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Design of grayscale digital light processing 3D printing block by machine learning and evolutionary algorithm

Composites Communications 2022年 36卷

作者： Zhao, Baowen Zhang, Mengjie Dong, Le Wang, Dong Robotics Institute School of Mechanical Engineering Shanghai Jiao Tong University Shanghai 200240 China State Key Laboratory of Mechanical System and Vibration Shanghai Jiao Tong University Shanghai 200240 China Meta Robotics Institute Shanghai Jiao Tong University Shanghai 200240 China

Grayscale digital light processing (DLP) 3D printing method, using grayscale light patterns to adjust the microscale material properties, is a revolutionary technology for future advanced manufacturing. However, the design and optimization method of the grayscale distribution remains elusive. In this paper, we propose an optimization method for grayscale DLP printed rectangular blocks based on a machine learning and evolutionary algorithm. We use an automated finite element model-based evaluation to predict the deformation shapes with arbitrary grayscale distribution, considering the nonlinear mechanical performances. A machine learning model based on recurrent neural networks is trained using the database formed by the finite element method model to enable fast and precise prediction of the deformed shapes. Optimal designs of the deformed shapes are efficiently realized via integrating the machine learning model and evolution algorithm method. Grayscale distributions are optimized to form desired deformations and validated by experiments. This work paves the way for designing and optimizing grayscale digital light processing 3D printed structures. © 2022 Elsevier Ltd

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Digital Modeling of Massage Techniques and Reproduction by Robotic Arms

arXiv

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arXiv 2024年

作者： Xu, Yuan Huang, Kui Guo, Weichao Du, Leyi The SJTU Paris Elite Institute of Technology Shanghai Jiao Tong University Shanghai200240 China The State Key Laboratory of Mechanical System and Vibration School of Mechanical Engineering Shanghai Jiao Tong University Shanghai200240 China Meta Robotics Institute Shanghai Jiao Tong University Shanghai200240 China School of Gongli Hospital Medical Technology University of Shanghai for Science and Technology China

This paper explores the digital modeling and robotic reproduction of traditional Chinese medicine (TCM) massage techniques. We adopt an adaptive admittance control algorithm to optimize force and position control, ensuring safety and comfort. The paper analyzes key TCM techniques from kinematic and dynamic perspectives, and designs robotic systems to reproduce these massage techniques. The results demonstrate that the robot successfully mimics the characteristics of TCM massage, providing a foundation for integrating traditional therapy with modern robotics and expanding assistive therapy applications. Copyright © 2024, The Authors. All rights reserved.

关键词： Digital elevation model

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Constant Direct Current Triboelectric Nanogenerator Based on Soft-Contact Mode for Self-Powered Cathodic Protection

SSRN

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SSRN 2022年

作者： Li, Ming Jiang, Tianyi Ren, Yukun Jiang, Hongyuan School of Mechatronics Engineering Harbin Institute of Technology West Da-zhi Street 92 Harbin150001 China State Key Laboratory of Robotics and System Harbin Institute of Technology West Da-zhi Street 92 Heilongjiang Harbin150001 China

Triboelectric nanogenerator (TENG) has been proved to be a promising technology for harvesting decentralized energy. However, the application fields of the traditional TENGs are limited by the high crest factor. Here a constant direct current TENG (CDC-TENG) with low crest factor is proposed by connecting three rotating TENGs with specific phase difference (Δ θ ) in parallel. Excellent wear resistance and humidity resistance are demonstrated owing to the soft-contact mode and 3D encapsulated design. For the CDC-TENG (3P6E), the crest factor surprisingly decreases to 1.05 while that of the TENGs without Δ θ is up to 1.31. Meanwhile, the current density up to 3021 μA·m -2 is achieved at the rotation speed of 500 r·min -1 . Then, owing to the excellent output of constant direct current (DC), a commercial timer is directly driven by the CDC-TENG without using capacitor. Finally, the CDC-TENG is used as the power source of cathodic protection (CP) system, which exhibits an excellent corrosion protection effect. In general, this work provides a meaningful template for TENGs to broaden the marine industrial applications of constant DC demand. © 2022, The Authors. All rights reserved.

关键词： Nanogenerators

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Design, Analysis, and Experiment of a Coupled-Adaptive Underactuated Prosthetic Handbased on Linkage Mechanisms

SSRN

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SSRN 2022年

作者： Fan, Shaowei Dai, Jinghui Zhang, Ning Zhang, Ting Cheng, Ming Liu, Bingchen Jiang, Li State Key Laboratory of Robotics and System Harbin Institute of Technology Heilongjiang Harbin150080 China National Research Center for Rehabilitation Technical Aids Beijing100176 China College of Mechanical and Electrical Engineering Soochow University Jiangsu Suzhou215021 China

To reproduce the characteristics of human hand motion, this paper proposes a novel four-degree-of-freedom prosthetic hand that combines the advantages of coupled motion and self-adaptive motion. A coupled-adaptive underactuated finger was developed using a cross-coupled four-link mechanism and an adaptive five-link mechanism. The finger can perform both power and precision grasping excellently. Based on the seesaw mechanism, a differential mechanism among the middle finger, ring finger, and little finger was developed to further reduce the size and weight of the prosthetic hand. To avoid the ejection phenomenon, the stability of the finger is systematically analyzed in this paper using the grasp-state space analysis technique. The stability analysis results indicate that ejection does not occur in the entire workspace of the proposed finger. The grasping experiments indicate that the proposed prosthetic hand possesses excellent stability and adaptability. © 2022, The Authors. All rights reserved.

关键词： Prosthetics

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Joint Counting, Detection and Re-Identification for Multi-Object Tracking

arXiv

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arXiv 2022年

作者： Ren, Weihong Wu, Denglu Cao, Hui Chen, Xi'ai Han, Zhi Liu, Honghai The School of Mechanical Engineering and Automation State Key Lab of Robotics and Systems Harbin Institute of Technology Shenzhen518055 China The Shenzhen Duorou Intelligent System Co. Ltd. Shenzhen518055 China The School of Electrical Engineering Xi’an Jiaotong University Xi’an710049 China State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Science Beijing110169 China

The recent trend in 2D multiple object tracking (MOT) is jointly solving detection and tracking, where object detection and appearance feature (or motion) are learned simultaneously. Despite competitive performance, in crowded scenes, joint detection and tracking usually fail to find accurate object associations due to missed or false detections. In this paper, we jointly model counting, detection and re-identification in an end-to-end framework, named CountingMOT, tailored for crowded scenes. By imposing mutual object-count constraints between detection and counting, the CountingMOT tries to find a balance between object detection and crowd density map estimation, which can help it to recover missed detections or reject false detections. Our approach is an attempt to bridge the gap of object detection, counting, and re-Identification. This is in contrast to prior MOT methods that either ignore the crowd density and thus are prone to failure in crowded scenes, or depend on local correlations to build a graphical relationship for matching targets. The proposed MOT tracker can perform online and real-time tracking, and achieves the state-of-the-art results on public benchmarks MOT16 (MOTA of 79.7%), MOT17 (MOTA of 81.3%) and MOT20 (MOTA of 78.9%). Source code is available at https://***/weihong9/CountingMOT. Copyright © 2022, The Authors. All rights reserved.

关键词： Object detection

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An Evolutionary Game based Secure Clustering Protocol with Fuzzy Trust Evaluation and Outlier Detection for Wireless Sensor Networks

arXiv

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arXiv 2022年

作者： Yang, Liu Lu, Yinzhi Yang, Simon X. Zhong, Yuanchang Guo, Tan Liang, Zhifang The School of Communication and Information Engineering Chongqing University of Posts and Telecommunications Chongqing China The Advanced Robotics and Intelligent Systems Laboratory School of Engineering University of Guelph GuelphONN1G2W1 Canada The State Key Laboratory of Power Transmission Equipment & System Security and New Technology School of Electrical Engineering Chongqing University Chongqing400044 China

Trustworthy and reliable data delivery is a challenging task in Wireless Sensor Networks (WSNs) due to unique characteristics and constraints. To acquire secured data delivery and address the conflict between security and energy, in this paper we present an evolutionary game based secure clustering protocol with fuzzy trust evaluation and outlier detection for WSNs. Firstly, a fuzzy trust evaluation method is presented to transform the transmission evidences into trust values while effectively alleviating the trust uncertainty. And then, a K-Means based outlier detection scheme is proposed to further analyze plenty of trust values obtained via fuzzy trust evaluation or trust recommendation. It can discover the commonalities and differences among sensor nodes while improving the accuracy of outlier detection. Finally, we present an evolutionary game based secure clustering protocol to achieve a trade-off between security assurance and energy saving for sensor nodes when electing for the cluster heads. A sensor node which failed to be the cluster head can securely choose its own head by isolating the suspicious nodes. Simulation results verify that our secure clustering protocol can effectively defend the network against the attacks from internal selfish or compromised nodes. Correspondingly, the timely data transfer rate can be improved significantly. © 2022, CC BY.

关键词： Sensor nodes

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Research on the seamless positioning method of an unmanned system based on UWB/IMU/GNSS fusion for indoor and outdoor

Research on the seamless positioning method of an unmanned s...

引用

International Conference on Advanced Mechatronic systems (ICAMechS)

作者： Tao Jiang Qian Wang Linshuai Zhang Shuoxin Gu Lin Xu Xianggui Tang School of Intelligent Medicine Chengdu University of Traditional Chinese Medicine Unmanned System Intelligent Perception Control Technology Engineering Laboratory of Sichuan Province Chengdu University of Information Technology Chengdu School of Automation Chengdu University of Information Technology Chengdu School of Intelligent Medicine Chengdu University of Traditional Chinese Medicine School of Automation Chengdu University of Information Technology International Joint Research Center of Robotics and Intelligence System of Sichuan Province Chengdu School of Automation Chengdu University of Information Technology International Joint Research Center of Robotics and Intelligence System of Sichuan Province Chengdu Sichuan School of Intelligent Medicine Chengdu University of Traditional Chinese Medicine Chengdu

This paper studies the multi-sensor fusion positioning methods of Ultra-wideband (UWB), Global Navigation Satellite system (GNSS) and Inertial measurement unit (IMU), and constructs a seamless positioning system based on UWB/IMU/GNSS multi-sensor fusion. In this paper, the indoor location information provided by UWB is fused with IMU location data through extended Kalman filter, which solves the problems of signal loss, track interruption and jump in positioning information when unmanned systems enter indoor environment, and also improves the positioning accuracy of the overall system. In the experiment of the indoor and outdoor scenes of the unmanned vehicle system, the trajectory diagram of each sensor combination positioning mode is counted, and the error of positioning information is analyzed and studied. The results show that the overall positioning error of this method is small, it can provide stable and reliable whole-time positioning information, and achieve the high-precision seamless positioning required by unmanned systems.

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Point Cloud based Motion State Estimation Method for Autonomous Driving

Point Cloud based Motion State Estimation Method for Autonom...

引用

2023 International Conference on Advanced Mechatronic systems, ICAMechS 2023

作者： Jiang, Tao Zhu, Enzhi Wu, Sidong Zhang, Linshuai Gu, Shuoxin Xu, Lin Wang, Qian Tang, Xianggui Chengdu Univ. of Traditional Chinese Med. Unmanned Syst. Intelligent Percept. Contr. Technol. Eng. Laboratory of Sichuan Province Chengdu University of Information Technology School of Intelligent Medicine Chengdu China Chengdu University of Information Technology School of Automation Chengdu China Chengdu Univ. of Info. Technol. Unmanned Syst. Intelligent Perception Control Technology Engineering Laboratory of Sichuan Province Chengdu University of Information Technology School of Automation Chengdu China Chengdu University of Traditional Chinese Medicine School of Automation Chengdu Univ. of Info. Technol. Intl. Jt. Res. Ctr. of Robotics and Intell. Syst. of Sichuan Prov. School of Intelligent Medicine Chengdu China Chengdu University of Information Technology International Joint Research Center of Robotics and Intelligence System of Sichuan Province School of Automation Chengdu China

ISBN: (纸本)9798350307474

Generally, motion vector information primarily stems from moving objects, while static objects contribute minimally to the estimation task. Traditional approaches for motion vector estimation typically rely on scene flow methods that depend on deep models to extract features from individual points at a high cost. These methods then acquire flow information through complex matching mechanisms or feature decoding. Such approaches are computationally expensive and exhibit substantial latency. Moreover, they neglect the importance of motion objects in motion vector estimation and the interference from static objects. Therefore, this paper introduces a novel method that first performs point cloud motion segmentation and subsequently estimates motion vectors. This approach focuses on leveraging point cloud information annotated with motion objects to estimate three-dimensional scene flow more effectively. By employing motion segmentation, we can obtain annotations for moving objects, enabling greater emphasis on the estimation of motion vectors for more challenging cases. In our experiments conducted on the KITTI dataset, the proposed method demonstrates superior performance compared to existing scene flow estimation methods. Specifically, without considering motion segmentation errors, the error in the motion direction is only 0.0363 m/s, showcasing better performance. Additionally, our method achieves an error of 0.076 m for three-dimensional endpoint error (EPE3D), showcasing distinct advantages over current scene flow networks. © 2023 IEEE.

关键词： Errors

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Hardware Programming of a Single-input Pneumatic Mechanism to Control Multiple Elastic Inflatable Actuators

Hardware Programming of a Single-input Pneumatic Mechanism t...

引用

International Conference on Mechatronics and Machine Vision in Practice (M2VIP)

作者： Ningbin Zhang Guoying Gu Xiangyang Zhu State Key Laboratory of Mechanical System and Vibration Shanghai Jiao Tong University and Robotics Institute School of Mechanical Engineering Shanghai Jiao Tong University China

ISBN: (纸本)9781665431545

Elastic inflatable actuators (EIAs) are widely used in the emerging field of soft robotics. Although integrating multiple EIAs in soft robots has been demonstrated successful, these EIAs typically require independent control inputs that results in a complex actuation process. This paper proposes a single-input pneumatic mechanisms (SIPM) to generate a wide range of output pressures via hardware programming, enabling multiple EIAs to achieve different motions. We first present a conceptual design of the SIPM and build its pneumatic model based on air compressibility, which relates the control inputs, the structural parameters of the SIPM, and the output pressures. Then, we perform a series of parametric analyses and numerical simulations to investigate the hardware programming of structural parameters for target output pressures. Finally, a SIPM prototype whose structural parameters are derived from simulation results is developed. The experimental results validate the effectiveness of the proposed mechanism.

关键词： Actuators Atmospheric modeling Simulation Prototypes Process control Programming Predictive models

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Debiased Distillation for Consistency Regularization 39

Debiased Distillation for Consistency Regularization

引用

39th Annual AAAI Conference on Artificial Intelligence, AAAI 2025

作者： Wang, Lu Xu, Liuchi Yang, Xiong Huang, Zhenhua Cheng, Jun School of Computer Science and Engineering Northeastern University Shenyang China Institute of Applied Artificial Intelligence of the Guangdong-Hong Kong-Macao Greater Bay Area Shenzhen Polytechnic University Shenzhen China School of Computer Science South China Normal University Guangzhou China Guangdong Provincial Key Laboratory of Robotics and Intelligent System Shenzhen Institute of Advanced Technology CAS China The Chinese University of Hong Kong Hong Kong

ISBN: (纸本)157735897X

Knowledge distillation transfers “dark knowledge” from a large teacher model to a smaller student model, yielding a highly efficient network. To improve the network's generalization ability, existing works use a larger temperature coefficient for knowledge distillation. Nevertheless, these methods may reduce the confidence of the target category and lead to ambiguous recognition of similar samples. To mitigate this issue, some studies introduce intra-batch distillation to reduce prediction discrepancy. However, these methods overlook the inconsistency between background information and the target category, which may increase prediction bias due to noise disturbance. Additionally, label imbalance from random sampling and batch size can undermine network generalization reliability. To tackle these challenges, we propose a simple yet effective Intra-class Knowledge Distillation (IKD) method that facilitates knowledge sharing within the same class to ensure consistent predictions. First, we initialize the matrix and the vector to store logits and class counts provided by the teacher, respectively. Then, in the first epoch, we calculate the sum of logits and sample counts per class and perform KD to prevent knowledge omission. Finally, in subsequent training, we update the matrix to obtain the average logits and compute the KL divergence between the student's output and the updated matrix according to the label index. This process ensures intra-class consistency and improves the student's performance. Furthermore, this method theoretically reduces prediction bias by ensuring intra-class consistency. Extensive experiments on the CIFAR-100, ImageNet-1K, and Tiny-ImageNet datasets validate the superiority of IKD. Copyright © 2025, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

关键词： Students

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