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IEEE International Conference on robotics and Biomimetics

作者： Wei Wang Yige Liu Pengqing Ren Juanjuan Zhang Jingtai Liu Institute of Robotics and Automation Information System Nankai University Tianjin China

ISBN: (纸本)9781728103785;9781728103778

Human-in-the-loop (HITL) optimization of exoskeleton control during assisted walking can improve human mobility and reduce the energy cost. This process involves human-robot coadaptation as suggested by prior studies. There was a drop in the same subjects metabolic cost under the same assisted walking condition before and after the optimization process. It means the subjects adapted to walking with the exoskeleton while the exoskeleton learned the optimal control parameters for the subjects. We analyzed the process of human bodies learning to walk with an ankle exoskeleton, aiming to quantify the characteristics of human-robot coadaptation during HITL optimization of exoskeleton control. Data of eleven participants from prior experiments were utilized in this study. We identified similar sample conditions for each participant and investigated the trend of metabolic cost along with the HITL exoskeleton control optimization process. Results showed that the relationship between human metabolic cost and the time past in the optimization cycle approximately followed exponential curves with widespread adaptation rates. For the optimization process of four parameters with each condition sampled for two minutes, the time constants were averaged at 238 ± 207 optimization sample conditions. Our results can provide guidance to the training process of robot assisted human motion.

关键词： Exoskeletons Optimization Torque Legged locomotion Process control Performance evaluation

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Research on Stereo Vision Technology Based on Improved Region Growing Method

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Journal of Physics: Conference Series 2021年第1期2024卷

作者： Shilong Dai Xinghua Xia Hualiang Zhang School of Information and Control Engineering Shenyang Jianzhu University Shenyang 110168 China. Industrial Control Network and System Laboratory Shenyang Institute of Automation Chinese Academy of Sciences Shenyang 110016 China. Institudes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang 110169 China.

Image segmentation is the cornerstone of image analysis and image processing, its main difficulty is the ill-posedness of image segmentation. The region growing method is the most commonly used method in image segmentation. Its advantages are fast calculation speed, lower algorithm difficulty, and easy understanding. This article uses the area growing algorithm and TOF combined with binocular fusion technology. Discussed how to select the seed points in the region growing method. The algorithm proposed in this paper has high accuracy and high matching quality in the boundary area of the object and the area with large difference in depth. It has both matching time and reliability. It has good results and overcomes the limitations of the active and passive distance methods in the vision system.

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Exploiting offset-guided network for pose estimation and tracking

arXiv

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arXiv 2019年

作者： Zhang, Rui Zhu, Zheng Li, Peng Wu, Rui Guo, Chaoxu Huang, Guan Xia, Hailun Bejing Key Laboratory of Network System Architecture and Convergence School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing China Beijing Laboratory of Advanced Information Networks Beijing Institute of Automation Chinese Academy of Sciences Beijing China Horizon Robotics Beijing

Human pose estimation has witnessed a significant advance thanks to the development of deep learning. Recent human pose estimation approaches tend to directly predict the location heatmaps, which causes quantization errors and inevitably deteriorates the performance within the reduced network output. Aim at solving it, we revisit the heatmap-offset aggregation method and propose the Offset-guided Network (OGN) with an intuitive but effective fusion strategy for both two-stages pose estimation and Mask R-CNN. For two-stages pose estimation, a greedy box generation strategy is also proposed to keep more necessary candidates while performing person detection. For mask R-CNN, ratio-consistent is adopted to improve the generalization ability of the network. State-of-the-art results on COCO and PoseTrack dataset verify the effectiveness of our offset-guided pose estimation and tracking. Copyright © 2019, The Authors. All rights reserved.

关键词： Deep learning

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Recent Advances in Triboelectric Nanogenerators: From Technological Progress to Commercial Applications

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ACS Nano 2023年第12期17卷 11087-11219页

作者： Choi, Dongwhi Lee, Younghoon Lin, Zong-Hong Cho, Sumin Kim, Miso Ao, Chi Kit Soh, Siowling Sohn, Changwan Jeong, Chang Kyu Lee, Jeongwan Lee, Minbaek Lee, Seungah Ryu, Jungho Parashar, Parag Cho, Yujang Ahn, Jaewan Kim, Il-Doo Jiang, Feng Lee, Pooi See Khandelwal, Gaurav Kim, Sang-Jae Kim, Hyun Soo Song, Hyun-Cheol Kim, Minje Nah, Junghyo Kim, Wook Menge, Habtamu Gebeyehu Park, Yong Tae Xu, Wei Hao, Jianhua Park, Hyosik Lee, Ju-Hyuck Lee, Dong-Min Kim, Sang-Woo Park, Ji Young Zhang, Haixia Zi, Yunlong Guo, Ru Cheng, Jia Yang, Ze Xie, Yannan Lee, Sangmin Chung, Jihoon Oh, Il-Kwon Kim, Ji-Seok Cheng, Tinghai Gao, Qi Cheng, Gang Gu, Guangqin Shim, Minseob Jung, Jeehoon Yun, Changwoo Zhang, Chi Liu, Guoxu Chen, Yufeng Kim, Suhan Chen, Xiangyu Hu, Jun Pu, Xiong Guo, Zi Hao Wang, Xudong Chen, Jun Xiao, Xiao Xie, Xing Jarin, Mourin Zhang, Hulin Lai, Ying-Chih He, Tianyiyi Kim, Hakjeong Park, Inkyu Ahn, Junseong Huynh, Nghia Dinh Yang, Ya Wang, Zhong Lin Baik, Jeong Min Choi, Dukhyun Kyung Hee University Gyeonggi Yongin17104 Korea Republic of Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology 77 Massachusetts Avenue CambridgeMA02139 United States Department of Mechanical Engineering Soft Robotics Research Center Seoul National University Seoul08826 Korea Republic of Department of Mechanical Engineering Gachon University Seongnam13120 Korea Republic of Department of Biomedical Engineering National Taiwan University Taipei10617 Taiwan Frontier Research Center on Fundamental and Applied Sciences of Matters National Tsing Hua University Hsinchu30013 Taiwan School of Advanced Materials Science & Engineering Sungkyunkwan University Suwon16419 Korea Republic of Sungkyunkwan University 2066 Seobu-ro Gyeonggi Suwon16419 Korea Republic of Department of Chemical and Biomolecular Engineering National University of Singapore 4 Engineering Drive 4 117585 Singapore Division of Advanced Materials Engineering Jeonbuk National University 567 Baekje-daero Jeonbuk Jeonju54896 Korea Republic of Jeonbuk National University 567 Baekje-daero Jeonbuk Jeonju54896 Korea Republic of Department of Physics Inha University 100 Inha-ro Incheon22212 Korea Republic of School of Materials Science & Engineering Yeungnam University Gyeongbuk Gyeongsan38541 Korea Republic of 291 Daehak-ro Daejeon34141 Korea Republic of School of Materials Science and Engineering Nanyang Technological University 50 Nanyang Avenue 639798 Singapore Institute of Flexible Electronics Technology of Tsinghua Zhejiang Jiaxing314000 China Nanomaterials and System Lab Major of Mechatronics Engineering Faculty of Applied Energy System Jeju National University Jeju632-43 Korea Republic of School of Engineering University of Glasgow GlasgowG128QQ United Kingdom Seoul02792 Korea Republic of Department of Physics Inha University Incheon22212 Korea Republic of Suwon16419 Korea Republic of Department of

Serious climate changes and energy-related environmental problems are currently critical issues in the world. In order to reduce carbon emissions and save our environment, renewable energy harvesting technologies will serve as a key solution in the near future. Among them, triboelectric nanogenerators (TENGs), which is one of the most promising mechanical energy harvesters by means of contact electrification phenomenon, are explosively developing due to abundant wasting mechanical energy sources and a number of superior advantages in a wide availability and selection of materials, relatively simple device configurations, and low-cost processing. Significant experimental and theoretical efforts have been achieved toward understanding fundamental behaviors and a wide range of demonstrations since its report in 2012. As a result, considerable technological advancement has been exhibited and it advances the timeline of achievement in the proposed roadmap. Now, the technology has reached the stage of prototype development with verification of performance beyond the lab scale environment toward its commercialization. In this review, distinguished authors in the world worked together to summarize the state of the art in theory, materials, devices, systems, circuits, and applications in TENG fields. The great research achievements of researchers in this field around the world over the past decade are expected to play a major role in coming to fruition of unexpectedly accelerated technological advances over the next decade. © 2023 The Authors. Published by American Chemical Society

关键词： Nanogenerators

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Retrieval-based localization based on domain-invariant feature learning under changing environments

arXiv

引用

arXiv 2019年

作者： Hu, Hanjiang Wang, Hesheng Liu, Zhe Yang, Chenguang Chen, Weidong Xie, Le Autonomous Robot Lab Department of Automation Key Laboratory of System Control and Information Processing Ministry of Education Shanghai Jiao Tong University Shanghai200240 China T Stone Robotics Institute Chinese University of Hong Kong Hong Kong Bristol Robotics Laboratory University of the West of England BristolBS16 1QY United Kingdom School of Material Science and Engineering Shanghai Jiao Tong University Shanghai200240 China

Visual localization is a crucial problem in mobile robotics and autonomous driving. One solution is to retrieve images with known pose from a database for the localization of query images. However, in environments with drastically varying conditions (e.g. illumination changes, seasons, occlusion, dynamic objects), retrieval-based localization is severely hampered and becomes a challenging problem. In this paper, a novel domain-invariant feature learning method (DIFL) is proposed based on ComboGAN, a multi-domain image translation network architecture. By introducing a feature consistency loss (FCL) between the encoded features of the original image and translated image in another domain, we are able to train the encoders to generate domain-invariant features in a self-supervised manner. To retrieve a target image from the database, the query image is first encoded using the encoder belonging to the query domain to obtain a domain-invariant feature vector. We then preform retrieval by selecting the database image with the most similar domain-invariant feature vector. We validate the proposed approach on the CMU-Seasons dataset, where we outperform state-of-the-art learning-based descriptors in retrieval-based localization for high and medium precision scenarios. Copyright © 2019, The Authors. All rights reserved.

关键词： Machine learning

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The design of 1553b relay circuit based on FPGA

引用

IOP Conference Series: Materials Science and Engineering 2020年第1期740卷

作者： Zhonghua Han Chengcheng Huang Jiayu Peng Shuai Wang Faculty of Information and Control Engineering Shenyang Jianzhu University Shenyang 110168 China Department of Digital Factory Shenyang Institute of Automation the Chinese Academy of Sciences (CAS) Shenyang 110016 China Key Laboratory of Network Control System Chinese Academy of Sciences Shenyang 110016 Liaoning China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang 110016 Liaoning China

On the basis of increasing the transmission distance of the 1553B bus, in order to maintain the simplicity and stability of the bus and improve its anti-jamming ability, the 1553B signal relay circuit based on FPGA is designed in this paper. The signal transmission part is consists of the software and the hardware, and the chip of ZYNQ series is used in the FPGA. Firstly, the transmitted signal oscillation is transformed into a group of positive and negative differential signals, which are realized by transformer (pmdb25). Secondly, the signal is sent to the main control chip of ZYNQ series through signal acquisition chip and level conversion chip. Finally, the data is processed by software program and forwarded to the receiver. The specific experiments have been done on the 1553B signal transmission platform, which significantly show that the proposed scheme is reasonable and reliable.

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A unified leader-follower scheme for mobile robots with uncalibrated on-board camera

A unified leader-follower scheme for mobile robots with unca...

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IEEE International Conference on robotics and automation (ICRA)

作者： Dejun Guo Hesheng Wang Weidong Chen Ming Liu Zeyang Xia Kam K. Leang DARC (Design Automation Robotics & Control) Lab University of Utah Robotics Center Salt Lake City Utah USA State Key Laboratory of Robotics and System (HIT) Key Laboratory of System Control and Information Processing Ministry of Education of China Department of Automation Shanghai Jiao Tong University Shanghai China Department of Electronics and Computer Engineering Hong Kong University of Science and Technology Hong Kong China Institute of Biomedical and Health Engineering Chinese Academy of Sciences Shenzhen China

This paper studies the problem of image-based leader-follower formation control for mobile robots, where the controller is designed independently of the leader's motion. An adaptive control scheme, which is suitable for both omnidirectional and perspective cameras, is proposed. The proposed approach avoids the need for accurate calibration of the extrinsic parameters of the omnidirectional camera as well as the intrinsic and extrinsic parameters of perspective camera. Additionally, the coefficients of the plane where the feature point moves relative to the camera frame can be uncertain. These uncertain constant parameters are estimated using an adaptive estimator. Uniform Semi-global Practical Asymptotic Stability (USPAS) of the system is shown using the Lyapunov approach. Experimental results are presented to demonstrate the effectiveness of the proposed control scheme.

关键词： Cameras Robot vision systems Kinematics Mobile robots Calibration automation

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Joint calibration of panoramic camera and lidar based on supervised learning

arXiv

引用

arXiv 2017年

作者： Mingwei, Cao Ming, Yang Chunxiang, Wang Yeqiang, Qian Bing, Wang Research Institute of Robotics Shanghai Jiao Tong University Shanghai200240 China Department of Automation Shanghai Jiao Tong University 200240 China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240

In view of contemporary panoramic camera-laser scanner system, the traditional calibration method is not suitable for panoramic cameras whose imaging model is extremely nonlinear. The method based on statistical optimization has the disadvantage that the requirement of the number of laser scanner's channels is relatively high. Calibration equipments with extreme accuracy for panoramic camera-laser scanner system are costly. Facing all these in the calibration of panoramic camera-laser scanner system, a method based on supervised learning is proposed. Firstly, corresponding feature points of panoramic images and point clouds are gained to generate the training dataset by designing a round calibration object. Furthermore, the traditional calibration problem is transformed into a multiple nonlinear regression optimization problem by designing a supervised learning network with preprocessing of the panoramic imaging model. Back propagation algorithm is utilized to regress the rotation and translation matrix with high accuracy. Experimental results show that this method can quickly regress the calibration parameters and the accuracy is better than the traditional calibration method and the method based on statistical optimization. The calibration accuracy of this method is really high, and it is more highly-automated. Copyright © 2017, The Authors. All rights reserved.

关键词： Supervised learning

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Cubature Kalman Filter based point set registration for SLAM

Cubature Kalman Filter based point set registration for SLAM

引用

International Conference on Intelligent Transportation

作者： Liang Li Ming Yang Chunxiang Wang Bing Wang Department of Automation Key Laboratory of System Control and Information Processing Shanghai CN Research Institute of Robotics Shanghai Jiao Tong University Shanghai China

ISBN: (纸本)9781509018901

Point set registration is an important problem in Simultaneous Localization And Mapping (SLAM). In this paper, a novel registration algorithm based on Cubature Kalman Filter (CKF) is proposed. First, the state space model (SSM) regarding two point sets with Gaussian noise is formulated. Then CKF and simulated annealing based algorithm is utilized to optimize the process recursively. Since point set registration problem in SLAM application is mainly 3D, algorithm proposed in this paper focuses on 3D rigid point set registration problem. Compared to classical method, like Iterative Closest Point (ICP), CKF based method is more robust to noise and outliers. Besides that, this algorithm does not depend much on proper initialization which is very important to ICP. In order to explore the state space more efficiently, continuous simulated annealing is used on the process noise. Compared to Unscented Kalman Filter (UKF) based registration algorithm, this algorithm can improve precision of approximating nonlinearity in measurement update. So it will converge to the desired minimum more quickly, which is very important to SLAM considering real-time requirement. Experiments on SLAM dataset validate good performance of CKF based algorithm. The results also demonstrate the proposed method outperforms ICP and UKF based methods in the presence of noise, outliers and initial misalignment.

关键词： Mathematical model Simultaneous localization and mapping Approximation algorithms Iterative closest point algorithm Gaussian noise Kalman filters Simulated annealing

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Unknown constrained mechanisms operation based on dynamic interactive control

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CAAI Transactions on Intelligence Technology 2016年第3期1卷 259-271页

作者： Hesheng Wang Bohan Yang Weidong Chen Department of Automation Shanghai Jiao Tong University Shanghai 200240 China Key Laboratory of System Control and Information Processing Ministry of Education of China China State Key Laboratory of Robotics and System Harbin Institute of Technology (HIT) Harbin 150001 China

In order to operate various constrained mechanisms with assistive robot manipulators, an interactive control algorithm is proposed in this paper. This method decouples motion and force control in the constrained frame, and modifies the motion velocity online. Firstly, the constrained frame is determined online according to previous motion direction; then the selection matrix is adjusted dynamically, the constrained motion direction is chosen as the driving-axis. Consequently, the driving-axis and non-driving-axis are decoupled; finally, velocity control and impedance control are implied on above axes respectively. The selecting threshold for driving-axis is also varying dynamically to fit different constrained mechanism. Door-opening experiments are conducted to verify the performance of the proposed method.

关键词： Unknown constrained mechanism Selection matrix Constrained frame Robot manipulator Impedance control

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