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Deep Domain Adaptation Regression for Force Calibration of Optical Tactile Sensors

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Deep Domain Adaptation Regression for Force Calibration of O...

IEEE/RSJ International Conference on intelligent Robots and systems (IROS)

作者： Zhuo Chen Ni Ou Jiaqi Jiang Shan Luo Department of Engineering Robot Perception Lab Centre for Robotics Research King’s College London London United Kingdom State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology Beijing China

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

Optical tactile sensors provide robots with rich force information for robot grasping in unstructured environments. The fast and accurate calibration of three-dimensional contact forces holds significance for new sensors and existing tactile sensors which may have incurred damage or aging. However, the conventional neural-network-based force calibration method necessitates a large volume of force-labeled tactile images to minimize force prediction errors, with the need for accurate Force/Torque measurement tools as well as a time-consuming data collection process. To address this challenge, we propose a novel deep domain-adaptation force calibration method, designed to transfer the force prediction ability from a calibrated optical tactile sensor to uncalibrated ones with various combinations of domain gaps, including marker presence, illumination condition, and elastomer modulus. Experimental results show the effectiveness of the proposed unsupervised force calibration method, with lowest force prediction errors of 0.102N (3.4% in full force range) for normal force, and 0.095N (6.3%) and 0.062N (4.1%) for shear forces along the x-axis and y-axis, respectively. This study presents a promising, general force calibration methodology for optical tactile sensors.

关键词： Accuracy Force Tactile sensors Lighting Elastomers Data collection Optical imaging Adaptive optics Calibration Optical sensors

Pre-Training to Learn in Context

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arXiv 2023年

作者： Gu, Yuxian Dong, Li Wei, Furu Huang, Minlie The CoAI Group DCST Institute for Artificial Intelligence State Key Lab of Intelligent Technology and Systems Beijing National Research Center for Information Science and Technology Tsinghua University Beijing100084 China Microsoft Research

In-context learning, where pre-trained language models learn to perform tasks from task examples and instructions in their contexts, has attracted much attention in the NLP community. However, the ability of in-context learning is not fully exploited because language models are not explicitly trained to learn in context. To this end, we propose PICL (Pre-training for In-Context Learning), a framework to enhance the language models' in-context learning ability by pre-training the model on a large collection of "intrinsic tasks" in the general plain-text corpus using the simple language modeling objective. PICL encourages the model to infer and perform tasks by conditioning on the contexts while maintaining task generalization of pre-trained models. We evaluate the in-context learning performance of the model trained with PICL on seven widely-used text classification datasets and the SUPERNATURALINSTRCTIONS benchmark, which contains 100+ NLP tasks formulated to text generation. Our experiments show that PICL is more effective and task-generalizable than a range of baselines, outperforming larger language models with nearly 4x parameters. The code is publicly available at https://***/thu-coai/PICL. © 2023, CC BY.

关键词： Natural language processing systems

Electromagnetic Property Sensing and Channel Reconstruction Based on Diffusion Schrödinger Bridge in ISAC

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arXiv 2024年

作者： Jiang, Yuhua Gao, Feifei Jin, Shi State Key Lab of Intelligent Technologies and Systems Tsinghua University Beijing National Research Center for Information Science and Technology [BNRist Beijing China The National Mobile Communications Research Laboratory Southeast University Nanjing210096 China

Integrated sensing and communications (ISAC) has emerged as a transformative paradigm for next-generation wireless systems. In this paper, we present a novel ISAC scheme that leverages the diffusion Schrödinger bridge (DSB) to realize the sensing of electromagnetic (EM) property of a target as well as the reconstruction of the wireless channel. The DSB framework connects EM property sensing and channel reconstruction by establishing a bidirectional process: the forward process transforms the distribution of EM property into the channel distribution, while the reverse process reconstructs the EM property from the channel. To handle the difference in dimensionality between the high-dimensional sensing channel and the lower-dimensional EM property, we generate latent representations using an autoencoder network. The autoencoder compresses the sensing channel into a latent space that retains essential features, which incorporates positional embeddings to process spatial context. The simulation results demonstrate the effectiveness of the proposed DSB framework, which achieves superior reconstruction of the targets shape, relative permittivity, and conductivity. Moreover, the proposed method can also realize high-fidelity channel reconstruction given the EM property of the target. The dual capability of accurately sensing the EM property and reconstructing the channel across various positions within the sensing area underscores the versatility and potential of the proposed approach for broad application in future ISAC systems. Copyright © 2024, The Authors. All rights reserved.

关键词： Signal reconstruction

DA-Ada: Learning Domain-Aware Adapter for Domain Adaptive Object Detection

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arXiv 2024年

作者： Li, Haochen Zhang, Rui Yao, Hantao Zhang, Xin Hao, Yifan Song, Xinkai Li, Xiaqing Zhao, Yongwei Li, Ling Chen, Yunji Intelligent Software Research Center Institute of Software CAS Beijing China State Key Lab of Processors Institute of Computing Technology CAS Beijing China State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation CAS Beijing China University of Chinese Academy of Sciences Beijing China

Domain adaptive object detection (DAOD) aims to generalize detectors trained on an annotated source domain to an unlabelled target domain. As the visual-language models (VLMs) can provide essential general knowledge on unseen images, freezing the visual encoder and inserting a domain-agnostic adapter can learn domain-invariant knowledge for DAOD. However, the domain-agnostic adapter is inevitably biased to the source domain. It discards some beneficial knowledge discriminative on the unlabelled domain, ***-specific knowledge of the target domain. To solve the issue, we propose a novel Domain-Aware Adapter (DA-Ada) tailored for the DAOD task. The key point is exploiting domain-specific knowledge between the essential general knowledge and domain-invariant knowledge. DA-Ada consists of the Domain-Invariant Adapter (DIA) for learning domain-invariant knowledge and the Domain-Specific Adapter (DSA) for injecting the domain-specific knowledge from the information discarded by the visual encoder. Comprehensive experiments over multiple DAOD tasks show that DA-Ada can efficiently infer a domain-aware visual encoder for boosting domain adaptive object detection. Our code is available at https://***/Therock90421/DA-Ada © 2024, CC BY-NC-SA.

关键词： Ada (programming language)

High responsivity and flexible deep-UV phototransistor based on Ta-doped β-Ga_(2)O_(3)

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npj Flexible Electronics 2022年第1期6卷 457-465页

作者： Xiao-Xi Li Guang Zeng Yu-Chun Li Hao Zhang Zhi-Gang Ji Ying-Guo Yang Man Luo Wei-Da Hu David Wei Zhang Hong-Liang Lu State Key Laboratory of ASIC and System Shanghai Institute of Intelligent Electronics&SystemsSchool of MicroelectronicsFudan University200433 ShanghaiChina National Key Laboratory of Science and Technology on Micro/Nano Fabrication Shanghai Jiao Tong University200240 ShanghaiChina Shanghai Synchrotron Radiation Facility(SSRF) Zhangjiang LabShanghai Advanced Research Institute&Shanghai Institute of Applied PhysicsChinese Academy of Sciences201204 ShanghaiChina State Key Laboratory of Infrared Physics Shanghai Institute of Technical PhysicsChinese Academy of Sciences200083 ShanghaiChina

Deep-ultraviolet(DUV)phototransistors have shown great potential applications in UV imaging,artificial intelligence,and wearable *** a large number of wide bandgap semiconductors,the quasi-two-dimensionalβ-Ga_(2)O_(3) is considered as an ideal candidate for DUV photodetector ***,we report a high responsivity(R)and fully flexible Ta-dopedβ-Ga_(2)O_(3) DUV phototransistor which exhibits outstanding optoelectrical properties with a high R of 1.32×10^(6) A/W,a large detectivity of 5.68×10^(14) Jones,a great photo-to-dark current ratio of 1.10×10^(10)%,a high external quantum efficiency of 6.60×10^(8)%,and an ultra-fast response time of~3.50 ***,the flexible Ta-dopedβ-Ga_(2)O_(3) device also displays high reliability and mechanical flexibility that can sustain well after over 1×10^(4) bending ***,high-contrast imaging of UV light was obtained on the flexible DUV detector arrays,which can be efficiently trained and recognized by an artificial neural *** findings offer a perspective to develop wearable optoelectronics and UV imaging based on high-performance flexibleβ-Ga_(2)O_(3) DUV phototransistors,providing an inspiration for the future work in artificial intelligence and bionic robot fields.

关键词： transistor responsivity artificial

DecompEval: Evaluating Generated Texts as Unsupervised Decomposed Question Answering

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arXiv 2023年

作者： Ke, Pei Huang, Fei Mi, Fei Wang, Yasheng Liu, Qun Zhu, Xiaoyan Huang, Minlie The CoAI Group DCST Institute for Artificial Intelligence State Key Lab of Intelligent Technology and Systems Beijing National Research Center for Information Science and Technology Tsinghua University Beijing100084 China Huawei Noah’s Ark Lab China

Existing evaluation metrics for natural language generation (NLG) tasks face the challenges on generalization ability and interpretability. Specifically, most of the well-performed metrics are required to train on evaluation datasets of specific NLG tasks and evaluation dimensions, which may cause over-fitting to task-specific datasets. Furthermore, existing metrics only provide an evaluation score for each dimension without revealing the evidence to interpret how this score is obtained. To deal with these challenges, we propose a simple yet effective metric called DecompEval. This metric formulates NLG evaluation as an instruction-style question answering task and utilizes instruction-tuned pre-trained language models (PLMs) without training on evaluation datasets, aiming to enhance the generalization ability. To make the evaluation process more interpretable, we decompose our devised instruction-style question about the quality of generated texts into the subquestions that measure the quality of each sentence. The subquestions with their answers generated by PLMs are then recomposed as evidence to obtain the evaluation result. Experimental results show that DecompEval achieves state-of-the-art performance in untrained metrics for evaluating text summarization and dialogue generation, which also exhibits strong dimension-level / task-level generalization ability and interpretability1 Copyright © 2023, The Authors. All rights reserved.

关键词： Quality control

A Novel Parameter-dependent Input Normalization-based Direct MRAC with Unknown Control Direction

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A Novel Parameter-dependent Input Normalization-based Direct...

IEEE Conference on Decision and Control

作者： Yizhou Gong Gilberto Pin Yanjun Zhang Yang Wang School of Information Science and Technology ShanghaiTech University Shanghai China Digital Technology Org. of Electrolux Italia S.p.A. Italy School of Automation Beijing Institute of Technology Beijing China State Key Lab of Automation Intelligent Unmanned Systems Beijing Institute of Technology Beijing China

ISBN: (数字)9798350316339

ISBN: (纸本)9798350316346

In this paper, we endow the model reference adaptive control (MRAC) with a novel parameter-dependent input normalization (PIN) to completely eliminate the conventional assumption of the high-frequency gain. Specifically, neither the sign nor the prior knowledge of the upper or lower bounds is required. To this end, we resort to an error augmentation together with a smart design of an adaptive law with a dead zone operation. Global stability in the mean square sense is established with the conventional proof concepts of the augmented error approach. In this way, no persistent excitation requirement is required. Although the system in question is assumed to be unity-relative-degree, the proposed technique can be easily extended to systems of arbitrary relative degrees. Finally, compared with the Nussbaum function-based methods in a numerical experiment, we show that transient behavior in our method is significantly improved.

关键词： Hands Lower bound Upper bound Simulation Stability analysis Robustness Pins Transient analysis Numerical stability Oscillators

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热扩散系统中非厄米趋肤效应的观测

Science Bulletin 2024年第9期69卷 1228-1236页

作者：刘云开曹培超祁铭鸿黄强开来高峰彭玉桂李鹰祝雪丰 School of Physics and Innovation Institute Huazhong University of Science and TechnologyWuhan 430074China State Key Laboratory of Extreme Photonics and Instrumentation ZJU-Hangzhou Global Scientiﬁc and Technological Innovation CenterZhejiang UniversityHangzhou 310027China International Joint Innovation Center The Electromagnetics Academy at Zhejiang UniversityZhejiang UniversityHaining 314400China Key Lab.of Advanced Micro/Nano Electronic Devices&Smart Systems of Zhejiang Jinhua Institute of Zhejiang UniversityZhejiang UniversityJinhua 321099China Shaoxing Institute of Zhejiang University Zhejiang UniversityShaoxing 312000China

The paradigm shift of Hermitian systems into the non-Hermitian regime profoundly modifies inherent property of the topological systems, leading to various unprecedented effects such as the nonHermitian skin effect(NHSE). In the past decade, the NHSE has been demonstrated in quantum, optical and acoustic systems. Beside those wave systems, the NHSE in diffusive systems has not yet been observed, despite recent abundant advances in the study of topological thermal diffusion. In this work,we design a thermal diffusion lattice based on a modified Su-Schrieffer-Heeger model and demonstrate the diffusive NHSE. In the proposed model, the asymmetric temperature field coupling inside each unit cell can be judiciously realized by appropriate configurations of structural parameters. We find that the temperature fields trend to concentrate toward the target boundary which is robust against initial excitation conditions. We thus experimentally demonstrated the NHSE in thermal diffusion and verified its robustness against various defects. Our work provides a platform for exploration of non-Hermitian physics in the diffusive systems, which has important applications in efficient heat collection, highly sensitive thermal sensing and others.

关键词： Non-Hermitian skin effect Asymmetric coupling Thermal metamaterial Heat diffusion

Gait Planning and Motion Control Based on Vrep Simulation for Quadruped Robot

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Gait Planning and Motion Control Based on Vrep Simulation fo...

WRC Symposium on Advanced Robotics and Automation (WRC SARA)

作者： Linqi Zhou Zhihua Chen Jun Liu Zhi Liu Yumeng Chen Liting Zhang key Laboratory of Jiangxi Province for Image Processing and Pattern Recognition and MOE Key Lab of Nondestructive Testing Technology Nanchang Hangkong University Nanchang China State Key Laboratory of Intelligent Control and Decision of Complex Systems School of Automation Beijing Institute of Technology Beijing China

Gait planning of quadruped robots plays an important role in achieving less walking, including dynamic and static gait. In this article, a static and dynamic gait control method based on center of gravity stability margin is proposed. Firstly, the robot model and kinematics modeling are introduced. Secondly, the robot’s foot static and dynamic gait were planned and the foot trajectory was designed. Finally, two types of gait of the robot were simulated using Vrep simulation software, and the differences in stability and speed between the coordinated gait with speed and stability in the static and dynamic gait of a 12 degree of freedom robot were analyzed, verifying the effectiveness of the gait control method proposed in this paper.

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