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BPS2025 - Twisting, stretching, and imaging chiral biopolymers, such as DNA, in real time

Biophysical Journal 2025年第3期124卷 379a-379a页

作者： Jack W. Shepherd Jamieson A.L. Howard Sebastien Guilbaud Zhaokun Zhou Mark C. Leake School of Physics Engineering and Technology University of York York United Kingdom Cairn Research Ltd. Faversham United Kingdom Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institute of Advanced Technology Guangdong China Department of Biology University of York York United Kingdom

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Effect of pattern on the resolution of the visual-tactile sensor

Effect of pattern on the resolution of the visual-tactile se...

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IEEE International Conference on robotics and Biomimetics

作者： Qingling Duan Qi Zhang Zhiyuan Liu Yongsheng Ou Faculty of Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen Guangdong Province PR China Department of Shenzhen College of Advanced Technology University of Chinese Academy of Sciences Shenzhen China Department of Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen Guangdong Province PR China Department of Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institute of Advanced Technology Chinese Academy of Sciences

ISBN: (纸本)9781665481106

Thanks to high spatial resolution and multi-tactile mode perception, visual-tactile sensing technology has been widely used in various robot operations such as active perception, pose estimation and in-palm operation. However, the pattern as an essential part of the optic tactile sensor has rarely been studied. Therefore, this paper investigated the effect of the different patterns on the resolution of the visual-tactile sensors. The silicone sensors with different densities and sizes and cameras integrate different tactile sensors, collect the sensor stress data in different situations, and process the data with deep learning models. The performance of the prediction forces of different patterns was evaluated by the root mean square error (RMSE). The results show that the proposed four patterns can decouple the normal and shear forces, and the force resolution of the semi-sparse pattern is better than the other pattern designs. Furthermore, the grad-cam method is used to obtain the focus of the deep learning model decoupling forces, showing that the semi-sparse pattern tends to cover the whole image because it has better performance.

关键词： Deep learning Training Three-dimensional displays Force Robot control Tactile sensors Cameras

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Hyper-redundant hybrid manipulator modeling method

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International Journal of Mechanical Sciences 2025年

作者： Shijie Wang Wei Feng Weijun Wang Jinyue Liu Dong Yang Tiejun Li School of Mechanical Engineering Hebei University of Science and Technology Shijiazhuang 050018 China School of Mechanical Engineering Hebei University of Technology Tianjin 300401 China Guangdong Provincial Key Laboratory of Construction Robotics and Intelligent Construction Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen 518055 China Guangdong Provincial International Joint Research Center for Robotics and Intelligent Construction Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen 518055 China University of Chinese Academy of Sciences Beijing 100049 China Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen 518055 China

The performance of traditional serial and parallel manipulators is inherently limited, leading to a growing interest in hybrid manipulators within the field of robotics. By incorporating both kinematic redundancy and actuation redundancy, the performance of hybrid manipulators can be further enhanced. However, this also presents challenges for their kinematics and dynamics modeling and analysis. To establish the motion mapping relationship between the end-effector and the actuated joints of hyper-redundant hybrid manipulators (HRHMs), this study introduces concepts of modularization and recursion, deriving a unified recursive model for generalized velocity and acceleration based on screw theory. Utilizing the proposed virtual world frame, different types of series-parallel combinations are unified, and the generalized kinematics model of the centroids for each component is formulated by integrating the geometric vector parameters of the manipulator. Subsequently, based on the principle of virtual work and wrench, the generalized dynamics model of HRHMs is developed. By constructing Jacobian matrices for each centroid within the local fixed frame, the dynamics model of the HRHM is further simplified, allowing for the determination of actuation forces in both non-redundant and redundant actuation modes. Finally, a simulation model of an HRHM comprising six modules is created, validating the accuracy of the theoretical model proposed in this study. The findings of this research possess universal applicability in the kinematics and dynamics modeling of general hybrid manipulators and can serve as a reference for exploring the modeling and analysis of continuum-like robots composed of rigid bodies.

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E3MoP: Efficient motion planning based on heuristic-guided motion primitives pruning and path optimization with sparse-banded structure

arXiv

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arXiv 2020年

作者： Wen, Jian Zhang, Xuebo Gao, Haiming Yuan, Jing Fang, Yongchun The Institute of Robotics and Automatic Information System College of Artificial Intelligence Nankai University Tianjin300350 China The Tianjin Key Laboratory of Intelligent Robotics Nankai University Tianjin300350 China Zhejiang Lab Hangzhou311121 China

To solve the autonomous navigation problem in complex environments, an efficient motion planning approach is newly presented in this paper. Considering the challenges from large-scale, partially unknown complex environments, a three-layer motion planning framework is elaborately designed, including global path planning, local path optimization, and time-optimal velocity planning. Compared with existing approaches, the novelty of this work is twofold: 1) a novel heuristic-guided pruning strategy of motion primitives is proposed and fully integrated into the state lattice-based global path planner to further improve the computational efficiency of graph search, and 2) a new soft-constrained local path optimization approach is proposed, wherein the sparse-banded system structure of the underlying optimization problem is fully exploited to efficiently solve the problem. We validate the safety, smoothness, flexibility, and efficiency of our approach in various complex simulation scenarios and challenging real-world tasks. It is shown that the computational efficiency is improved by 66.21% in the global planning stage and the motion efficiency of the robot is improved by 22.87% compared with the recent quintic Bézier curve-based state space sampling approach. We name the proposed motion planning framework E3MoP, where the number 3 not only means our approach is a three-layer framework but also means the proposed approach is efficient in three stages. Copyright © 2020, The Authors. All rights reserved.

关键词： Motion planning

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An Improved Chimp Optimization Algorithm for Short-term Hydrothermal Scheduling

IAENG International Journal of Computer Science

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IAENG International Journal of Computer Science 2022年第3期49卷 666页

作者： Chen, Gonggui Wang, Shumin He, Yongsheng Shang, Wanfeng Long, Hongyu Key Laboratory of Industrial Internet of Things and Networked Control Ministry of Education Chongqing University of Posts and Telecommunications Chongqing400065 China Chongqing University of Posts and Telecommunications Chongqing400065 China State Grid Chongqing Electric Power Company Chongqing400015 China Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen Shenzhen518055 China Chongqing Key Laboratory of Complex Systems and Bionic Control Chongqing University of Posts and Telecommunications Chongqing400065 China

The short-term hydrothermal scheduling (STHS) is a complex non-linear, non-convex and high-dimensional mathematical optimization problem. Due to the fact that the original chimp optimization algorithm (ChOA) is likely to fall into local optimum and has the disadvantage of low population diversity, an improved chimp optimization algorithm (IChOA) is proposed to solve the STHS problem. Firstly, Logistic-Tent chaotic mapping is employed to initialize the population and increase the population diversity. Then a new nonlinear convergence factor is introduced to make the optimization search process more applicable to STHS problems. Next, particle swarm algorithm (PSO) and gravitational search algorithm (GSA) are combined to enhance the shortcoming and balance the global search ability and local exploration ability of ChOA. Moreover, Cauchy mutation and opposition-based learning strategy are supplemented as perturbation interference when the optimal position is not updated to improve the ability to leap out of the local optimum. Finally, a graded optimization strategy is adopted for the constraint handing of dynamic reservoir balance and thermal power balance. Three standard hydrothermal power systems are utilized to verify the practicability and validity of the proposed method. Results of simulations reveal that IChOA has significant competitive advantages in addressing the STHS problem. © 2022, IAENG International Journal of Computer Science. All Rights Reserved.

关键词： Particle swarm optimization (PSO)

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A Deep Siamese Neural Network N-Shot Learning Approach for the Recognition of Chinese Calligraphy

SSRN

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SSRN 2022年

作者： Zhou, Zhaokun Wang, Weijun Ou, Yuhao Che, Qishu Feng, Wei Shenzhen Key Laboratory of Smart Sensing and Intelligent Systems Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Guangdong Shenzhen518055 China Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Guangdong Shenzhen518055 China CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Guangdong Shenzhen518055 China Guangzhou Institute of Advanced Technology Chinese Academy of Sciences Guangdong Guangzhou511458 China University of Chinese Academy of Sciences Guangdong Shenzhen518055 China

The forms of Chinese calligraphic characters vary considerably, posing a challenge even for a typical educated Chinese to read. The total number of characters is in the excess of ten thousand, many of which have small numbers of samples surviving to date. Thus, Chinese calligraphy recognition is a unique challenge for the state-of-the art deep-learning algorithms that require large training datasets to accurately categorize. Here we present a novel deep-convolutional Siamese Neural Network (SNN) based architecture that finishes training in one day on a single RTX 2080 Ti graphics card while reaching an accuracy of 95.0% on a vast set of more than 6000 Chinese characters. We found that, after image pre-processing and setting the optimized SNN parameters, our recognition algorithm (i) is light weight, (ii) trains with small numbers of samples, achieving few-/one-shot learning (iii) recognizes a new character that is not present in the training set and (iv) includes the new character in the dictionary so the dictionary is continually expanded. Further work on the improvement of our method is also proposed including the localization of multiple tokens in an image to further automate detections and word prediction with RNNs to boost categorization accuracy. © 2022, The Authors. All rights reserved.

关键词： Optical character recognition

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A novel multi-scale fourier descriptor based on plane orthogonal vectors for fast shape retrieval

A novel multi-scale fourier descriptor based on plane orthog...

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2019 IEEE International Conference on robotics and Biomimetics, ROBIO 2019

作者： Ma, Jiajun Zhu, Jiafeng Liang, Guoyuan Wu, Xinyu Guangdong Provincial Key Lab of Robotics and Intelligent System CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen Guangdong Province China

ISBN: (纸本)9781728163215

Shape retrieval is an interesting and challenging issue in computer vision and robot vision. The recent works employing Fourier-based multi-scale descriptors achieve some success in shape retrieval, especially make real-time application possible by improving the efficiency. However, these methods are commonly adopting really complex shape descriptors to present the shape information which is not intuitive enough. In our work, we propose a new Fourier-based method with novel multi-scale descriptor which is a combination of contour feature and regional feature. This novel descriptor has two main characteristics: First, utilize six different invariant signatures which are based on plane orthogonal vectors;Second, leverage multiple scale structures to describe local and global information of shapes. Except the easiness in understanding, this descriptor approach also produces a more distinct topology of shapes than other approaches which means the property of stability on variations, linear or nonlinear. The method is tested on some popular databases that provides a promising retrieval rate(87.46% and 99.27%) with constant time complexity optimization. The results confirm that our method is more capable of representing the topology of shapes than most other methods based on Fourier descriptor. © 2019 IEEE.

关键词： Topology

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The EEG-based lower limb exoskeleton system optimization strategy based on channel selection

The EEG-based lower limb exoskeleton system optimization str...

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2019 IEEE International Conference on Real-Time Computing and robotics, RCAR 2019

作者： Long, Xingguo Ma, Yue Ma, Xunju Yan, Zefeng Wang, Can Wu, Xinyu Shenzhen 518055 China Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institutes of Advanced Technology CAS University of Chinese Academy of Sciences Chinese University of Hong Kong Department of Mechanical and Automation Engineering

ISBN: (纸本)9781728137261

Compared with traditional exoskeleton robots, the brain-computer interface (BCI) based lower limb exoskeleton system can directly control the robot by recording the user's brain activity signals, such as the electroencephalogram (EEG). The brain activity signals contain the original and global motion intention, which is capable of operating the walking assistance exoskeleton device in a way that matches the operator's will more closely. In our previous work, an EEG-based lower limb exoskeleton system and a human-machine interaction paradigm that orient to the scenario of dynamic motion is designed. However, the EEG sensor configuration is a time-consuming process and limit the utility of the EEG based system. Besides, channel redundancy makes it difficult to explore experimental mechanisms of the designed paradigm. Therefore, in this paper, a heuristic channel selection optimization algorithm with the L1 norm is applied to the BCI system. Based on the data of four subjects, we verify the performance of the selected optimal channel subset and explore a universal optimal channel subset. Tested on another two new subjects, the universal optimal subset shows a promising prospect in improving the performance of the EEG-based exoskeleton system. © 2019 IEEE.

关键词： Electroencephalography

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Improved dynamic window approach with ellipse equations for autonomous navigation of unmanned surface vehicle

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Journal of Institute of Control, robotics and systems 2020年第8期26卷 624-629页

作者： Kim, Hyogon Yun, Sung-Jo Choi, Young-Ho Ryu, Jae-Kwan Won, Byong-Jae Suh, Jin-Ho Korea Institute of Robotics and Technology Convergence Korea Republic of Unmanned/Intelligent Robotic Systems R&D Lab. LIG Nex1 Korea Republic of Department. of Mechanical System Engineering Pukyoung National University Korea Republic of

Autonomous navigation technology for Unmanned Surface Vehicles (USVs) has seen many recent advancements. In order for a USV to operate autonomously, the path to move from its current location to its destination must be planned, and local path planning must be applied for tracking the path and avoiding obstacles. The Dynamic Window Approach (DWA) is a well-known navigation algorithm used for local path planning. The DWA algorithm derives the linear velocity and angular velocity by evaluating the object function defined as destination direction, velocity, and distance from the obstacle. However, because DWA does not consider the velocity and direction of obstacles, USVs may be in danger when avoiding high-speed obstacles. In this paper, we propose an improved DWA algorithm that considers the velocity and direction of obstacles. Whereas the existing DWA algorithm defines the obstacle recognition area as a circle, the proposed DWA algorithm defines the obstacle recognition area as an ellipse and reflects the speed of the obstacle in the ellipse. In this study, we implemented a simulation to compare the existing DWA algorithm with the improved DWA algorithm proposed here. The results confirm that the proposed DWA algorithm can avoid dynamic obstacles more safely than the existing DWA algorithm. © ICROS 2020.

关键词： Unmanned surface vehicles

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Integration of ferroelectric materials in microdevices for biomedical application

Integration of ferroelectric materials in microdevices for b...

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第9届纳米操纵、制造与测量国际会议

作者： Xiangzhong Chen Bradley J.Nelson Salvador Pané Multi-Scale Robotics Lab(MSRL) Institute of Robotics and Intelligent System Swiss Federal Institute of Technology(ETH)ZurichSwitzerland

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