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

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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Full Resolution Repetition Counting 16th

Full Resolution Repetition Counting

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16th International Conference on Intelligent robotics and Applications, ICIRA 2023

作者： Li, Jianing Chen, Bowen Wang, Zhiyong Liu, Honghai School of Mechanical Engineering and Automation Harbin Institute of Technology Shenzhen China State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin China

ISBN: (纸本)9789819964826

Given an untrimmed video, repetitive actions counting aims to estimate the number of repetitions of class-agnostic actions. To handle the various length of videos and repetitive actions, also optimization challenges in end-to-end video model training, down-sampling is commonly utilized in recent state-of-the-art methods, leading to ignorance of several repetitive samples. In this paper, we attempt to understand repetitive actions from a full temporal resolution view, by combining offline feature extraction and temporal convolution networks. The former step enables us to train repetition counting network without down-sampling while preserving all repetitions regardless of the video length and action frequency, and the later network models all frames in a flexible and dynamically expanding temporal receptive field to retrieve all repetitions with a global aspect. Besides, temporal self-similarity matrix is used in our model to represent the correlation of action, which contains much cycle information in time series. We experimentally demonstrate that our method achieves better or comparable performance in three public datasets, i.e., TransRAC, UCFRep and QUVA. We expect this work will encourage our community to think about the importance of full temporal resolution. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Convolution

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S2H-GNN: Learning Soft to Hard Feature Matching with Sparsified Graph Neural Network

S2H-GNN: Learning Soft to Hard Feature Matching with Sparsif...

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2023 IEEE International Conference on Real-Time Computing and robotics, RCAR 2023

作者： Xie, Tao Li, Ruifeng Jiang, Zhiqiang Dai, Kun Wang, Ke Zhao, Lijun Li, Shuozhan Harbin Institute of Technology State Key Laboratory of Robotics and System Harbin150006 China -HIT Research Institute of Engineering and Technology Quanzhou China

ISBN: (纸本)9798350327182

In this work, we introduce a soft-to-hard network (S2H-GNN) for precise local feature matching between image pairs. The core of S2H-GNN is a weighted context aggregation algorithm that enables nodes to receive information from their neighbors in order to form a more global understanding. S2HGNN leverages a sparsified graph neural network to enhance the features, consisting of the following modules alternately: (1) Inducing Point Initial Module that uses cosine correlation to identify highly scored keypoints as Inducing points. (2) Message Passing Module that integrates the features of original keypoints into those of Inducing points, which are further leveraged to exchange messages through self attention and cross attention. (3) Attention Upsample Module that propagates the feature of Inducing points to that of original keypoints, obtaining discriminative feature representation. Additionally, we propose an assignment layer to obtain a soft assignment matrix, which views feature matching as a graphy matching problem. Finally, we introduce a novel gap loss to guide S2H-GNN in learning a discriminative cognition of matching and non-matching keypoints, ultimately obtaining the hard assignment matrix. Experimental results demonstrate that S2H-GNN achieves comparable or higher performance in image matching and homography estimation tasks. © 2023 IEEE.

关键词： Graph neural networks

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A Real-Time Hardware-Accelerator-Aided MJ-EKF SLAM Algorithm for Large-Scale Map Based on Heterogeneous Multi-Core SoC 49

A Real-Time Hardware-Accelerator-Aided MJ-EKF SLAM Algorithm...

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49th Annual Conference of the IEEE Industrial Electronics Society, IECON 2023

作者： Fan, Zhendong Wang, Ke Bao, Minjie Li, Ruifeng Harbin Institute of Technology State Key Laboratory of Robotics and Systems Harbin China

ISBN: (纸本)9798350331820

As a classic SLAM algorithm, LIDAR-based EKF SLAM still remains a problem. An open issue is high computational complexity, which leading a very limited map size to sufficient real-time requirements. To address this problem, in this paper, we propose an MJ-EKF SLAM system that is fully implemented on a Heterogeneous Multi-Core SoC(HMS). To limit the EKF SLAM computation complexity, the Map Joining algorithm participates in the framework. The most computation cost step in EKF SLAM and Map Joining algorithms is implemented on an MJ-EKF dedicated accelerator. Meanwhile, several hardware optimization methods are proposed to save logic resources, avoid redundant computation and reduce data communication between on-chip memory and off-chip main memory. Field experiments demonstrate the HMS-based MJ-EKF algorithm achieved high real-time performance (over 30Hz) in a large-scale map with 500 landmarks. © 2023 IEEE.

关键词： system-on-chip

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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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Self-adjusting voxelated electrochemical three-dimensional printing of metallic microstructures

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International Journal of Extreme Manufacturing 2025年第1期7卷 420-433页

作者： Xianghe Meng Xiaomo Wu Xingjian Shen Yan Xu Hao Zhang Mingjun Chen Hui Xie State Key Laboratory of Robotics and Systems Harbin Institute of TechnologyHarbin 150080People’s Republic of China

Microscale metallic structures enhanced by additive manufacturing technology have attracted extensive attention especially in microelectronics and electromechanical ***-confined electrodeposition(MCED)advances microscale 3D metal printing,enabling simpler fabrication of superior metallic microstructures in air without complex equipment or ***,accurately predicting growth rates with current MCED techniques remain challenging,which is essential for precise structure fabrication and preventing nozzle *** this work,we present a novel approach to electrochemical 3D printing that utilizes a self-adjusting,voxelated method for fabricating metallic *** from conventional voxelated printing which focuses on monitoring voxel thickness for structure control,this technique adopts a holistic *** ensures each voxel’s position is in alignment with the final structure by synchronizing the micropipette’s trajectory during deposition with the intended design,thus facilitating self-regulation of voxel position and reducing errors associated with environmental fluctuations in deposition *** method’s ability to print micropillars with various tilt angles,high density,and helical arrays demonstrates its refined control over the deposition *** electron microscopy analysis reveals that the deposited structures,which are fabricated through layer-by-layer(voxel)printing,contain nanotwins that are widely known to enhance the material’s mechanical and electrical ***,in situ scanning electron microscopy(SEM)microcompression tests confirm this enhancement,showing these structures exhibit a compressive yield strength exceeding 1 *** indentation tests provided an average hardness of 3.71 GPa,which is the highest value reported in previous work using *** resistivity measured by the four-point probe method was(1.95±0.01)×10^(−7)Ω·m,nearly 11 times that of bulk ***

关键词： additive manufacturing self-adjusting voxelated electrodeposition metallic microstructures 3D printing nanotwinned copper

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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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Numerical simulation of the vacuum casting process of solid propellants 3

Numerical simulation of the vacuum casting process of solid ...

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2024 3rd International Conference on Acoustics, Fluid Mechanics and Engineering, AFME 2024

作者： Gao, Zhe Wei, Ming Li, Wensen Chen, Cunzhuang Li, Changle Zhao, Jie State Key Laboratory of Robotics and Systems Harbin Institute of Technology Harbin150000 China Hubei Institute of Aerospace Chemical Technology Xiangyang441003 China

Solid propellant is one of the main components of rocket engines, and the casting of low-viscosity propellant slurry usually uses a vacuum casting process. During the vacuum casting process, the rheological properties of solid propellant slurry are complex, and the theoretical analytical method cannot intuitively and accurately analyze its flow characteristics. Therefore, this paper numerically simulates the casting process through simulation software, uses the Herschel-Bulkley model to characterize the changes in the flow characteristics of solid propellant slurry during the vacuum casting process, and studies the effects of different hopper angles and anti-break vacuum plug shapes on the slurry's rheological properties. By analyzing parameters such as slurry mass flow rate, velocity, residual amount in the hopper, and surface pressure of the plug, the appropriate hopper angle and the bottom edge angle of the anti-break vacuum plug are selected. Finally, the slurry leveling characteristics under suitable hopper and plug conditions are analyzed. The results indicate that a hopper angle of 140° and an anti-break vacuum plug bottom angle of 120° are optimal. The entire vacuum casting process takes approximately 42 seconds, and the overall slurry leveling is good. As the casting progresses, the slurry gradually compacts and levels out, and the bubbles at the bottom of both sides of the combustion chamber gradually disappear. © Published under licence by IOP Publishing Ltd.

关键词： Hoppers

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Human-machine shared control:New avenue to dexterous prosthetic hand manipulation

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Science China(Technological Sciences) 2021年第4期64卷 767-773页

作者： YANG DaPeng LIU Hong State Key Laboratory of Robotics and System Harbin Institute of TechnologyHarbin 150080China Artificial Intelligence Laboratory Harbin Institute of TechnologyHarbin 150080China

At present,albeit the dexterous hand prostheses of multiple degrees of freedom(DOFs)have become prosperous on the market,the user’s demand on intuitively operating these devices have not been well addressed so that their acceptance rate is relatively *** unintuitive control method and inadequate sensory feedback are frequently cited as the two barriers to the successful application of these dexterous ***,driven by the wave of artificial intelligence(AI),a series of shared control methods have emerged,in which"bodily function"(myoelectric control)and"artificial intelligence"(local autonomy,computer vision,etc.)are tightly integrated,and provided a new conceptual solution for the intuitive operation of dexterous *** this paper,the background and development trends of this type of methods are described in detail,and the potential development directions and the key technologies that need breakthroughs are *** practice,we instantiate this shared control strategy by proposing a new method combining simultaneous myoelectric control,multi-finger grasp autonomy,and augmented reality(AR)feedback *** method"divides"the human sophisticated reach-and-grasp task into several subtasks,and then"conquers"them by using different strategies from either human or machine *** is highly expected that the shared control methods with hybrid human-machine intelligence could address the control problem of dexterous prostheses.

关键词： robotic hand dexterous prostheses shared control computer vision deep learning

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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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