature matching. We evaluate our method on two public datasets. the experimental results demonstrate the effectiveness of the system and also show that the adaptive strategies can increase tracking performance and improve the robustness in challenging conditions. © 2023 SPIE.

关键词： robotics

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Autonomous Conscious Humanoid Robot System

Autonomous Conscious Humanoid Robot System

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robotics, Intelligent Control and Artificial Intelligence (RICAI), international conference on

作者： Zhijun Zhang Haomin Yu Wentong Wang Yamei Luo School of Automation Science and Engineering South China University of Technology Guangzhou China School of Automation Science and Engineering School of Design South China University of Technology Guangzhou China

In order to enable intelligent robots to have autonomous consciousness and make decisions autonomously, and generate behaviors safely and ethically, an autonomous conscious humanoid robot (ACHR) architecture is proposed and designed in this paper. the ACHR is mainly composed of mental system, environment perception system and behavior generation system. When the robot is stimulated externally in an environmental interaction, or generates an internal motivation due to an internal need, the stimulation is analyzed and goals of the robot are generated. then goals are decomposed and logically sorted through the mental system, and sent into the behavioral decision-making system. Finally, behavior decision that meet moral ethics and safety principle is transferred to the behavior generation module so that the robot can generate behaviors. Compared with existing humanoid robots, the ACHR proposed in this paper combines large-scale models with generative intelligence technology and it is more autonomous. the framework of autonomous conscious humanoid robot proposed in this paper can promote the development of conscious robot in the future and provide a new idea for the development of intelligent robots.

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A Raspberry Pi Driven Autonomous Humanoid Robot for Advanced Applications

A Raspberry Pi Driven Autonomous Humanoid Robot for Advanced...

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international conference on Control, Mechatronics and automation (ICCMA)

作者： A S M Ahsanul Sarkar Akib Md Amit Hasan Md. Montasir Rahman Md Washim Akram Md Abdullah Al Ahasan Md Ahsan Habib Dept. of Robotics Robo Tech Valley Dhaka Bangladesh Dept. of IT Washington University of Science and Technology Alexandria VA United States Dept. of CSE Green University of Bangladesh Narayanganj Bangladesh Dept. of CS University of Regina Regina Canada Dept. of CSE Green University of Bangladesh Dhaka Bangladesh

ISBN: (数字)9798331517519

ISBN: (纸本)9798331517526

As the human race entered the 5th Industrial Revolution era, the collaboration between humans and advanced technologies flourished at a speed that no one ever imagined before. the collaboration between human and machine intelligence contributed significantly to enhancing manufacturing, healthcare, retail, education, agriculture, and many other fields. the 5th Industrial Revolution introduces us to advanced technologies like Artificial Intelligence, robotics, and the Internet of things. In robotics, extensive work is ongoing to ensure effective collaboration between humans and robots. the type of robots that are used to ensure this collaboration is known as Humanoid Robots which interact, work, and behave like humans. Around the world, various types of Humanoid Robots are made and researchers are working consistently to improve their performance to be able to establish these robots as trustworthy companions of human beings. In this paper, we have discussed a Humanoid Robot that we have built named Elina can effectively communicate with humans, grab and drop things with its hands, answer questions, and also move its arm according to specific commands given. the purpose of building this robot is to gain deep insight into Humanoid Robots and conduct research to analyze its performance in multiple scenarios. We have observed a significant performance of the Humanoid Robot Elina after experimentation.

关键词： Accuracy Service robots Humanoid robots Collaboration Speech enhancement Hardware Software Text to speech Robots Speech to text

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SlowFast GCN Network for Quantification of Parkinsonian Gait Using 2D Videos 12

SlowFast GCN Network for Quantification of Parkinsonian Gait...

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12th international conference on CYBER Technology in automation, Control, and Intelligent systems, CYBER 2022

作者： Zeng, Qingyi Liu, Peipei Bai, Ying Yu, Huan Sun, Xiaoyi Han, Jianda Wu, Jialing Yu, Ningbo College of Artificial Intelligence Nankai University Haihe Education Park Tianjin300350 China Tianjin Key Laboratory of Intelligent Robotics Nankai University Haihe Education Park Tianjin300350 China Department of Neurology Tianjin Huanhu Hospital Tianjin300350 China State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China Institute of Intelligence Technology and Robotics Systems Shenzhen Research Institute of Nankai University Shenzhen518083 China

ISBN: (数字)9781665472678

ISBN: (纸本)9781665472678

Parkinson's disease(PD) is a progressive neu-rodegenerative disease defined by clinical syndrome including bradykinesia, tremor and postural instability. the PD-related disability and impairment are usually monitored by clinicals using the MDS-UPDRS scale. However, due to COVID-19, it became much harder for the patients to reach hospitals and obtain necessary assessment and treatment. Nowadays, 2D videos are easily accessible and can be a promising so-lution for on-site and remote diagnosis of movement disorder. Inspired by the frequency-based video processing mechanism of human visual system, we propose a video-based SlowFast GCN network to quantify the gait disorder. the model consists of two parts: the fast pathway and the slow pathway. the former detects characteristics such as tremor and bilateral asymmetry, while the latter extracts characteristics such as bradykinesia and freezing of gait. Furthermore, in order to investigate the influence of age on the model performance, an aged control group and a young control group were set up for verification. the proposed model was evaluated on a video dataset collected from 68 participants. We achieved a balanced accuracy of 87.5% and precision of 87.9%, which outperformed existing competing methods. When replacing the young healthy controls with the same number of older controls, the balanced accuracy and precision were decreased by 10.4% and 9.7%, which indicates that age has a significant effect on the model perfomance. © 2022 IEEE.

关键词： COVID-19

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A fault detection method for AUV based on multi-scale spatiotemporal feature fusion 5

A fault detection method for AUV based on multi-scale spatio...

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5th international conference on Computer Information Science and Artificial Intelligence, CISAI 2022

作者： Xia, Shaoxuan Zhou, Xiaofeng Shi, Haibo Li, Shuai Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang110016 China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110169 China University of Chinese Academy of Sciences Beijing100049 China

ISBN: (纸本)9781510662520

Autonomous underwater vehicles (AUVs) are important equipment for ocean development and exploration. To ensure the task implementation of AUV, faults shall be detected in time. We propose a fault detection method based on multi-scale spatiotemporal feature fusion (MSF) for the time-varying characteristics and multiple correlation characteristics of AUV monitoring data. First, we apply a variety of sampling and data processing methods to generate monitoring windows with different scales along the time axis. then, a composite feature extraction method is proposed to obtain temporal and spatial features simultaneously, and a feature pyramid of temporal and spatial information is formed. We use bidirectional long short-term memory (BiLSTM) to obtain the time-series characteristics of a single monitoring variable, and convolutional neural networks (CNN) to obtain the implicit spatial relationship characteristics among multiple monitoring variables. Next, we use an adaptive feature fusion method to solve the inconsistency in different feature scales, which can adaptively suppress the possible conflict information of different scale features. Finally, we use a fully connected network to detect the fault of the fused features. the fault detection experiment of Haizhe AUV shows the effectiveness and superiority of the proposed method. © 2023 SPIE.

关键词： Autonomous underwater vehicles

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Improved YOLOv5-based Method for Recognition of Insulator String Pins 12

Improved YOLOv5-based Method for Recognition of Insulator St...

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12th international conference on CYBER Technology in automation, Control, and Intelligent systems, CYBER 2022

作者： Du, Jingbo Jiang, Yong Shenyang Ligong University Shenyang110158 China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110169 China

ISBN: (数字)9781665472678

ISBN: (纸本)9781665472678

Aiming at the problem that the substation insulator replacement robot cannot accurately identify insulator pins in the complex outdoor light environment, an improved YOLOv5-based insulator pin identification method YOLOv5-CBP is proposed. For the substation insulator pin recognition task, the backbone of the network is replaced by the lightweight EfficientNet-lite0;the Neck of the network is optimized and a more efficient feature fusion module BiFPN combined with an attention mechanism is introduced. the bounding box regression loss function was changed to improve the accuracy of inspection frame detection. Finally, the improved algorithm is compared with the original YOLOv5 algorithm on a self-built dataset for experiments. the results show that the insulator pin recognition accuracy is improved by 8.3%, the size of the algorithm model is reduced to 54% of the original, and the number of parameters is reduced by 49.4%. the improved algorithm model more lightweight. © 2022 IEEE.

关键词： Degradation Substations Inspection Insulators Control systems Pins Neck

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