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arXiv 2023年

作者： Zhang, Feilong State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China

The design and structure of generalized predictive control (GPC) are not simple and intuitive. The performance analysis does not deeply analyze how the controller parameters affect the system characteristics and the relationship between the tracking error caused by the noise and the selected controller parameters. This paper proposes a generalized predictive control, and its design is simple and intuitive for unnecessary solving the Diophantine equation. Then the relationship between desired output, disturbance, and system output is analyzed by the characteristic equation and steady-state analysis. Based on this, the study presents research findings on the steady state of the system and verifies them through simulations. Furthermore, this paper introduces GPC with disturbance compensation and incremental generalized minimum variance control (IGMVC) with disturbance compensation. The conditions for the elimination of disturbance are presented in theory and simulation for the first time. © 2023, CC BY.

关键词： Controllers

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Research on High Reliability and Redundancy Design Method of Risk-driven Transformer Internal Inspection Robot

Research on High Reliability and Redundancy Design Method of...

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robotics, Artificial Intelligence and Intelligent Control (RAIIC), International Conference on

作者： Yabiao Wang Yuming Zhao Xianshuai Sun Zhen He Zhigang Li State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Chinese Academy of Sciences Institutes for Robotics and Intelligent Manufacturing Shenyang China Key Laboratory of Marine Robotics Shenyang China University of Chinese Academy of Sciences Beijing China

Aiming at the demand for intelligent operation and maintenance of large-scale oil-immersed power transformers with high reliability tasks, the research on risk-driven design methods for power transformer internal inspection robots was carried out. From the perspective of operation and maintenance safety, we reduce the risks of robot operation and put forward a risk-driven robot system-wide high reliability and redundancy design method, which includes the robot structure design, control strategy, backup design and other dimensions. The research results of the article provide reliable theoretical support for the safe, reliable and intelligent operation and maintenance of power transformers, in the areas of robot space vector arrangement propulsion, omni-directional environment sensing vision, high reliability robot control strategy, and redundancy and hot backup system design. The research results of the article provide reliable theoretical support for safe and reliable intelligent operation and maintenance of power transformers.

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Flapping-Wing Robot Achieves Multi-Domain Locomotion Using Transformable Wheel Mechanism

Flapping-Wing Robot Achieves Multi-Domain Locomotion Using T...

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IEEE International Conference on robotics and Biomimetics

作者： Xiangxiao Chai Shihua Wang Erzhen Pan Wenfu Xu School of Mechanical Engineering and Automation Harbin Institute of Technology (Shenzhen) Shenzhen China Key University Laboratory of Mechanism & Machine Theory and Intelligent Unmanned Systems of Guangdong Shenzhen China State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin China

ISBN: (数字)9798331509644

ISBN: (纸本)9798331509651

The difficulty of moving from aquatic to aerial environment is one of the major challenges limiting the development of trans-medium multi-domain locomotion vehicles. In this paper, the concept of the transformable wheel, a feature commonly found in autonomous land vehicles (AL V s), is introduced into the design. Additionally, a flapping-wing robot equipped with multi-domain locomotion capability, which can not only realize aerial flight and surface navigation on water, but also ascend from water to land for subsequent takeoff is presented. The paper first introduces the system design of the robot and proposes the corresponding multi-domain locomotion strategy. Subsequently, the design of the transformable wheel mechanism is described in detail and the force analysis for the water-exit is conducted. The feasibility of the proposed strategy is experimentally validated, confirming the prototype's multi-domain locomotion performance finally. This research explores the feasibility of introducing the transformable wheel mechanism into trans-medium multi-domain vehicle platforms and provides a design example.

关键词： Legged locomotion Torque Limiting Navigation Propellers Roads Wheels Prototypes Motors system analysis and design

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Human joints estimation system of rescue robot with occlusion

Human joints estimation system of rescue robot with occlusio...

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2022 International Conference on Intelligent Dynamics and Control Technology, IDC 2022

作者： Fang, Zhenghui Wang, Anna Bu, Chunguang Sui, Jin Fan, Xiaoliang College of Information Science and Engineering Northeastern University Shenyang110819 China State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110169 China

The human body is often in a partially visible state during rescue at the disaster site. At the same time, when the human body is grasped, the camera located on the actuator at the end of the robotic arm cannot fully bring the human body into the field of view. The existing human pose estimation algorithms do not perform well in this situation, and a joint detection method that can estimate the complete human pose through partial human body information and can perform data refresh in real time is required. We use the occlusion part classification module to extract the weight vector, re-weight it and the joint features extracted from AlphaPose, and add human body geometric constraints when generating 3D human body joints to obtain more accurate 3D human body joint positions. Finally, the robot is successfully used to complete the human grasping experiment, which verifies the effectiveness of the algorithm. © Published under licence by IOP Publishing Ltd.

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Development of a power line Inspection Robot Capable of automatically crossing Obstacles 5

Development of a power line Inspection Robot Capable of auto...

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5th World Conference on Mechanical Engineering and Intelligent Manufacturing, WCMEIM 2022

作者： Yue, Xiang Liu, Yanhua Wang, Hongguang Feng, Yan State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China College of Engineering Shenyang Agricultural University Shenyang110866 China

ISBN: (纸本)9781665473699

According to the characteristics of the transmission line environment and the requirements of the inspection task, a robot mechanism for inspection based on the transformation of the transmission line is proposed. The configuration of the robot and the magnetic online charging device are analyzed. The obstacle surmounting process of typical obstacles is analyzed by using finite state machine. The motion sequence of the robot crossing obstacles is planned and the obstacle crossing test is carried out. The test results show that the mechanism can cross the drainage line, tension clamp and other complex obstacles, which verifies the rationality of the mechanism design and the feasibility of the motion planning. With the transformation of the transmission line environment, the robot can efficiently and quickly cross the typical obstacles. © 2022 IEEE.

关键词： Electric lines

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A Compliant Traction Method of Manipulator Based on Online Calibration of Force Sensor Zero-Point 6

A Compliant Traction Method of Manipulator Based on Online C...

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6th International Conference on Automation, Control and Robots, ICACR 2022

作者： Xu, Zhilu Wang, Weijun Feng, Wei Chinese Academy of Sciences Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institute of Advanced Technology Shenzhen China Shenzhen Institute of Advanced Technology Cas Key Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen China

ISBN: (数字)9781665498739

ISBN: (纸本)9781665498739

With the increasing number of cooperative robots, it is becoming increasingly important to improve the safety and operability of human-robot interaction. Installing a six-dimensional force sensor at the end of the manipulator can realize the drag of the manipulator in Cartesian space. A compliant traction method of manipulator based on online calibration of force sensor zero-point is proposed in this paper. Aiming at the problem of "zero drift"of force sensor, after calculating the gravity of the end tool, the zero-point of the force sensor is calibrated online by means of mean processing, so as to obtain more accurate external force. Then, the relationship between the end position of the manipulator and the external force, the end moving speed of the manipulator and the external force is established, and the change of the position and speed of the manipulator is controlled by the external force at the same time. Finally, experiments show the effectiveness of this method and ensure the safety and reliability in the traction process. © 2022 IEEE.

关键词： Manipulators

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Sagittal SLIP-anchored task space control for a monopode robot traversing irregular terrain

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Frontiers of Mechanical Engineering 2020年第2期15卷 193-208页

作者： Haitao YU Haibo GAO Liang DING Zongquan DENG State Key Laboratory of Robotics and Systems Harbin Institute of TechnologyHarbin 150001China

As a well-explored template that captures the essential dynamical behaviors of legged locomotion on sagittal plane,the spring-loaded inverted pendulum(SLIP)model has been extensively employed in both biomechanical study and robotics *** at fully leveraging the merits of the SLIP model to generate the adaptive trajectories of the center of mass(CoM)with maneuverability,this study presents a novel two-layered sagittal SLIP-anchored(SSA)task space control for a monopode robot to deal with terrain *** work begins with an analytical investigation of sagittal SLIP dynamics by deriving an approximate solution with satisfactory apex prediction accuracy,and a two-layered SSA task space controller is subsequently developed for the monopode *** higher layer employs an analytical approximate representation of the sagittal SLIP model to form a deadbeat controller,which generates an adaptive reference trajectory for the *** lower layer enforces the monopode robot to reproduce a generated CoM movement by using a task space controller to transfer the reference CoM commands into joint torques of the multi-degree of freedom monopode ***,an adaptive hopping behavior is exhibited by the robot when traversing irregular *** results have demonstrated the effectiveness of the proposed method.

关键词： legged robots spring-loaded inverted pendulum task space control apex return map deadbeat control irregular terrain negotiation

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A Three-Stage Low-Illumination Image Enhancement Method Based on Feature Refining and Its Application in Inspection Robot for High-Voltage Substation Room

A Three-Stage Low-Illumination Image Enhancement Method Base...

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International Conference on Advanced robotics and Mechatronics (ICARM)

作者： Bo Fu Hongguang Wang Yong Jiang Yifeng Song State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China

To address color deviation and noise problem in some Retinex theory based image enhancement methods, this paper proposes a three-stage low-illumination image enhancement method based on feature refining. Additionally, a vision subsystem for an electric inspection robot is introduced based on this network to mitigate the impact of low illumination environments on vision detection tasks in high-voltage substation rooms. In the first stage, the proposed network decomposes the image using Retinex theory and leverages the Swin Transformer to perceive global information. In the second stage, the image undergoes preliminary enhancement. In the third stage, the feature refining network is introduced. Initially, a U-shaped network is employed to extract image features. Subsequently, a convolutional neural network and attention mechanism are applied to screen the extracted information, completing the feature refinement and improving the quality of the result. Through illumination assessment and algorithm selection, the proposed vision subsystem for the robot effectively addresses the challenges of low illumination enhancement and object detection in complex lighting conditions in high-voltage transformer rooms. Experimental results demonstrate that the proposed network outperforms some state-of-the-art methods in terms of peak signal-to-noise ratio and structural similarity index. Moreover, the vision subsystem presented in this paper significantly enhances the robot's detection capabilities, reducing the omission ratio and fallout ratio, thus validating the effectiveness of the proposed method.

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Image Recovery and Object Detection Integrated Algorithms for Robots in Harsh Battlefield Environments 16th

Image Recovery and Object Detection Integrated Algorithms f...

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16th International Conference on Intelligent robotics and Applications, ICIRA 2023

作者： Wang, Xudong Chen, Xi’ai Wang, Feifan Xu, Chonglong Tang, Yandong State Key Laboratory of Robotics 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 School of Automation and Electrical Engineering Shenyang Ligong University Shenyang110159 China Limited Shenyang110170 China

ISBN: (纸本)9789819964918

Battlefield environments are harsher than normal environments, and the images captured by imaging equipment are more prone to degradation. Degraded images seriously affect the analysis of military intelligence and the deployment of intelligent weapons. To address this issue, we propose an image recovery algorithm, which recovers degraded battlefield images based on a physical imaging model and uses a light-weight network to estimate the parameters of physical model. In addition, we propose a strategy to joint training of the image recovery module and the object detection module. Specifically, we integrate the recovery module to the front of YOLO detector to jointly optimize the two modules with detection loss. The image recovery module is light-weight without significant adverse impact on the real-time running of object detection, which can be easily deployed to intelligent unmanned devices such as battlefield robots. The experimental results show that the proposed algorithm achieves better recovery performance in battlefield environments, and the joint training strategy effectively improve the accuracy of object detection. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2023.

关键词： Object detection

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Learning effective pruning at initialization from iterative pruning

arXiv

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arXiv 2024年

作者： Liu, Shengkai Cheng, Yaofeng Zha, Fusheng Guo, Wei Sun, Lining Bing, Zhenshan Yang, Chenguang State Key Laboratory of Robotics and Systems Harbin Institute of Technology China Technical University of Munich Germany University of Liverpool United Kingdom

Pruning at initialization (PaI) reduces training costs by removing weights before training, which becomes increasingly crucial with the growing network size. However, current PaI methods still have a large accuracy gap with iterative pruning, especially at high sparsity levels. This raises an intriguing question: can we get inspiration from iterative pruning to improve the PaI performance? In the lottery ticket hypothesis, the iterative rewind pruning (IRP) finds subnetworks retroactively by rewinding the parameter to the original initialization in every pruning iteration, which means all the subnetworks are based on the initial state. Here, we hypothesise the surviving subnetworks are more important and bridge the initial feature and their surviving score as the PaI criterion. We employ an end-to-end neural network (AutoSparse) to learn this correlation, input the model’s initial features, output their score and then prune the lowest score parameters before training. To validate the accuracy and generalization of our method, we performed PaI across various models. Results show that our approach outperforms existing methods in high-sparsity settings. Notably, as the underlying logic of model pruning is consistent in different models, only one-time IRP on one model is needed (e.g., once IRP on ResNet-18/CIFAR-10, AutoS can be generalized to VGG-16/CIFAR-10, ResNet-18/TinyImageNet, et al.). As the first neural network-based PaI method, we conduct extensive experiments to validate the factors influencing this approach. These results reveal the learning tendencies of neural networks and provide new insights into our understanding and research of PaI from a practical perspective. Our code is available at: https://***/ChengYaofeng/***. © 2024, CC BY.

关键词： HTTP

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