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High Performance Soft Electrochemical Actuators Based on Hierarchical Conductive Polymer Ionogels

Journal of Bionic engineering 2023年第6期20卷 2755-2763页

作者： Hongwei Hu Shengtao Zhang Yan Li Xinghao Hu Lin Xu Aixin Feng Guanggui Cheng Jianning Ding Zhejiang Provincial Key Laboratory of Laser Processing Robotics College of Mechanical and Electrical EngineeringWenzhou UniversityWenzhou325035China Institute of Intelligent Flexible Mechatronics Jiangsu UniversityZhenjiang212013China School of Mechanical Engineering Jiangsu University of Science and TechnologyZhenjiang212100China School of Mechanical Engineering Yangzhou UniversityYangzhou225127China Jiangsu Collaborative Innovation Center of Photovoltaic Science and Engineering Changzhou UniversityChangzhou213164China Ruian Graduate School of Wenzhou University Ruian325207ZhejiangChina

Electrochemical actuators based on conductive polymers are emerging as a strong competitive in the field of soft actuators because of their intrinsically conformable/elastic nature,low cost,low operating voltage and air-working *** development has shown that adding electroactive materials,such as CNT and graphene,can improve their actuation *** the complex material systems used,their output strains(one of the key factors)are generally lower than 1%,which limited further applications of them in multiple ***,we report soft electrochemical actuators based on conductive polymer ionogels by embedding polyaniline particles between the PEDOT:PSS *** show that such a hierarchical structure not only leads to a high conductivity(1250 S/cm)but also improved electrochemical *** a low operating voltage of 1 V,the maximum strain of these soft actuators reaches an exceptional value of 1.5%,with a high blocking force of 1.3 *** these high-performance electrochemical actuators,we demonstrate soft grippers for manipulating object and a bionic flower stimulated by an electrical *** work sets an important step towards enabling the enhanced performance of electrochemical actuators based on conductive polymers with designed microstructures.

关键词： Conductive polymer Soft actuator Polyaniline PEDOT:PSS Bioinspired actuator

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Active Movements Intention Recognition for Upper Limb Rehabilitation Robots Based on EMG Signals

Active Movements Intention Recognition for Upper Limb Rehabi...

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2023 IEEE International Conference on Real-Time Computing and robotics, RCAR 2023

作者： Zhang, Hengwei Xu, Linsen Chen, Gen Hohai University School of Mechanical and Electrical Engineering Changzhou213000 China Hohai University Changzhou Key Laboratory of Intelligent Manufacturing Technology and Equipment Suzhou Research Institute Hohai University College of Mechanical and Electrical Engineering Changzhou213000 China

ISBN: (纸本)9798350327182

The recognition of upper limb movements based on Electromyographic(EMG) signals is an important method for the implementation of active assisted training modes for rehabilitation robots. In this paper, EMG signals are used for the recognition of six common upper limb movements. Specifically, the acquired EMG signals are first processed by noise reduction, active segment detection, and windowing. Then, fusing deep learning algorithms and attention mechanisms, two deep learning networks are designed to recognise the pre-processed segmented time-domain signals and spectrograms respectively. The experimental results show that the accuracy of upper limb movement recognition based on segmented EMG signals is 93.7%, which is better than the recognition accuracy based on spectrograms and meets the requirements of active-assisted training mode for upper limb rehabilitation robots. © 2023 IEEE.

关键词： Deep learning

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Tactile-Based Object Pose Estimation Employing Extended Kalman Filter 8

Tactile-Based Object Pose Estimation Employing Extended Kalm...

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8th IEEE International Conference on Advanced robotics and Mechatronics, ICARM 2023

作者： Lin, Qiguang Yan, Chaojie Li, Qiang Ling, Yonggen Zheng, Yu Lee, Wangwei Wan, Zhaoliang Huang, Bidan Liu, Xiaofeng College of IoT Engineering Hohai University Jiangsu Key Laboratory of Special Robotic Technology Jiangsu Changzhou213022 China Zhejiang University Institute of Cyber-System and Control State Key Laboratory of Industrial Control and Technology Hangzhou China Bielefeld33619 Germany Tencent Robotics X Shenzhen China School of Computer Science and Engineering Sun Yat-sen University Guangzhou China

ISBN: (纸本)9798350300178

In this paper, we present a new approach to estimate the pose of an object being manipulated by a multi-fingered robotic hand. The method utilizes advanced tactile sensors with high spatial resolution to optimize the estimation of the object's pose using an Extended Kalman Filter (EKF) based approach. We defined and derived the state and measurement equations, as well as evaluated the estimation accuracy in grasping tasks. The approach is able to effectively account for the pose transition caused by tactile pushing, and the mapping from the object's pose to the contact position and normal direction as measured by the tactile sensor. The method was evaluated in multiple grasping experiments in simulation scenarios. Results show that the estimation can converge towards the ground truth in a relatively short period of time, with displacement and rotation errors remaining within acceptable levels. This new method has the potential to improve the accuracy and reliability of robotic grasping and manipulation tasks. © 2023 IEEE.

关键词： Extended Kalman filters

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Planning strategy for intruder agent based on game theory and artificial potential field

Planning strategy for intruder agent based on game theory an...

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2021 IEEE International Conference on Real-Time Computing and robotics, RCAR 2021

作者： Xu, Jiahong Liu, Xiaofeng Zhou, Xu Wang, Huan Lin, Qiguang Jiangsu Key Laboratory of Special Cloud Robots Changzhou213022 China Changzhou Key Laboratory of Cloud Robots and Intelligent Technology Changzhou213022 China College of IoT Engineering Hohai University Changzhou213022 China

ISBN: (纸本)9781665436786

In our work, we propose a planner based on game theory and artificial potential field (APF) that enables intruder to confront defender in 2-D environment. The intruder would compute the mixed strategy approximate Nash equilibrium in the space of agent APF trajectory to maximally approach the target region while evading the pursuit of defender. First, according to the improved APF, the finite pure strategy matrix of agents is obtained by considering the opponent's response to the agents' actions iteratively. Then, Particle Swarm optimization (PSO) is taken to compute the mixed strategy approximate Nash equilibrium based on the expected profit composed of pure strategy matrix. Final, extensive simulation tests on agents are conducted to measure the performance of the planner we proposed. The simulation results show that our method not only has great advantages in the face of greedy defenders, but also is superior to the traditional APF planning algorithm. © 2021 IEEE.

关键词： Game theory

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A Novel Soft-Rigid Hybrid Actuator with Vertebrae

A Novel Soft-Rigid Hybrid Actuator with Vertebrae

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2023 IEEE International Conference on Real-Time Computing and robotics, RCAR 2023

作者： Chen, Gen Xu, Linsen Liu, Zhipeng Zhang, Hengwei Hohai University School of Mechanical and Electrical Engineering Changzhou213000 China Hohai University Changzhou Key Laboratory of Intelligent Manufacturing Technology and Equipment College of Mechanical and Electrical Engineering China Hohai University Suzhou Research Institute Changzhou213000 China Hefei Institutes of Physical Science Chinese Academy of Sciences Hefei230031 China

ISBN: (纸本)9798350327182

Soft robots are very widely used nowadays, yet the combination of soft and rigid is too little studied. In this paper, a novel spine-inspired soft-rigid hybrid actuator (SRHA) is proposed. The SRHA can limit its radial deformation to reduce the ineffective deformation, while also controlling the balloon effect of the SRHA and also enhancing its maximum withstand pressure. The bending angle and motion of SRHA are modeled. The relationship between pressure and bending angle of SRHA is derived based on the constitutive model and moment balance and verified with experiments, and the results show a good agreement. The kinematic model of the proposed SRHA is established by the piecewise constant curvature(PCC) method and coordinate transformation, and the model can calculate the arbitrary position of the SRHA. It is verified that the SRHA is almost twice as stiff in the 90 degree bending position and that the SRHA can provide greater end forces within the pressure tolerance range. Finally, it is demonstrated that changing the shape of the rigid vertebrae can change the function of the actuator, providing a direction for soft robotics where shape or form is required. © 2023 IEEE.

关键词： Kinematics

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Mechanism Design and Mechanical Analysis of Reconfigurable Wheel-track Wheel Based on Offset Guide Rod Mechanisms 4

Mechanism Design and Mechanical Analysis of Reconfigurable W...

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2022 4th International Symposium on robotics and intelligent Manufacturing technology, ISRIMT 2022

作者： Li, Zelin Xu, Linsen Liu, Jinfu Sui, Xiang Hefei Institutes of Physical Science Chinese Academy of Sciences Hefei China University of Science and Technology of China Hefei China College of Mechanical and Electrical Engineering Hohai University China Changzhou Key Laboratory of Intelligent Manufacturing Technology and Equipment China Suzhou Research Institute Hohai University Changzhou China Changzhou Vocational Institute of Industry Technology Changzhou China School of Intelligent Equipment Changzhou College of Information Technology Changzhou China

According to different terrain characteristics, combined with the motion characteristics of wheeled and tracked mobile mechanisms, a reconfigurable wheel-track hybrid deformable wheel with multiple motion forms is proposed and developed. It is composed of a track, wheel body, slewing bearing, and conductive slip ring. In the wheel body, the deformation mechanism, braking mechanism, and turnover locking mechanism can make it realize four kinds of motion forms, such as wheeled form and triangular-tracked form. Based on the corresponding parameter model, the static and dynamic analysis of the deformation mechanism is carried out. Among them, the dynamic analysis puts forward two solutions to the rigid impact problem in the deformation process, and the second solution is systematically modeled. It is found that it can be expressed as a standard second-order system, and the simulation parameters are set according to its characteristics to verify the feasibility of the scheme. © Published under licence by IOP Publishing Ltd.

关键词： Wheels

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Efficient Network Compression through Smooth-Lasso Constraint

Efficient Network Compression through Smooth-Lasso Constrain...

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2020 International Conference on Communications, Information System and Computer engineering, CISCE 2020

作者： Ye, Xiaowei Xu, Ning Liu, Xiaofeng Yao, Xiao Jiang, Aiming Hohai University The College of IoT Engineering Changzhou China Hohai University Changzhou Key Laboratory of Robotics and Intelligent Technology College of Iot Engineering Dept. of Communication Engineering Changzhou China

ISBN: (纸本)9781728197616

The powerful capabilities of deep convolutional neural networks make them useful in various fields. However, most edge devices are difficult to afford the huge amount of parameters and high computational cost. Therefore, it is highly imperative to compress these huge models to make them lightweight to enable real-time inference on edge devices. Channel pruning is a mainstream method of network compression. Generally, the Lasso constraint is imposed on the scaling factor in the batch normalization layer to make them tend to zero for selecting unimportant channels and then prune them. However, Lasso is a non-smooth function that is not derivable at zero, we experimentally find that when the value of the loss function is small, it is difficult to decline continuously. Aiming at the above problems, this paper proposes a pruning strategy based on the derivable function Smooth-Lasso, using Smooth-Lasso as a regularization constraint to perform sparse training and then prune the network. Experiments on benchmark datasets and convolutional networks show that our method can not only make the loss function converge quickly, but also save more storage space and computational cost than the baseline method while maintaining the same level of accuracy as the original network. © 2020 IEEE.

关键词： Convolutional neural networks

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Active Movements Intention Recognition for Upper Limb Rehabilitation Robots Based on EMG Signals

Active Movements Intention Recognition for Upper Limb Rehabi...

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IEEE International Conference on Real-time Computing and robotics (RCAR)

作者： Hengwei Zhang Linsen Xu Gen Chen School of Mechanical and Electrical Engineering Hohai University Changzhou China College of Mechanical and Electrical Engineering Hohai University Changzhou Key Laboratory of Intelligent Manufacturing Technology and Equipment Suzhou Research Institute Hohai University Changzhou China

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A Novel Soft-Rigid Hybrid Actuator with Vertebrae

A Novel Soft-Rigid Hybrid Actuator with Vertebrae

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IEEE International Conference on Real-time Computing and robotics (RCAR)

作者： Gen Chen Linsen Xu Zhipeng Liu Hengwei Zhang School of Mechanical and Electrical Engineering Hohai University Changzhou China College of Mechanical and Electrical Engineering Hohai University Changzhou Key Laboratory of Intelligent Manufacturing Technology and Equipment Suzhou Research Institute Hohai University Changzhou China Chinese Academy of Sciences Hefei Institutes of Physical Science Hefei China

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Efficient Network Compression Through Smooth-Lasso Constraint

Efficient Network Compression Through Smooth-Lasso Constrain...

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International Conference on Communications, Information System and Computer engineering (CISCE)

作者： Xiaowei Ye Ning Xu Xiaofeng Liu Xiao Yao Aiming Jiang The College of IoT Engineering Hohai University Changzhou China Key Laboratory of Robotics and Intelligent Technology College of IOT Engineering Hohai University Changzhou China

ISBN: (数字)9781728197616

ISBN: (纸本)9781728197623

关键词： Conferences Computer vision Information processing Pattern recognition Training Computer science Germanium

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