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

作者： Huan, Liu Sen, Lin Zhi, Han School of Automation and Electrical Engineering Shenyang Ligong University Shenyang110159 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 Shenyang110016 China

ISBN: (纸本)9789819964918

Object detection model DETR (Detection Transformer) based on the Transformer architecture has demonstrated outstanding performance in various benchmark tests. However, these models often have a large number of parameters, which can make them slow and computationally intensive. Therefore, it is crucial to optimize the performance of these models by identifying any redundancy in the recognition model. This paper analyzes the internal mechanism of DETR detection and reveals that the backbone network and the transformer decoder already serve the intended purpose of the encoder module. The analysis results are validate through experimental design. It is find that the encoder module does not fulfill its initial intended role in the network but instead increases the parameter count and computational complexity of the entire network. For example, the performance of a single-layer encoder is equivalent to that of six layers. When using a Transformer backbone network, the encoder does not provide performance improvement to the overall architecture. Therefore, it is possible to optimize DETR-like architectures by using suitable module components without employing the encoder structure. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2023.

关键词： Redundancy

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Heat transfer simulation of optogenetics-LED based on microchannel heat dissipation

Heat transfer simulation of optogenetics-LED based on microc...

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2024 International Conference on Optoelectronic Information and Computer Engineering, OICE 2024

作者： Liu, Lusheng Le, Song Zhang, Yuan Zhang, Jing Wang, Aiping Bin, Jianxiong Niu, Lan Zhang, Lihua Kang, Xiaoyang Laboratory for Neural Interface and Brain Computer Interface Engineering Research Center of AI & Robotics Ministry of Education Shanghai Engineering Research Center of AI & Robotics MOE Frontiers Center for Brain Science State Key Laboratory of Medical Neurobiology Institute of AI and Robotics Academy for Engineering & Technology Fudan University Shanghai200433 China Ji Hua Laboratory Guangdong Province Foshan528200 China Yiwu Research Institute of Fudan University Zhejiang Yiwu City322000 China Research Center for Intelligent Sensing Zhejiang Lab Hangzhou311121 China

ISBN: (纸本)9781510682504

Optogenetics technology has greatly promoted the development of neuroscience. Flexible gene manipulation tools and sensitive light activation methods have provided convenience for neural function research. However, the thermal effect generated in the process of light stimulation affects the activation of neurons by optogenetic technology, which makes the results of light-activated light-sensitive proteins to generate neural currents inaccurate. Here, we established an in vivo activation model of LED-based optogenetic technology through simulation and analyzed the thermal effect produced by it. We propose to use microchannels to dissipate heat from implanted devices, reducing the thermal effect of light stimulation for neural activation. Through simulation, we propose the use of the vortex-like and cobweb-like microchannels for heat dissipation, which can control the temperature rise within 0.28K and 0.31K, respectively. © 2024 SPIE.

关键词： Heat losses

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A Real-time Local Planner Design for Smart Wheelchairs Based on Koopman Bilinear Model Predictive Control

A Real-time Local Planner Design for Smart Wheelchairs Based...

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2024 IEEE International Conference on Real-Time Computing and robotics, RCAR 2024

作者： Yu, Guanfeng Zhang, Han Wang, Zehao Wang, Jingchuan Shanghai Jiao Tong University Institute of Medical Robotics Department of Automation China Ministry of Education of China Key Laboratory of System Control and Information Processing China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai200240 China

ISBN: (纸本)9798350372601

The paper introduces a Koopman bilinear model predictive control (KBMPC) as a local planner for smart wheelchair systems. This approach leverages the Koopman Operator to streamline the nonlinear terms in MPC, aiming to achieve superior real-time performance. In particular, we employ the Extended Dynamic Mode Decomposition (EDMD) method to approximate the infinite dimensional Koopman operator. To tackle the challenge of designing lifting functions, we systematically utilize the derivatives of known nonlinear structures to methodically derive lifting functions. This systematic approach facilitates the identification of a precise bilinear model. Next, we formulate the corresponding Koopman bilinear MPC problem. Finally, an iterative algorithm is employed to efficiently solve the KBMPC problem. This method linearizes the bilinear model around estimations and iteratively solves the resulting quadratic programming problem to refine estimations. This allows KBMPC to function as a real-time local planner for smart wheelchairs. The prediction of nonlinear terms shows that the identified Koopman bilinear model increases the prediction accuracy. Furthermore, experiments demonstrate the advantages of the designed KBMPC local planner, highlighting its superior real-time performance and predictive capabilities. © 2024 IEEE.

关键词： Iterative methods

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Fruit Image Recognition Based on YOLOv5 3

Fruit Image Recognition Based on YOLOv5

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3rd International Conference on Machine Learning and Computer Application, ICMLCA 2022

作者： Qin, Lijuan Zhu, Yubin School of Information Science and Engineering Shenyang Ligong University Shenyang China State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Science Shenyang China

ISBN: (纸本)9781510664814

The fruit picking robot based on YOLOv5 has great development and application prospect in many fields in today's society, among which the target recognition accuracy of fruit image is the key. In view of the low recognition accuracy of small target fruit, this paper improves the data enhancement in the data pre-processing stage based on the YOLOv5 algorithm. The improved image recognition rate is 0.064s and mAP@0.5 is 0.91530. The optimized algorithm has high accuracy and certain practicability, which lays a foundation for automatic picking and other services in the future. © 2023 SPIE.

关键词： Fruits

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Research on 3D Semantic Map Based on SLAM and YOLOv4 3

Research on 3D Semantic Map Based on SLAM and YOLOv4

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3rd International Conference on Machine Learning and Computer Application, ICMLCA 2022

作者： Qin, Lijuan Ma, Zeqi School of Information Science and Engineering Shenyang Ligong University Shenyang China State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Science Shenyang China

ISBN: (纸本)9781510664814

To enable mobile robots to perform different tasks intelligently and autonomously in different work scenarios, we usually use SLAM to achieve simultaneous localization and map building of the robot mainly using to complete the functions. Localization and mapping are done only by detecting and matching feature points in the image, which only utilizes the geometric information in the environment and cannot obtain the linguistic information in the environment, resulting in the robot not being able to perceive the surrounding environment well. Location and mapping can only be done by detecting and matching the feature points in the image. Only the geometric information in the environment is used, and the linguistic information in the environment cannot be obtained, which makes the robot unable to perceive the environment well. In this paper, a three-dimensional semantic map is implemented based on the system design. The data uses RGBD image sequence, and the target detection algorithm YOLOv4 is applied to ORB-SLAM2 system to extract the semantic information in the environment. A three-dimensional dense point cloud map constructed by ORB-SALM2 system is segmented using an improved LCCP algorithm. Semantic information in the environment is projected to the three-dimensional point cloud according to the globally consistent camera posture, and a three-dimensional dense point cloud map with semantic information is constructed. © 2023 SPIE.

关键词： Robots

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A Survey of Underwater Multi-Robot systems

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IEEE/CAA Journal of Automatica Sinica 2022年第1期9卷 1-18页

作者： Ziye Zhou Jincun Liu Junzhi Yu State Key Laboratory for Turbulence and Complex System Department of Advanced Manufacturing and RoboticsBeijing Innovation Center for Engineering Science and Advanced TechnologyCollege of EngineeringPeking UniversityBeijing 100871China College of Information and Electrical Engineering China Agricultural UniversityBeijing 100083China

As a cross-cutting field between ocean development and multi-robot system(MRS),the underwater multi-robot system(UMRS)has gained increasing attention from researchers and engineers in recent *** this paper,we present a comprehensive survey of cooperation issues,one of the key components of UMRS,from the perspective of the emergence of new *** specifically,we categorize the cooperation in terms of task-space,motion-space,measurement-space,as well as their ***,we analyze the architecture of UMRS from three aspects,i.e.,the performance of the individual underwater robot,the new functions of underwater robots,and the technical approaches of *** conclude,we have discussed related promising directions for future *** survey provides valuable insight into the reasonable utilization of UMRS to attain diverse underwater tasks in complex ocean application scenarios.

关键词： Cooperation formation control multi-robot systems(MRS) taxonomy underwater robots underwater tasks

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A Continuous Illumination Estimator for Shadow Removal 13

A Continuous Illumination Estimator for Shadow Removal

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13th IEEE International Conference on CYBER Technology in Automation, Control, and Intelligent systems, CYBER 2023

作者： Liu, Jiawei Fan, Huijie Su, Yiming Yan, Zhen Wang, Qiang Li, Wentao 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 Key Laboratory of Manufacturing Industrial Integrated Shenyang University Shenyang110044 China

ISBN: (纸本)9798350315196

Shadow removal methods often encounter difficulties in completely removing shadows or avoiding excessively bright removal results in shadow areas. To address this challenge, we propose a continuous-intensity shadow synthesis model and an illumination estimator for shadow removal. Our shadow synthesis model generates visually realistic images with continuously varying shadow intensity to augment the current shadow removal dataset. By utilizing the synthesized shadow images, we train a network to accurately estimate the illumination intensity in shadow areas. The estimated illumination intensity is positive for a shadow input image and negative for an over-lit input image, thus our method can illuminate shadow areas or suppress over-lit areas. Experimental results demonstrate that our method outperforms current state-of-the-art shadow removal methods, particularly when handling shadows with a wide range of intensity variations. © 2023 IEEE.

关键词： Computer vision

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A Framework for Automatic Identification of Neural Network Structural Redundancy Based on Reinforcement Learning 5

A Framework for Automatic Identification of Neural Network S...

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5th International Conference on Computer Information Science and Artificial Intelligence, CISAI 2022

作者： Wu, Tingting Song, Chunhe Zeng, Peng State Key Laboratory of Robotics 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 University of Chinese Academy of Sciences Beijing100049 China

ISBN: (纸本)9781510662520

The increasing structure of neural networks makes it difficult to deploy on edge devices with limited computing resources. Network pruning has become one of the most successful model compression methods in recent years. Existing works usually compress models by removing unimportant filters based on the importance. However, the importance-based algorithms tend to ignore the parameters that extract edge features with small criterion values. And recent studies have shown that the existing criteria rely on norm and lead to similar model compression structures. Aiming at the problems of ignoring edge features and manually specifying the pruning rate in current importance-based model pruning algorithms, this paper proposes an automatic recognition framework for neural network structure redundancy based on reinforcement learning. First, we perform cluster analysis on the filters of each layer, and map the filters into a multidimensional space to generate similar sets with different functions. We then propose a criterion for identifying redundant filters within similar sets. Finally, we use reinforcement learning to automatically optimize the cluster dimension, and then determine the optimal pruning rate for each layer to reduce the performance loss caused by pruning. Extensive experiments on various benchmark network architectures and datasets demonstrate the effectiveness of our proposed framework. © 2023 SPIE.

关键词： Reinforcement learning

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Design and Control for WLR-3P:A Hydraulic Wheel-Legged Robot

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Cyborg and Bionic systems 2023年第1期4卷 243-259页

作者： Xu Li Haoyang Yu Haibo Feng Songyuan Zhang Yili Fu State Key Laboratory of Robotics and System College of Mechatronics EngineeringHarbin Institute of TechnologyHarbin 150001China State Key Laboratory of Fluid Power and Mechatronic Systems Zhejiang UniversityHangzhou 310027China Intelligent Robot Research Center Zhejiang LaboratoryHangzhou 311100China

The robot used for disaster rescue or field exploration requires the ability of fast moving on flat road and adaptability on complex *** hybrid wheel-legged robot(WLR-3P,prototype of the third-generation hydraulic wheel-legged robot)has the characteristics of fast and efficient mobility on flat surfaces and high environmental adaptability on rough *** this paper,3 design requirements are proposed to improve the mobility and environmental adaptability of the *** meet these 3 requirements,2 design principles for each requirement are put ***,for light weight and low inertia with high stiffness,3-dimensional printing technology and lightweight material are ***,the integrated hydraulically driven unit is used for high power density and fast response ***,the microhydraulic power unit achieves power autonomy,adopting the hoseless design to strengthen the reliability of the hydraulic *** is more,the control system including hierarchical distributed electrical system and control strategy is *** mobility and adaptability of WLR-3P are demonstrated with a series of ***,the robot can achieve a speed of 13.6 km/h and a jumping height of 0.2 m.

关键词： robot Robot terrain

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Flexible Sensors Used for Lower Assisting Exoskeleton 16th

Flexible Sensors Used for Lower Assisting Exoskeleton

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

作者： Xiao, Yang Chen, Chunjie Liu, Yao Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen518055 China Guangdong Provincial Key Laboratory of Robotics and Intelligent System Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen518055 China

ISBN: (纸本)9789819964857

In recent years, with the aging of the social population, exoskeleton robots have a wide range of application prospects in rehabilitation assistance, walking assistance, and physical expansion. However, the sensors developed for traditional robots currently have problems such as poor wearability, poor biocompatibility, and poor adaptability. To realize human-machine motion coordination assistance with multiple degrees of freedom and multiple motion states more effectively, and improve the flexibility, real-time performance, and reliability of the interaction between the wearer and the exoskeleton, it is necessary to design a set of flexible sensing systems to monitor the wearer’s motion status. It provides intelligent sensing technology support for adaptive control of exoskeleton in complex environments. This paper proposes a new flexible stretchable capacitive sensor and introduces its selection and manufacturing process. In the following experiments, three different slopes in the static experiment and dynamic experiment were used to test its performance and explore the accuracy and stability of its angle measurement. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023.

关键词： Capacitive sensors

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