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Large photovoltaic effect with ultrahigh open-circuit voltage in relaxor-based ferroelectric Pb(In_(1/2)Nb_(1/2))O_(3)-Pb(Mg_(1/3)Nb_(2/3))O_(3)-PbTiO_(3)ceramics

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Journal of Materials Science & technology 2022年第9期104卷 119-126页

作者： Xudong Qi Kai Li Enwei Sun Bingqian Song Da Huo Jiaming Li Xianjie Wang Rui Zhang Bin Yang Wenwu Cao Condensed Matter Science and Technology Institute School of Instrumentation Science and EngineeringHarbin Institute of TechnologyHarbin 150080China Key Laboratory for Photonic and Electronic Bandgap Materials Ministry of EducationSchool of Physics and Electronic EngineeringHarbin Normal UniversityHarbin 150025China School of Physics Harbin Institute of TechnologyHarbin 150001China Department of Mathematics and Materials Research Institute The Pennsylvania State UniversityUniversity ParkPennsylvania 16802USA

Recently,the anomalous photovoltaic effect of ferroelectric materials has attracted considerable attention in the construction of efficient solar cells owing to the above-bandgap photovoltage of these *** this study,we investigate the anomalous photovoltaic effect of relaxor-based ferroelectric Pb(In_(1/2)Nb_(1/2))O_(3)-Pb(Mg_(1/3)Nb_(2/3))O_(3)-PbTiO_(3)(PIMN-PT)ceramics with large remnant polarization and a narrow optical *** photovoltaic performance with an ultrahigh open-circuit voltage of 23 V(575 V/cm)is achieved,which is higher than the open-circuit voltages of all reported polycrystalline materials with similar *** phase structure,microstructure morphology,domain structure,ferroelectric and optical characteristics are analyzed,which could provide clues to the origin of the ultrahigh open-circuit voltage of PIMN-PT *** results suggest that the relaxor-based ferroelectric PIMNPT system is a potential candidate for photovoltaic solar energy conversion devices.

关键词： Photovoltaic Ferroelectric PIMN-PT ceramics Open-circuit voltage Domain structure

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Versatile Jumping of Humanoid Robots via Curriculum-Assisted Reinforcement Learning

Versatile Jumping of Humanoid Robots via Curriculum-Assisted...

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Chinese Automation Congress (CAC)

作者： Ruiyu Tan Xueai Li Fenglei Ni Dong Zhou Yi Ji Xiangyu Shao Key Laboratory of Autonomous Intelligent Unmanned Systems Harbin Institute of Technology Harbin China State Key Laboratory of Robotics and Systems Harbin Institute of Technology Harbin China

ISBN: (数字)9798350368604

ISBN: (纸本)9798350368611

Versatile jumping is crucial for agile and adaptive behavior of humanoid robots in complex environments. However, humanoid robots have to manage impact forces while maintaining balance and stability throughout the take-off, flight, and landing phases, which imposes significant challenges for motion planning and controller design. This paper proposes a curriculum-assisted reinforcement learning framework for the humanoid robot to achieve various jumping tasks. The curriculum learning divides the jump training process into multi-stages and design different episodes in each stage to guarantee the training feasibility and generalize learned skills. Simulations on a 28 DOFs humanoid robot verify the excellent diverse jumping capability of the proposed policy. This exploration of different tasks also proves the policy's robustness, allowing the robot quickly recover from perturbations using a variety of learned maneuvers.

关键词： Training Automation Perturbation methods Humanoid robots Reinforcement learning Robustness Stability analysis Planning

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Offline Deep Reinforcement Learning Two-stage Optimization Framework Applied to Recommendation systems 43

Offline Deep Reinforcement Learning Two-stage Optimization F...

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43rd Chinese Control Conference, CCC 2024

作者： Jiang, Yihua Liu, Qi Li, Yanjie the Harbin Institute of Technology Shenzhen Guangdong Key Laboratory of Intelligent Morphing Mechanisms and Adaptive Robotics School of Mechanical Engineering and Automation 518055 China

ISBN: (纸本)9789887581581

Most traditional recommendation systems (RS) improve the model structure to obtain valid user behavior representation and make better recommendations. However, limited by the scale of the model, the model cannot accommodate an extended range of user historical data and cannot effectively extract long-term preferences. Reinforcement learning (RL) aims to maximize the cumulative return. Introducing RL can smoothly solve the long-term and short-term profit balance. However, there are specific problems with the direct combination of the two. Training RS that relies on offline user data will cause the strategy to suffer from an overestimation of action and distribution shift. Unlike the traditional RL environment, the ample space of the RS will also cause problems of insufficient exploration and sparse rewards, making the policy more difficult to learn. In response to the above issues, this work proposes an offline RL two-stage optimization framework. The framework consists of an offline RL method based on unknown behavior to alleviate the problem of action overestimation and a two-stage feature optimization training method to reduce the impact of large spaces. Experimental results prove that the method proposed in this article can effectively improve the long-term recommendation ability of the model and more effectively improve the model performance than the general offline RL algorithm. © 2024 Technical Committee on Control Theory, Chinese Association of Automation.

关键词： Deep reinforcement learning

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NNPP: A Learning-Based Heuristic Model for Accelerating Optimal Path Planning on Uneven Terrain

arXiv

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arXiv 2023年

作者： Ji, Yiming Liu, Yang Xie, Guanghu Ma, Boyu Xie, Zongwu Cao, Baoshi State Key Laboratory of Robotics and System Harbin Institute of Technology Heilongjiang Harbin150001 China

Intelligent autonomous path planning is essential for enhancing the exploration efficiency of mobile robots operating in uneven terrains like planetary surfaces and off-road environments. In this paper, we propose the NNPP model for computing the heuristic region, enabling foundation algorithms like A* to find the optimal path solely within this reduced search space, effectively decreasing the search time. The NNPP model learns semantic information about start and goal locations, as well as map representations, from numerous pre-annotated optimal path demonstrations, and produces a probabilistic distribution over each pixel representing the likelihood of it belonging to an optimal path on the map. More specifically, the paper computes the traversal cost for each grid cell from the slope, roughness and elevation difference obtained from the digital elevation model. Subsequently, the start and goal locations are encoded using a Gaussian distribution and different location encoding parameters are analyzed for their effect on model performance. After training, the NNPP model is able to accelerate path planning on novel maps. Experiments demonstrate that the heuristic region generated by the NNPP model achieves a 3×speedup for optimal path planning under identical hardware conditions. Moreover, the NNPP model’s advantage becomes more pronounced as the size of the map increases. Copyright © 2023, The Authors. All rights reserved.

关键词： Motion planning

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Robustness and Push Recovery of Humanoid Robots Using Predictive and Whole-Body Control

Robustness and Push Recovery of Humanoid Robots Using Predic...

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IEEE International Conference on Unmanned systems (ICUS)

作者： Shaojie Zhang Fenglei Ni Xueai Li Xu Li Yi Ji Xiangyu Shao State Key Laboratory of Robotics and Systems Harbin Institute of Technology Harbin China Key Laboratory of Autonomous Intelligent Unmanned Systems Harbin Institute of Technology Harbin China

ISBN: (数字)9798350384185

ISBN: (纸本)9798350384192

Robustness walking and recovery ability in uneven terrains and unexpected collisions are crucial for the practical application of humanoid robots. However, existing methods struggle to effectively balance stability, motion safety and walking agility. This paper proposes a hybrid control strategy combing Nonlinear Model Predictive Control (NMPC) and Whole-Body Control (WBC) to improve the robot's walking stability and reaction safety in collisions situations. The NMPC generates long-term and macroscopic movements, with capture point theory being utilized for foot placements determination under external impacts. On this foundation, the WBC regulates the robot refinedly in real-time based on task priorities and weights. Simulations verify the effectiveness of the proposed method, involving uneven terrain walking and external impacts rejection.

关键词： Legged locomotion Resistance Humanoid robots Stability analysis Robustness Real-time systems Planning Collision avoidance Motion analysis Predictive control

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MDRN: Multi-distillation residual network for efficient MR image super-resolution

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Mathematical Biosciences and Engineering 2024年第10期21卷 7421-7434页

作者： Deng, Liwei Chen, Jingyi Yang, Xin Huang, Sijuan Heilongjiang Provincial Key Laboratory of Complex Intelligent System and Integration School of Automation Harbin University of Science and Technology Heilongjiang Harbin150080 China State Key Laboratory of Oncology in South China Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy Guangdong Provincial Clinical Research Center for Cancer Sun Yat-sen University Cancer Center Guangdong Guangzhou510060 China Guangdong Esophageal Cancer Institute Guangdong Guangzhou510060 China

Super-resolution (SR) of magnetic resonance imaging (MRI) is gaining increasing attention for being able to provide detailed anatomical information. However, current SR methods often use the complex convolutional network for feature extraction, which is difficult to train and not suitable for limited computation resources in the medical scenario. To tackle these bottlenecks, we propose a multidistillation residual network (MDRN) for more differential feature refinement, which has a superior trade-off between reconstruction accuracy and computation cost. Specifically, a novel feature multidistillation residual block with a contrast-aware channel attention module was designed to make the residual features more focused on low-vision information, which maximizes the power of MDRN. Comprehensive experiments demonstrate the superiority of our MDRN over state-of-the-art methods in reconstruction quality and efficiency. Our method outperforms other existing methods in peak signal-noise ratio by up to 0.44-1.82 dB in 4× scale when GPU memory and runtime are lower than in other SR methods. The source code will be available at https://***/Jennieyy/MDRN. © 2024 the Author(s).

关键词： Magnetic resonance imaging

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MECHANICAL CHARACTERISTICS ANALYSIS OF CORNER TENSIONED RECTANGULAR THIN MEMBRANES 1

MECHANICAL CHARACTERISTICS ANALYSIS OF CORNER TENSIONED RECT...

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1st International Conference on Mechanical system Dynamics, ICMSD 2022

作者： Li, Bingyan Peng, Tao Lin, Qiuhong Wang, Xiaoyu Cong, Qiang Tian, Xinqi Liu, Rongqiang Beijing Institute of Spacecraft Engineering Beijing100094 China State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin150001 China College of Mechanical and Electrical Engineering Harbin Engineering University Harbin150001 China

ISBN: (数字)9781839537837

ISBN: (纸本)9781839537837

This paper presents the calculation of the stress distribution of corner tensioned rectangular thin membrane based on the stress superposition method (SSM). By comparing with the results of finite element simulation, the theoretical results of stress distribution of tensioned membrane structure are verified. Based on SSM and free vibration calculation theory, the effects of tension boundary parameters on membrane stress distribution and models are investigated. The influence of corner tension on the mechanical characteristics is analyzed for the corner tensioned rectangular membranes with different aspect ratios. The formula for each order's fundamental frequency ratio of atmospheric to spatial environment is proposed. Conducting the dynamics experiment of a rectangular tensioned membrane, the theoretical analysis is verified by the experimental modal results. © 2022 IET Conference Proceedings. All rights reserved.

关键词： Stress concentration

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Force Distribution-Based Control Strategy of Landing Gear for the Unmanned Helicopter Landing on the Inclined Surface

Force Distribution-Based Control Strategy of Landing Gear fo...

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2022 IEEE International Conference on robotics and Biomimetics, ROBIO 2022

作者： Tian, Baolin Yu, Haitao Mao, Shihao Cui, Yuxin Yan, Zhen Gao, Haibo Harbin Institute of Technology State Key Laboratory of Robotics and System Harbin China College of Electronic Information Engineering Beihang University and the Shanghai Academy of Spaceflight Technology Shanghai China

ISBN: (纸本)9781665481090

The unmanned helicopter plays an important role in the fields of cargo transportation and rescue missions. Due to the limitation of the traditional landing gear structure, the unmanned helicopter has more stringent requirements on the landing terrain. In order to improve the ability to land on the inclined surface for the unmanned helicopter, a novel control strategy of the landing gear based on contact force distribution algorithm is proposed. The overall of landing process includes the desired position tracking stage, the following stage and the attitude adjusting stage. By obtaining the desired acceleration according to the landing and attitude correcting curve of the fuselage, and calculating the desired force based on contact force distribution algorithm, the adaptive motion and trajectory tracking of the landing gear during the landing process has been realized. The simulation results have demonstrated the effectiveness of the strategy when the unmanned helicopter with the initial roll angle of -3 degrees and pitch angle of 3 degrees lands on the inclined surface of 7.07 degrees. In the future, the control strategy can provide a reference for the dynamic landing of the unmanned helicopter while at sea. © 2022 IEEE.

关键词： Acceleration

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Tuning interfacial charge transfer for efficient visible-light-driven photodegradation and simultaneous H_(2)evolution

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Journal of Materials Science & technology 2024年第1期168卷 35-49页

作者： Zhiyang Li Yaogang Chen Yinghe Zhang Wei Ai Qian Lei Tingjun Yao Dan Zhong Wenjie Liu Wenbiao Jin Lei Yang State Key Laboratory of Urban Water Resource and Environment Shenzhen Key Laboratory of Organic Pollution Prevention and ControlSchool of Civil and Environmental EngineeringHarbin Institute of Technology ShenzhenShenzhen 518055China Key Laboratory of Northwest Water Resources Environment and EcologyMinistry of EducationSchool of Environmental and Municipal EngineeringXi’an University of Architecture and TechnologyXi’an 710055China CNAS Accredited Test Center Guangdong Engineering Technology Research Center of Air PurificationHealthlead Co.Ltd.Shenzhen 518055China School of Science Harbin Institute of Technology ShenzhenShenzhen 518055China

The edge-graphitized carbon nitride(C_(3)N_(4)-C g)was prepared by secondary pyrolysis to construct ZnO/C_(3)N_(4)-C g(ZCN)type-Ⅱheterojunction photocatalyst via a facile sonication dispersion method,which achieved∼7.04-fold and∼18.3-fold enhanced visible-light-driven photocatalytic performance for refrac-tory micropollutant removal and simultaneous hydrogen(H_(2))evolution respectively compared to con-ventional ZnO/g-C_(3)N_(4)Step-scheme *** apparent quantum efficiency of the ZCN_(0.4)het-erojunction reaches 0.92%(λ=420 nm).Such excellent performance stems from that the edge-graphene moieties stitched onto the interface of heterojunction extend light absorption to the full visible spec-trum,meanwhile,the built-in electric field generated during Fermi level alignment accompanying fa-vorable band-bending structure provides an effective pathway for the rapid migration of photoinduced electrons via the edge graphene channel to improve interfacial charge separation ***,the midgap states introduced in ZCN heterojunction could temporarily retain photoexcited electrons to effectively inhibit the in situ carrier recombination for improved photocatalytic H_(2)***,ZCN/peroxymonosulfate system exhibited excellent anti-interference performance against complex water bodies under visible illumination due to the synergistic effect between the co-existing anions and organic ***,the eco-friendly nature of the ZCN/peroxymonosulfate system showed no biotoxicity of reaction filtrate on cell proliferation after treatment,which avoided secondary ***-ering the outstanding performance in photocatalysis,the ZCN system exhibits broad potential for practical applications in water pollution control and green energy production.

关键词： ZnO C_(3)N_(4)-C g Heterojunction Photodegradation Hydrogen evolution

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Inverse Kinematics of a Reconfigurable Space Manipulator Based on the Closed-Loop Algorithm

Inverse Kinematics of a Reconfigurable Space Manipulator Bas...

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IEEE International Conference on Mechatronics and Automation

作者： Zhiyuan Zhao Xiaohang Yang Zichun Xu Yuntao Li Zhonglai Tian Jingdong Zhao State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin Heilongjiang Province China

This paper investigates a reconfigurable space manipulator’s inverse kinematics (IK) with two lockable passive telescopic links (LPTLs). Depending on these LPTLs’ locking state, the manipulator includes free-space and reconfiguration operation modes. Firstly, we introduce a new ball joint-based solution for the reconfigurable operation mode. Then, we propose an IK simplified method capable of significantly reducing the computational load of the complex inverse differential kinematic (IDK) equations corresponding to the two operation modes. Next, to solve the resulting simplified IDK equations efficiently, we present an IK solution method based on the closed-loop algorithm. This method is developed to resolve the redundancy at the velocity level and can generate highly accurate and smooth trajectory IK solutions that satisfy the joint limit constraints. Finally, we design two typical case studies corresponding to working scenarios of the manipulator during two operation modes. Their simulation results validate the proposed methods’ effectiveness.

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