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

作者： Gao, Chengzhi Xie, Ye Zhu, Yiting Liang, Dingkun Kong, Lingyu Wang, Xin Xie, Anhuan Gu, Jianjun Research Center for Intelligent Robotics Research Institute of Interdisciplinary Innovation Zhejiang Laboratory Hangzhou311100 China Zhejiang Engineering Research Center for Intelligent Robotics Hangzhou311100 China Zhejiang University Zhejiang Hangzhou311100 China Department of Electrical and Computer Engineering Dalhousie University HalifaxNSB3H 4R2 Canada

ISBN: (纸本)9789819964918

Due to the lack of accurate stability theoretical basis, the dynamic balance control of bipedal robots is a challenging topic. In this paper, we propose a controller that combines virtual model control and whole body control. In our framework, the whole system is simplified into a spring inverted pendulum model. Decoupling control is carried out for this model, and a virtual model is introduced to establish the relationship between the joint torque of the support leg and the state of the center of mass. The distribution of reaction force is obtained through decoupling closed-loop control. The whole body control part first uses multi task whole body control to determine the kinematics information, and then solves the joint feedforward torque through dynamical model, thus obtaining the desired force position hybrid control. Proposed algorithm improved the problem of incomplete decoupling between states and increased the stiffness of the support leg. The newly designed control framework was tested in Simscape dynamic simulation and verified the anti-interference ability and fast walking ability of Whole Body Balance Control for bipedal robots based on Virtual Model Control. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2023.

关键词： Inverted pendulum

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Dissolvable temporary barrier:a novel paradigm for flexible hydrogel patterning in organ-on-a-chip models

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Bio-Design and Manufacturing 2024年第2期7卷 153-166页

作者： Ding Wang Qinyu Li Chenyang Zhou Zhangjie Li Kangyi Lu Yijun Liu Lian Xuan Xiaolin Wang Department of Micro/Nano Electronics School of Electronic Information and Electrical EngineeringShanghai Jiao Tong UniversityShanghai 200240China Department of Ophthalmology LKS Faculty of MedicineThe University of Hong KongHong Kong 999077China Institute of Medical Robotics Shanghai Jiao Tong UniversityShanghai 200240China National Key Laboratory of Advanced Micro and Nano Manufacture Technology Shanghai Jiao Tong UniversityShanghai 200240China National Center for Translational Medicine(Shanghai)SHU Branch Shanghai UniversityShanghai 200444China

A combination of hydrogels and microfluidics allows the construction of biomimetic three-dimensional(3D)tissue models in vitro,which are also known as *** hydrogel patterningwith awell-controlled spatial distribution is typically achieved by embedding sophisticated microstructures to act as a ***,these physical barriers inevitably expose cells/tissues to a less physiologically relevant microenvironment than in vivo ***,we present a novel dissolvable temporary barrier(DTB)strategy that allows robust and flexible hydrogel patterning with great freedom of design and desirable flow stimuli for cellular *** key aspect of this approach is the patterning of a water-soluble rigid barrier as a guiding path for the hydrogel using stencil printing technology,followed by a barrier-free medium perfusion after the dissolution of the *** and multiple tissue compartments with different geometries can be established using either straight or curved DTB *** effectiveness of this strategy is further validated by generating a 3D vascular network through vasculogenesis and angiogenesis using a vascularized microtumor *** a new proof-of-concept in vasculature-on-a-chip,DTB enables seamless contact between the hydrogel and the culture medium in closed microdevices,which is an improved protocol for the fabrication ofmultiorgan ***,we expect it to serve as a promising paradigm for organ-on-a-chip devices for the development of tumor vascularization and drug evaluation in the future preclinical studies.

关键词： Dissolvable temporary barrier Hydrogel patterning Microfluidics Organ-on-a-chip Vascularization

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Base position planning of mobile manipulators for assembly tasks in construction environments

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Advances in Manufacturing 2023年第1期11卷 93-110页

作者： Dai-Jun Xie Ling-Dong Zeng Zhen Xu Shuai Guo Guo-Hua Cui Tao Song Shanghai Key Laboratory of Intelligent Manufacturing and Robotics School of Mechatronic Engineering and AutomationShanghai UniversityShanghai200444People’s Republic of China National Demonstration Center for Experimental Engineering Training Education Shanghai UniversityShanghai200444People’s Republic of China School of Mechanical and Automotive Engineering Shanghai University of Engineering ScienceShanghai201620People’s Republic of China Shanghai Collaborative Innovation Center of Intelligent Manufacturing Robot Technology for Large Components Shanghai201620People’s Republic of China

With good mobility and flexibility,mobile manipulators have shown broad applications in construction *** position(BP)planning,which refers to the robot autonomously determining its working station in the environment,is an important technique for mobile manipulators when performing the construction assembly task,especially in a large-scale construction ***,the BP planning process is tedious and time-consuming for a human worker to carry ***,to improve the efficiency of construction assembly tasks,a novel BP planning method is proposed in this paper,which can lead to appropriate BPs and minimize the number of BPs at the same ***,the feasible BP regions are generated based on the grid division and the variable workspace of the mobile ***,the positioning uncertainties of the mobile manipulator are considered in calculating the preferred BP areas using ***,a set coverage optimization model is established to obtain the minimum number of BPs using an optimization algorithm according to the greedy *** simulated experiment based on a 9-degree of free(DoF)mobile manipulator has been *** results illustrated that the time for BP planning was significantly reduced and the number of BPs was reduced by 63.41%compared to existing manual planning,which demonstrated the effectiveness of the proposed method.

关键词： Base position(BP)planning Mobile manipulators Variable workspace Positioning uncertainties Construction environments

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UAV Swarm Exploration With Byzantine Fault Tolerance

UAV Swarm Exploration With Byzantine Fault Tolerance

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2021 China Automation Congress, CAC 2021

作者： Liao, Zhentang Zhang, Lihua Dong, Zhiyan Institute of AI and Robotics Fudan University Shanghai China Shanghai Engineering Research Center of AI and Robotics China Engineering Research Center of AI and Robotics Ministry of Education China

ISBN: (纸本)9781665426473

Swarm robots need Byzantine fault tolerance to ensure their tasks can still be complete even if malfunctioning or malicious robots exist. Nevertheless, advancement in implementing Byzantine fault tolerance is not suitable for the UAV swarm exploration task. This study aims to contribute to this growing area of research. We presented an implementation of Byzantine fault tolerance for swarm robots, proposing a theoretically more effective and flexible approach than previous approaches. We integrated a multi-agent foraging algorithm with a BFT consensus algorithm for the UAV swarm exploration task, providing a method that can be generalized to similar multi-agent cooperative tasks. We developed a ROS-based framework to incorporate such algorithms into swarm robots, facilitating robotics development and testing. Empirical results of the UAV swarm exploration task imply our approach's advantages. © 2021 IEEE

关键词： Unmanned aerial vehicles (UAV)

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Deep Reinforcement Learning-Based Path-Tracking for Unmanned Vehicle Navigation Enhancement

Deep Reinforcement Learning-Based Path-Tracking for Unmanned...

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2024 International Conference on Electronics, Information, and Communication, ICEIC 2024

作者： Yang, Seung Geon Cho, Eun Ho Kim, Jeongyun Lim, Seung-Chan School of ICT Robotics and Mechanical Engineering Hankyong National University Anseong Korea Republic of School of Electrical Electronic and Control Engineering Hankyong National University Anseong Korea Republic of Massachusetts Institute of Technology Wireless Information and Network Sciences Laboratory CambridgeMA02139 United States

ISBN: (纸本)9798350371888

Despite the growing interest in autonomous vehicles, practical challenges remain particularly in achieving high tracking performance. In this study, we address this issue by developing a path tracking algorithm based on deep reinforcement learning. To this end, we elaborately design the Markov decision process and implement the deep Q-network (DQN) training algorithm. Simulation results validate the superior convergence speed, accuracy, and stability of the proposed DQN-based tracking algorithm in comparison to the conventional approach. © 2024 IEEE.

关键词： Reinforcement learning

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Towards Consistent Object Detection via LiDAR-Camera Synergy

Towards Consistent Object Detection via LiDAR-Camera Synergy

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2024 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2024

作者： Luo, Kai Wu, Hao Yi, Kefu Yang, Kailun Hao, Wei Hu, Rongdong College of Automotive and Mechanical Engineering Changsha University of Science and Technology China School of Traffic and Transportation Engineering Changsha University of Science and Technology China School of Robotics Hunan University China National Engineering Research Center of Robot Visual Perception and Control Technology Hunan University China Changsha Intelligent Driving Institute China

ISBN: (纸本)9781665410205

As human-machine interaction continues to evolve, the capacity for environmental perception is becoming increasingly crucial. Integrating the two most common types of sensory data, images, and point clouds, can enhance detection accuracy. Currently, there is no existing model capable of detecting an object's position in both point clouds and images while also determining their corresponding relationship. This information is invaluable for human-machine interactions, offering new possibilities for their enhancement. In light of this, this paper introduces an end-to-end Consistency Object Detection (COD) algorithm framework that requires only a single forward inference to simultaneously obtain an object's position in both point clouds and images and establish their correlation. Furthermore, to assess the accuracy of the object correlation between point clouds and images, this paper proposes a new evaluation metric, Consistency Precision (CP). To verify the effectiveness of the proposed framework, an extensive set of experiments has been conducted on the KITTI and DAIR-V2X datasets. The study also explored how the proposed consistency detection method performs on images when the calibration parameters between images and point clouds are disturbed, compared to existing post-processing methods. The experimental results demonstrate that the proposed method exhibits ex-cellent detection performance and robustness, achieving end-to-end consistency detection. The source code will be made publicly available at https://***/xifen523/COD. © 2024 IEEE.

关键词： Object detection

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Advances of triboelectric and piezoelectric nanogenerators toward continuous monitoring and multimodal applications in the new era

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International Journal of Extreme Manufacturing 2025年第1期7卷 174-205页

作者： Jianlong Hong Xiao Wei Huiyun Zhang Yukun Xiao Chongguang Meng Yuqi Chen Jiahui Li Ling Li Sanghoon Lee Qiongfeng Shi Jun Wu Interdisciplinary Research Center School of Electronic Science and EngineeringSoutheast UniversityNanjing 211189People’s Republic of China Department of Robotics&Mechatronics Engineering Daegu Gyeongbuk Institute of Science&TechnologyDaegu 42899Republic of Korea

Benefiting from the widespread potential applications in the era of the Internet of Thing and metaverse,triboelectric and piezoelectric nanogenerators(TENG&PENG)have attracted considerably increasing *** outstanding characteristics,such as self-powered ability,high output performance,integration compatibility,cost-effectiveness,simple configurations,and versatile operation modes,could effectively expand the lifetime of vastly distributed wearable,implantable,and environmental devices,eventually achieving self-sustainable,maintenance-free,and reliable ***,current triboelectric/piezoelectric based active(***-powered)sensors still encounter serious bottlenecks in continuous monitoring and multimodal applications due to their intrinsic limitations of monomodal kinetic response and discontinuous transient *** work systematically summarizes and evaluates the recent research endeavors to address the above challenges,with detailed discussions on the challenge origins,designing strategies,device performance,and corresponding diverse ***,conclusions and outlook regarding the research gap in self-powered continuous multimodal monitoring systems are provided,proposing the necessity of future research development in this field.

关键词： triboelectric piezoelectric continuous monitoring multimodal sensing internet of thing

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Feedforward Backpropagation Artificial Neural Network for Modeling the Forward Kinematics of a Robotic Manipulator

Feedforward Backpropagation Artificial Neural Network for Mo...

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2023 International Conference on Innovation and Intelligence for Informatics, Computing, and Technologies, 3ICT 2023

作者： Bouzid, Rania Narayan, Jyotindra Gritli, Hassene Higher Institute of Information and Communication Technologies Tunis1164 Tunisia Indian Institute of Technology Guwahati Mechatronics and Robotics Laboratory Department of Mechanical Engineering Guwahati781039 India National Engineering School of Tunis Tunis1002 Tunisia

ISBN: (纸本)9798350307771

Determining an end-effector position and orientation, known as forward kinematics (FK), is a crucial aspect of robotic manipulation. This research addresses the FK problem using a Feedforward Backpropagation Artificial Neural Network (FFBP-ANN) and examines the network's performance with different hyperparameters. The input of the FFBP-ANN is primarily formed using three different datasets: fixed-step values, random values, and sinusoidal-signal based values, for a 2-DOF robotic manipulator. The output of the FFBP-ANN is evaluated using FK formulation of the robot manipulator. Thereafter, the FFBP-ANN is trained utilizing the input-output training dataset using The Neural Network Toolbox for MATLAB. The network's potential is investigated by varying the critical hyperparameters, including the number of hidden neurons and the number of hidden layers. Moreover, the effectiveness of the proposed FFBP-ANN is investigated with three different training optimizers including the utilization of Levenberg-Marquardt, Bayesian Regularization, and Scaled Conjugate Gradient optimization algorithms. During training, by adjusting the network's weights and biases iteratively, the backpropagation technique allows the network to effectively learn and comprehend the relationship between joint positions and Cartesian coordinates. The comparative results offer valuable insights into the strengths and limitations of different ANN architectures when applied to solving FK problems. In this way, this study focuses on exploring the application of the FFBP-ANN in resolving FK challenges and assisting in the identification of appropriate network types for path-planning tasks. © 2023 IEEE.

关键词： End effectors

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Dual Fuzzy Sliding Mode Control of Manipulator Based on Rotor UAV Platform 6

Dual Fuzzy Sliding Mode Control of Manipulator Based on Roto...

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

作者： Liu, Yunfei He, Chunlai Cheng, Shuo The 21ST Research Institute of China Electronic Technology Group Corporation Robotics Engineering Center Shanghai China

ISBN: (数字)9781665498739

ISBN: (纸本)9781665498739

In order to achieve the purpose that the robotic arm based on the rotor platform can still track the position and attitude of the end of the robotic arm stably when subjected to external disturbances and internal disturbances, this paper first designs a sliding mode control algorithm to enhance the anti-interference ability of the control system. In this method, the phenomenon of control law chattering occurs due to the problem of a large upper bound of interference. Therefore, the fuzzy sliding mode control method is designed on the basis of the above algorithm, and the coefficient of the switching gain term in the exponential reaching law sliding mode control algorithm is adaptively adjusted by the fuzzy control, thereby weakening the chattering of the control law. Fuzzy sliding mode control obviously improves chattering, but it does not solve the problem that the overall adjustment time of the control system is too long, and the performance of the control system in the control index of "rapidity"is not very good. Then a double fuzzy sliding mode control algorithm is designed, and the stability of the control system is proved by using the Lyapunov stability criterion. And through the simulation, it is known that this method not only retains the robustness of the sliding mode control algorithm, but also effectively weakens the chattering of the sliding mode control algorithm and the problem of long adjustment time, and improves the trajectory tracking of the end of the mechanical arm of the rotor platform precision. © 2022 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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Glass Objects Detection Based on Transformer Encoder-Decoder 6

Glass Objects Detection Based on Transformer Encoder-Decoder

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

作者： Hou, Xiaonan Zhan, Minghao Wang, Chunlei Fan, Chunhui The 21st Research Institute of China Electronics Technology Group Corporation Robotics Engineering Center Shanghai China

ISBN: (数字)9781665498739

ISBN: (纸本)9781665498739

Glass objects detection is a relatively new and challenging work in the field of computer vision. This work will also have an impact on other visual tasks, such as depth estimation, instance segmentation and saliency detection. Compared with using high-precision sensors for glass object detection, the vision based detection method is more economical and robust. In this paper, we focus on the task of glass object detection in the field of image segmentation. Traditional semantic segmentation methods mostly used the model based on convolutional neural network to complete the task. On this basis, we introduce the Transformer encoder-decoder architecture to expand the size of receptive field, make full use of different levels of context information and improve the detection effect of glass objects. In this paper, the mixed model of convolutional neural network and Transformer is used to realize the detection of glass objects in the Pytorch environment, and the model is trained and evaluated on the Trans10K-v2 dataset. In the experiment, the input image resolution is 512 × 512, the final pixel accuracy is 93.94%, and the mean intersection over union is 71.32%. © 2022 IEEE.

关键词： Object detection

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