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Effects of fluorene-9-bisphenol exposure on anxiety-like and social behavior in mice and protective potential of exogenous melatonin

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Environmental Science and Pollution Research 2024年第20期31卷 29385-29399页

作者： Zuo, Xiang Zhang, Shuhui Bai, Huijuan Yu, Qian Zhao, Qili Sun, Mingzhu Zhao, Xin Feng, Xizeng College of Life Sciences State Key Laboratory of Medicinal Chemical Biology Key Laboratory of Bioactive Materials Ministry of Education Nankai University Weijin Road 94 Tianjin300071 China Institute of Robotics & amp Automatic Information System College of Artificial Intelligence Nankai University Tianjin300071 China

Fluorene-9-bisphenol (BHPF) is widely used in the manufacture of plastic products and potentially disrupts several physiological processes, but its biological effects on social behavior remain unknown. In this study, we investigated the effects of BHPF exposure on anxiety-like and social behavior in female mice and the potential mechanisms, thereby proposing a potential therapy strategy. We exposed female Balb/c mice to BHPF by oral gavage at different doses (0.5, 50 mg/kg bw/2-day) for 28 days, which were found BHPF (50 mg/kg) exposure affected motor activity in the open field test (OFT) and elevated cross maze (EPM), resulting in anxiety-like behaviors, as well as abnormal social behavioral deficits in the Social Interaction Test (SIT). Analysis of histopathological staining results showed that BHPF exposure caused damage to hippocampal neurons in the CA1/CA3/DG region and decreased Nissl pyramidal neurons in the CA1/CA3 regions of the hippocampus, as well as a decrease in parvalbumin neuron expression. In addition, BHPF exposure upregulated the expression of excitatory and inhibitory (E/I) vesicle transporter genes (Vglut1, Vglut2, VGAT, GAD67, Gabra) and axon growth gene (Dcc) in the mouse hippocampus. Interestingly, behavioral disturbances and E/I balance could be alleviated by exogenous melatonin (15 mg/kg bw/2-day) therapy. Our findings suggest that exogenous melatonin may be a potential therapy with protective potential for ameliorating or preventing BHPF-induced hippocampal neuronal damage and behavioral disturbances. This study provided new insight into the neurotoxicological effects on organisms exposed to endocrine-disrupting chemicals and aroused our vigilance in current environmental safety about chemical use. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.

关键词： Neurons

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A Novel Gait Pattern Recognition Method Based on LSTM-CNN for Lower Limb Exoskeleton

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Journal of Bionic Engineering 2021年第5期18卷 1059-1072页

作者： Chao-feng Chen Zhi-jiang Du Long He Yong-jun Shi Jia-qi Wang Wei Dong State Key Laboratory of Robotics and System Harbin Institute of Technology(HIT)Harbin 150001China China South Industries Group Corporation Weapon Equipment Research InstituteBeijing 102202China

This paper describes a novel gait pattern recognition method based on Long Short-Term Memory(LSTM)and Convolutional Neural Network(CNN)for lower limb *** Inertial Measurement Unit(IMU)installed on the exoskeleton to collect motion information,which is used for LSTM-CNN *** article considers five common gait patterns,including walking,going up stairs,going down stairs,sitting down,and standing *** the LSTM-CNN model,the LSTM layer is used to process temporal sequences and the CNN layer is used to extract *** optimize the deep neural network structure proposed in this paper,some hyperparameter selection experiments were carried *** addition,to verify the superiority of the proposed recognition method,the method is compared with several common methods such as LSTM,CNN and *** results show that the average recognition accuracy can reach 97.78%,which has a good recognition eff ***,according to the experimental results of gait pattern switching,the proposed method can identify the switching gait pattern in time,which shows that it has good real-time performance.

关键词： Lower limb exoskeleton Gait pattern recognition LSTM-CNN Recognition accuracy Real-time performance

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Trajectory planning and base attitude restoration of dual-arm free-floating space robot by enhanced bidirectional approach

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Frontiers of Mechanical Engineering 2022年第1期17卷 2-17页

作者： Zongwu XIE Xiaoyu ZHAO Zainan JIANG Haitao YANG Chongyang LI State Key Laboratory of Robotics and System Harbin Institute of TechnologyHarbin 150001China Robotic System Department Jiangsu Jitri-Hust Intelligent Equipment TechnologyWuxi 214000China

When free-floating space robots perform space tasks,the satellite base attitude is disturbed by the dynamic *** disturbance of the base orientation may affect the communication between the space robot and the control center on *** this paper,the enhanced bidirectional approach is proposed to plan the manipulator trajectory and eliminate the final base attitude variation.A novel acceleration level state equation for the nonholonomic problem is proposed,and a new intermediate variable-based Lyapunov function is derived and solved for smooth joint trajectory and restorable base *** the method,the state equation is first proposed for dual-arm robots with and without end constraints,and the system stability is analyzed to obtain the system *** input modification further increases the system stability and simplifies the calculation *** are carried out in the end,and the proposed method is validated in minimizing final base attitude change and trajectory ***,the minute internal force during the coordinated operation and the considerable computing efficiency increases the feasibility of the method during space tasks.

关键词： free-floating space robot dual arm coordinated operation base attitude restoration bidirectional approach

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PMM-Net: Single-Stage Multi-Agent Trajectory Prediction with Patching-Based Embedding and Explicit Modal Modulation

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IEEE robotics and Automation Letters 2025年第7期10卷 6664-6671页

作者： Huajian, Liu Wei, Dong Kunpeng, Fan Chao, Wang Yongzhuo, Gao Harbin Institute of Technology State Key Laboratory of Robotics and System Harbin150001 China

Analyzing and forecasting trajectories of agents like pedestrians plays a pivotal role for embodied intelligent applications. The inherent indeterminacy of human behavior and complex social interaction among a rich variety of agents makes this task more challenging than common time-series forecasting. In this letter, we aim to explore a distinct formulation for multi-agent trajectory prediction framework. Specifically, we propose a patching-based temporal feature extraction module and a graph-based social feature extraction module, enabling effective feature extraction and cross-scenario generalization. Moreover, we reassess the role of social interaction and present a novel method based on explicit modality modulation to integrate temporal and social features, thereby constructing an efficient single-stage inference pipeline. Results on public benchmark datasets demonstrate the superior performance of our model compared with the state-of-the-art methods. © 2025 IEEE.

关键词： Signal modulation

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An adaptive Kalman filter for physiological tremor suppression in robot-assisted minimally invasive surgery

An adaptive Kalman filter for physiological tremor suppressi...

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2023 IEEE International Conference on robotics and Biomimetics, ROBIO 2023

作者： Yang, Daolong Jiang, Li Xu, Kun Robotics Institute of School of Mechanical Engineering and Automation Beijing100191 China Harbin Institute of Technology State Key Laboratory of Robotics and System Harbin150008 China

ISBN: (纸本)9798350325706

Physiological tremors of surgeons' hands bring vibration to the tip of surgical instruments, which may severely damage the accuracy of surgical procedures and even put patients' lives at risk. Thus robot-assisted surgery using a teleoperation system was introduced to solve this problem. Many filter algorithms were implemented into the robot-assisted surgery system to suppress the inevitable tremors, but always overlooking the traits of hand motion. An innovation/residual-based floating forgetting-factor adaptive Kalman filter (IFFAKF) is proposed to address this problem. A floating forgetting-factor is brought into the innovation/residual-based adaptive estimation algorithm to adjust the process noise covariance (Q) and measurement noise covariance (R) of the system, thus generating estimation of voluntary hand movement and suppressing the vibration at the tip of the surgical instrument caused by the physiological tremor during surgeries. The proposed filter has been contrasted with various filters in simulations and experiments. The results confirm that the proposed filter has obvious advantages in terms of time delay, estimation error, and tremor suppression performance. © 2023 IEEE.

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Design and Control of Continuous Jumping Gaits for Humanoid Robots Based on Motion Function and Reinforcement Learning

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Procedia Computer Science 2024年 250卷 51-57页

作者： Zida Zhao Shilong Sun Haodong Huang Qingbin Gao Wenfu Xu State Key Laboratory of Robotics and System (HIT) Harbin Institute of Technology Harbin Heilongjiang China School of Mechanical Engineering and Automation Harbin Institute of Technology Shenzhen 518055 China

Continuous jumping of humanoid robots is a challenging problem that requires appropriate gait and force control for the robot to achieve. Reinforcement learning (RL) has been applied to the motion control of humanoid robots and has achieved significant progress. However, traditional RL control methods primarily rely on designing reward signals to generate human-like movements, and it requires developing complex reward signals for continuous jumping, resulting in limited actions and suboptimal jumping performance. To address this issue, we have designed motion functions for humanoid continuous jumping and incorporated them into the RL framework to obtain desired human-like continuous jumping actions. Furthermore, two different jumping gaits are designed to investigate the jumping effects produced by different jumping functions: bent-knee jumping (BJ) and straight-knee jumping (SJ). BJ is a typical jumping style where the legs flex during the jumping process to accumulate energy, enabling higher explosive power. SJ is more suitable for tasks requiring quick responses, as the legs remain upright during the jump, providing faster reaction speed. The performance in continuous jumping tasks has been evaluated by comparing the effects of training with different jumping functions. This research has particular guidance for improving the jumping ability of robots and enhancing the stability and efficiency of humanoid continuous jumping.

关键词： Continuous jumping gaits Humanoid robots Motion function Reinforcement learning

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A Unified Trajectory Optimization Approach for Long-Term and Reactive Motion Planning of Legged Locomotion

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Journal of Bionic Engineering 2023年第5期20卷 2108-2122页

作者： Yapeng Shi Bin Yu Kaixian Ba Mantian Li School of Mechanical Engineering Yanshan UniversityNo.438 West Hebei AvenueQinhuangdao066004HebeiPeople’s Republic of China State Key Laboratory of Robotics and System Harbin Institute of TechnologyHarbin150001People’s Republic of China

This paper proposes a unified trajectory optimization approach that simultaneously optimizes the trajectory of the center of mass and footholds for legged *** on a generic point-mass model,the approach is formulated as a nonlinear optimization problem,incorporating constraints such as robot kinematics,dynamics,ground reaction forces,obstacles,and target *** unified optimization approach can be applied to both long-term motion planning and the reactive online planning through the use of model predictive control,and it incorporates vector field guidance to converge to the long-term planned *** effectiveness of the approach is demonstrated through simulations and physical experiments,showing its ability to generate a variety of walking and jumping gaits,as well as transitions between them,and to perform reactive walking in obstructed environments.

关键词： Legged locomotion Motion planning Trajectory optimization Bionic robot

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Mechanical design and analysis of a novel variable stiffness actuator with symmetrical pivot adjustment

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Frontiers of Mechanical Engineering 2021年第4期16卷 711-725页

作者： Yiwei LIU Shipeng CUI Yongjun SUN State Key Laboratory of Robotics and System Harbin Institute of TechnologyHarbin 150001China

The safety of human-robot interaction is an essential requirement for designing collaborative ***,this paper aims to design a novel variable stiffiiess actuator(VSA)that can provide safer physical human-robot interaction for collaborative *** A follows the idea of modular design,mainly including a variable stiffiiess module and a drive *** variable stiffiiess module transmits the motion from the drive module in a roundabout maimer,making the modularization of VS A *** the key component of the variable stiffiiess module,a stiffness adjustment mechanism with a symmetrical structure is applied to change the positions of a pair of pivots in two levers linearly and simultaneously,which can eliminate the additional bending moment caused by the asymmetric *** design of the doubledeck grooves in the lever allows the pivot to move freely in the groove,avoiding the geometric constraint between the ***,the VSA stiffiiess can change from zero to infinity as the pivot moves from one end of the groove to the *** facilitate building a manipulator in the future,an expandable electrical system with a distributed structure is also *** calibration and control experiments are performed to evaluate the physical performance of the designed *** results show that the VSA stiffiiess is close to the theoretical design ***,the VSA with a proportional-derivative feedback plus feedforward controller exhibits a fast response for stiffiiess regulation and a good performance for position tracking.

关键词： variable stiffiiess actuator variable stiffness module drive module symmetrical structure doubledeck grooves expandable electrical system

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An Autonomous Obstacle Avoidance Path Planning Method Involving PSO for Dual-Arm Surgical Robot 5

An Autonomous Obstacle Avoidance Path Planning Method Involv...

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5th International Conference on Mechatronics, robotics and Automation, ICMRA 2022

作者： Chen, Qiao Liu, Yiwei Chen, Zhuo Zhou, Yangjunjian Harbin Institute of Technology State Key Laboratory of Robotics and System Harbin China

ISBN: (纸本)9781665472654

Currently, motion planning and reasonable obstacle avoidance of surgical robots are essential research directions. Most surgical robots adopt a simple master-slave control strategy and cannot avoid obstacles autonomously. To this end, we propose an autonomous obstacle avoidance method for the dual-arm surgical robot. Firstly, the obstacle avoidance path planning is based on the artificial potential field method. We propose the splicing algorithm to make the manipulator jump out of the local minimum and improve the planning efficiency. And using the adaptive step to stable motion. Secondly, for collision detection, we use the Gilbert-Johnson-Keerthi (GJK) algorithm to calculate the distance between the obstacle and the equivalent convex body of the manipulator. A warning appears when there is a collision. Because the artificial potential field method lacks time planning, we use the time-optimized 3-5-3 polynomial interpolation based on the Particle Swarm optimization (PSO) to the obtained path. And make manipulators perform the surgery without collision for a suitable period. Finally, we carry out the system simulation, physical experiments, and dual-arm obstacle avoidance experiments based on the above autonomous obstacle avoidance algorithm. Experiments show that this study can make the dual-arm surgical robot move quickly and smoothly on the premise of avoiding obstacles, which provides a reference for the automation of surgical robots. © 2022 IEEE.

关键词： Motion planning

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Integral Real-time Locomotion Mode Recognition Based on GA-CNN for Lower Limb Exoskeleton

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Journal of Bionic Engineering 2022年第5期19卷 1359-1373页

作者： Jiaqi Wang Dongmei Wu Yongzhuo Gao Xinrui Wang Xiaoqi Li Guoqiang Xu Wei Dong State Key Laboratory of Robotics and System Harbin Institute of TechnologyHarbin 150001China Weapon Equipment Research Institute China South Industries Group CorporationBeijing 102202China

The wearable lower limb exoskeleton is a typical human-in-loop human–robot coupled system,which conducts natural and close cooperation with the human by recognizing human locomotion *** subject-specific training is the main challenge of the existing approaches,and most methods have the problem of insufficient *** paper proposes an integral subject-adaptive real-time Locomotion Mode Recognition(LMR)method based on GA-CNN for a lower limb exoskeleton *** LMR method is a combination of Convolutional Neural Networks(CNN)and Genetic Algorithm(GA)-based multi-sensor information *** improve network performance,the hyper-parameters are optimized by Bayesian *** exoskeleton prototype system with multi-type sensors and novel sensing-shoes is used to verify the proposed *** locomotion modes,which composed an integral locomotion system for the daily application of the exoskeleton,can be recognized by the proposed *** to a series of experiments,the recognizer shows strong comprehensive abilities including high accuracy,low delay,and sufficient adaption to different subjects.

关键词： Locomotion mode recognition Gait mode detection Lower limb exoskeleton Convolutional neural network Genetic algorithm Bionic design

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