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2022 IEEE International Conference on robotics and Biomimetics, ROBIO 2022

作者： Gao, Hongyan Zou, Yun Huang, Shaoping Chen, Weidong Gao, Anzhu Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education Institute of Medical Robotics and Department of Automation Shanghai200240 China Institute of Medical Robotics Shanghai Jiao Tong University Shanghai200240 China

ISBN: (纸本)9781665481090

Cochlear implant surgery is one of the most challenging surgeries due to the limited workspace and delicate inner structure. A traditional electrode implant instrument is a passive elastic forceps, which needs another forceps to help grip or release the electrode. It is not convenient to achieve delicate operations in a confined space. This paper develops a miniaturized pneumatic electrode gripper at the tip of forceps to achieve active gripping. It transmits the pressurized air through 3D-printed inner lumens to form two inflated soft bubbles to push the electrode to the rigid shell for accurate positioning. The finite element analysis is carried out to evaluate the shape of inflated soft bubbles with variable soft films. A prototype of a gripper with inner tortuous airways is fabricated using micro 3D printing technique, and experiments are carried out to validate its accuracy and demonstrate its ability to grip and release. Finally, robotic teleoperation using a robotic arm and a joystick is implemented for cochlear implant surgery. Results demonstrate that the developed miniaturized pneumatic gripper has successfully achieved electrode implantation in a 3D-printed cochlear phantom. © 2022 IEEE.

关键词： Electrodes

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Dimension Reduction for Dynamic Analysis of Gene Expression Data Using Variational Autoencoder 13

Dimension Reduction for Dynamic Analysis of Gene Expression ...

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

作者： Yuan, Shuai Chen, Shipeng Yang, Yongliang School of Electrical and Control Engineering Shenyang Jianzhu University Liaoning Shenyang110016 China Shenyang Institute of Automation State Key Laboratory of Robotics Chinese Academy of Sciences Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Liaoning Shenyang110106 China

ISBN: (纸本)9798350315196

Single-cell RNA sequencing technology captures gene expression at the whole-genome scale and single-cell level in many cells. Thus, the cellular states during a physiological process would be captured in detail. These data provide new opportunities and challenges for systems biology. Previously, the models in systems biology dealt with the dynamics of specific signaling pathways. However, it is almost impossible to directly model the dynamics of the whole genome due to the ultrahigh dimensionality of the data. Here, to model its gene regulatory dynamics, the dimensionality of the whole genome was reduced significantly using the latent space of a variational autoencoder, a generative deep learning model. In the low-dimensional latent space, an ordinary differentiation equation (ODE) system has been established to analyze the dynamic characteristics of the whole genome system. To demonstrate the effectiveness of this method, we generated a low-dimensional representation of a systems biology model we previously developed. The variational autoencoder reduced the dimension from 13 to 2 in latent space. An ODE model was developed to analyze the dynamics of this two-dimensional system. The results indicated that the 2-dimensional model captured the essence of the original systems biology model. © 2023 IEEE.

关键词： Dynamics

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Point-line RGB-D SLAM Algorithm Based on Multiple Back-projection Strategy

Point-line RGB-D SLAM Algorithm Based on Multiple Back-proje...

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robotics, Control and Automation Engineering (RCAE), International Conference on

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

ISBN: (数字)9798350355642

ISBN: (纸本)9798350355659

To overcome the limitations of the application of the SLAM algorithm, which is based on point features under harsh conditions, this paper innovatively proposes a SLAM algorithm that is based on point and line feature fusion. The algorithm uses an RGB-D camera as an input sensor to extract feature points and feature lines simultaneously from the input RGB image. To fully exploit spatial line feature information and mitigate the impact of environmental noise, we propose a multiple back-projection strategy guided by a depth map to robustly recover spatial line information. Finally, the proposed algorithm is compared with the ORB-SLAM2 algorithm in the public dataset TUM RGB-D. The results show that the proposed algorithm significantly improves the accuracy of localization and mapping.

关键词： Location awareness Simultaneous localization and mapping Automation Accuracy Working environment noise Feature extraction Cameras

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A grid-assisted 3D printing method for magnetically driven micro soft robot 9

A grid-assisted 3D printing method for magnetically driven m...

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9th International Conference on Advanced Manufacturing Technology and Materials Science, AMTMS 2021

作者： Gao, Jian Gao, Peng Rong, Weibin Li, Dongjie Wang, Lefeng State Key Laboratory of Robotics and System Harbin Institute of Technology Heilongjiang Harbin150001 China Key Laboratory of Advanced Manufacturing and Intelligent Technology Ministry of Education Harbin University of Science and Technology Heilongjiang Harbin150080 China

The magnetically driven micro soft robot is one of the research hotspots in the field of micro robots. A 3D printing method for manufacturing micro soft robots with the help of auxiliary grids is proposed. The shape flexibility of the micro soft robots manufactured by the micro 3D printing method can be improved, and internal structures composed of different materials inside the micro robots can be printed using this method. The technical details of the grid-assisted 3D printing process are introduced in this article. Micro soft robots with specific patterns were 3D printed, and the deformation and movement capabilities of the robots were verified in magnetically driven motion experiments. The experimental results prove that the grid-assisted 3D printing technology can not only manufacture magnetically driven micro soft robots, but also adjust the internal structure and motion performance of the robots. © 2022 institute of Physics Publishing. All rights reserved.

关键词： 3D printers

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Reexamining Indoor Mobile Robots from a Cognitive Perspective 5

Reexamining Indoor Mobile Robots from a Cognitive Perspectiv...

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5th International Conference on robotics and Computer Vision, ICRCV 2023

作者： Song, Fei Li, Jinyu Tang, Fengzhen Tang, Yandong Si, Bailu 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 University of Chinese Academy of Sciences Beijing China School of Systems Science Beijing Normal University Beijing China

ISBN: (纸本)9798350326369

The field of traditional mobile robot navigation has undergone a gradual transformation, evolving into a standardized and procedural research domain. Through a fresh cognitive perspective on this navigation process, a bridge emerges between robotic researchers and cognitive neuroscientists, thereby fostering the growth of interdisciplinary exploration. This article meticulously examines three pivotal phases of robot navigation: information acquisition, simultaneous localization and mapping (SLAM), and path planning. These phases are intricately linked to pertinent cognitive research. Furthermore, a comprehensive survey of existing biomimetic and neuromorphic algorithms is presented, highlighting their applications in augmenting robot navigation capabilities. Ultimately, this article charts a visionary course for the future of robot navigation, envisioning its potential in facilitating more intelligent and efficient navigation techniques. © 2023 IEEE.

关键词： Navigation

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Low-gain Control Strategy for Robot Manipulators Based on Sparse Feature Learning Dynamics with an Application to Collision Detection

Low-gain Control Strategy for Robot Manipulators Based on Sp...

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IEEE International Workshop on Safety, Security, and Rescue robotics (SSRR)

作者： Chenglong Yu Zhiqi Li Weixin Chou Hong Liu State Key Laboratory of Robotics and System Harbin Institute of Technology China

ISBN: (纸本)9781665456814

Recently, with the robotic technique developing toward precision and intelligence, robots have been used more widely in human life and production. As a common feature in the foreseen applications, robots should be able to detect unexpected collisions while ensuring dynamic accuracy, so as to improve safety at work. In the previous model-based collision detection solution, most methods assume that the robot dynamic model is complete and accurate. Unfortunately, reliable robot dynamics is hard to obtain due to model uncertainties, assembly errors, and the lack of information provided by manufacturers. This paper proposed a novel low-gain control strategy based on sparse feature learning dynamics. Firstly, without considering the physical structure parameters, the dynamics was learned directly via the data-driven technique. Secondly, according to the learned accurate dynamics, a model-based low-gain controller was designed to ensure control performance while avoiding excessive unspecified force. Finally, using this control strategy, sensorless collision detection was realized in a 7-DOF manipulator and the performance of the proposed method was evaluated.

关键词： Representation learning Service robots Dynamics Force Robot sensing systems Safety Security

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Centra-Net: A Centralized Network for Visual Localization Spanning Multiple Scenes

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IEEE Transactions on Multimedia 2025年

作者： Jiang, Zhiqiang Dai, Kun Wang, Ke Xie, Tao Fan, Zhendong Li, Ruifeng Kang, Peng Zhao, Lijun Harbin Institute of Technology State Key Laboratory of Robotics and System Harbin150006 China Harbin Institute of Technology Zhengzhou Research Institute Zhengzhou450000 China Jianghuai Advance Technology Center Hefei230000 China

We present Centra-Net, a centralized network that concurrently optimizes visual localization over numerous scenes under heterogeneous dataset domains. Centra-Net exemplifies storage efficiency by amalgamating multiple models with task-shared parameters into a singular cohesive structure. Technically, we develop a basic feature extraction unit (BFEU) with two parallel branches: one dedicated to local feature extraction and the other adept at adaptively generating a task-specific attention mask for feature calibration, thus bolstering its feature extraction capability across diverse scenes. Based on the BFEU, we introduce a filter-wise sharing mechanism (FSM) that adaptively determines parameter sharing within the unit, thus facilitating fine-grained parameter allocation. The key insight of FSM resides in reconceptualizing the parameter sharing of the unit as a learnable paradigm, enabling the determination of shared parameters to be made post-training. Finally, we suggest a complexity-prioritized gradient algorithm (CPGA) that capitalizes on task complexity to attain a harmonious learning space for various tasks, thus safeguarding optimal performances across all tasks. Through rigorous experiments on numerous benchmarks, Centra-Net demonstrates a notable edge over existing state-of-the-art works while operating with a significantly reduced parameter footprint. © 1999-2012 IEEE.

关键词： Deep learning Feature extraction Task complexity Visual localization

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An Underwater Acoustic Signal Denoising Method for Broadband Interference from Underwater Platforms Based on the Deep Neural Network Model 6

An Underwater Acoustic Signal Denoising Method for Broadband...

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6th International Conference on Information Communication and Signal Processing, ICICSP 2023

作者： Cao, Linxuan Lei, Zhixiong Zhou, Zihao Sun, Jie Shi, Yang School of Marine Science and Technology Northwestern Polytechnical University Shaanxi Key Laboratory of Underwater Information Technology Xi'an China Southwest China Institute of Electronic Technology Chengdu610036 China Shenyang Institute of Automation Chinese Academy of Sciences State Key Laboratory of Robotics Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110169 China

ISBN: (纸本)9798350339994

As underwater vehicles widely used in ocean observation, the self-noise generated from the underwater platforms will affect the underwater acoustic signal observation, impeding signal detection. In this paper, we proposed an ideal binary mask (IBM) based Deep Neural Network (DNN) denoising method to reduce the broadband transient interference that underwater platforms caused. First, we analysis the interference produced by the underwater glider, illustrating its hazard by a common noisy situation. Then the IBM based DNN model was train to reduce this interference. Compared with spectral subtraction and Wiener filtering method, the method we proposed has short processing time of 0.15 $s$ in average, 7 dB higher signal-to-interference ratio (SIR) gain, and more complete retention of the original signal components in low SIR situations. © 2023 IEEE.

关键词： broadband interference deep neural network ideal binary mask transient signal underwater acoustic signal denoising

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Fault-Tolerant formation keeping design for Multi-AUVs in MOOS-IvP

Fault-Tolerant formation keeping design for Multi-AUVs in MO...

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2022 International Conference on Innovations and Development of Information Technologies and robotics, IDITR 2022

作者： Gao, Peiyan Li, Yiping Zeng, Junbao Li, Shuo Chinese Academy of Sciences State Key Laboratory of Robotics Shenyang Institute of Automation Shenyang110016 China Chinese Academy of Sciences Institutes for Robotics and Intelligent Manufacturing Shenyang110169 China Key Laboratory of Marine Robotics Liaoning Province Shenyang110169 China University of Chinese Academy of Sciences Beijing100049 China

ISBN: (纸本)9781665409322

this paper demonstrates the design of the MOOSIvP middleware for multi-AUVs to solve the fault-tolerant formation keeping problem efficiently. The problem introduced in this paper addresses a map reconfiguration approach for the occurrence of failure. A vehicle failure may be a propeller failure, communication failure, or other similar undesirable events. A simulated AUV's failure was presented into the maritime environment in MOOS-IvP. Multiple AUVs sailed an area and discovered that one of them broke down. To complete its mission, the leader vehicle broadcasts new follower vehicles' waypoint configuration according to the reconfiguration map algorithm. Upon broadcasting, the followers formed a stable formation to continue their mission. A final report was sent to the shoreside control station with the location of the broken AUV and the updated shape of the formation. © 2022 IEEE.

关键词： Fault tolerance

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Research on adaptive crawling of underwater hexapod robot on complex seabed 12

Research on adaptive crawling of underwater hexapod robot on...

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12th International Conference on CYBER Technology in Automation, Control, and Intelligent systems, CYBER 2022

作者： Sun, Yingzhe Zhang, Qifeng Yao, Qingfeng Zhang, Aiqun 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 Key Laboratory of Marine Robotics Liaoning Province Shenyang1572000 China University of Chinese Academy of Sciences Beijing100049 China

ISBN: (数字)9781665472678

ISBN: (纸本)9781665472678

In this paper, the research on underwater adaptive walking planning of underwater hexapod robot is carried out aiming at the research goal of safe and stable seabed climbing behavior of underwater hexapod robot. Aiming at the unknown complex terrain on the seabed, an innovative method based on five-point gait is proposed to perceive the unknown terrain through the position of the foot tip. On the one hand, five-point gait can meet the high stability of underwater hexapod robot, on the other hand, it can avoid the problem of asynchronous landing of legs under other gait. The method of evaluating unknown terrain by foot position can reduce the number of sensors carried by the body on the one hand, and reduce the complexity of the overall planning method on the other hand. Finally, the paper will verify the correctness of the theory through the simulation method, and provide theoretical support for the underwater hexapod robot to crawl on the seabed. © 2022 IEEE.

关键词： Robot programming

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