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作者： Qin, Zhonghao Wang, Ke Li, Ruifeng State Key Laboratory of Robotics and System Harbin Institute of Technology 92 Xidazhi Street Harbin150006 China

In the process of vision-assisted robot automatic welding, splash and arc noise will interfere with the useful information in the image, which has a serious impact on the subsequent vision-based weld seam recognition and tracking algorithm. Although various methods have been proposed to achieve noise reduction, those are implemented from a perspective of image processing or intelligent algorithm. In this paper, we propose a pairwise response noise reduction model (PRNM) from the imaging perspective of seam tracking camera, which provides an image processing-free method to suppress welding splash and arc. Inverse response law and the loss function is established and solved by using singular value decomposition, and then the irradiance of reference scene is restored. A tone mapping approach is proposed based on the advantages of full-range compression and joint estimator, followed by mapping the obtained irradiance distribution to a high dynamic range (HDR) image. The grayscale correspondences of two reference images and the HDR image are reflected in the form of a two-dimensional lookup table (LUT). For welding noise characteristics, an alignment strategy is proposed to further correct the LUT to form a PRNM, which responds to all pairwise inputs with high computational efficiency. A batch of PRNMs have potential to form imaging solutions serving a welding process library. Experimental results reveal that the proposed model has a good effect in noise reduction, and the real-time performance is suitable for weld seam tracking. © 2022, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

关键词： Noise abatement

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On-orbit assembly control based on model predictive control and load online identification

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Advances in Space Research 2025年第1期76卷 533-550页

作者： Li, Yuntao Xu, Zichun Zhao, Zhiyuan Zhuang, Lei Yang, Xiaohang Ma, Boyu Zhao, Jingdong Liu, Hong State Key Laboratory of Robotics and Systems Harbin Institute of Technology Harbin150001 China

Space manipulator are essential for on-orbit assembly (OOA) tasks. This paper proposes an advanced control framework to address key challenges in Cartesian trajectory tracking and compliant assembly. First, a rigid-body dynamic model of the manipulator is established using CAD model and joint friction identification. A Linear Extended state Observer (LESO) is designed to mitigate system errors by modeling both parametric uncertainties and external disturbances as an extended state. Additionally, the method for selecting parameters of the LESO, along with its convergence proof, is presented. Second, a model predictive control (MPC) algorithm is employed to optimize the Cartesian trajectory of the manipulator in real time. By linearizing the Cartesian space trajectory, the MPC problem is formulated as a QP problem. Solving this QP problem in real-time allows for the optimization of the Cartesian space trajectory, thereby improving the trajectory tracking accuracy in Cartesian space. Finally, online identification of load parameters, sensor zero drift, and temperature drift enables effective compliant assembly control. Extensive experiments validate the proposed methods: (1) The Cartesian trajectory tracking error is maintained below 0.1 mm. (2) After sensor compensation for identified load parameters, zero drift, and temperature drift, the maximum force residual is 0.42 N, and the maximum torque residual is 0.1 N m. © 2025 COSPAR

关键词： Predictive control systems

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WSC-Trans: A CNN-Transformer Structure-Based 3D Multi-Structural Automatic Segmentation Model for Temporal Bone CT

WSC-Trans: A CNN-Transformer Structure-Based 3D Multi-Struct...

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2024 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2024

作者： Hua, Xin Ma, Jixin Yu, Hongjian Du, Zhijiang Zheng, Fanjun Zhang, Chen Lu, Qiaohui Zhao, Hui Harbin Institute of Technology State Key Laboratory of Robotics and System Harbin China The 6th Medical Center Chinese Pla General Hospital Senior Department of Otolaryngology Head and Neck Surgery Beijing China

ISBN: (纸本)9798350386226

Cochlear implantation is the most effective treatment for severe deafness, which requires accurate localization of temporal bone anatomy. Preoperative CT image segmentation is an essential technique to determine the location of relevant tissues in the temporal bone. However, manual segmentation is usually time-consuming and suffers from low accuracy due to the complex and small structures of these tissues in temporal bone CT. To address this issue, we proposed a CNN-Transformer structure-based 3D multi-structured model for the automatic segmentation of fine and complex tissues such as the cochlea, facial nerve, ossicles, vestibule and semicircular canal in the temporal bone CT. Our model adopts a new Transformer deformation structure, which effectively utilizes the spatial attention mechanism to capture feature dependencies, and uses the channel attention mechanism to fuse different channel semantic representations to improve segmentation accuracy. Extensive experiments on a private temporal bone CT dataset show that our model achieves higher DSS and JSS scores, and lower HD95 and ASSD scores for all targets compared with other existing segmentation methods, demonstrating its superior performance. © 2024 IEEE.

关键词： Computerized tomography

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Research on Motion Mode Conversion Control of Wheel-legged Biped Robot 20

Research on Motion Mode Conversion Control of Wheel-legged B...

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20th IEEE International Conference on Mechatronics and Automation, ICMA 2023

作者： Fu, Yili Li, Xu Dong, Xinyu Intelligent Robot Research Center Zhejiang Laboratory Hangzhou China Harbin Institute of Technology State Kay Laboratory of Robotics and System Heilongjiang Province Harbin China Harbin Institute of Technology Heilongjiang Province Harbin China

ISBN: (纸本)9798350320831

The bipedal wheel-legged robot with auxiliary legs studied in this paper has two motion modes, two wheels and four wheels, and can transform motion modes according to operation requirements. This paper focuses on how to realize motion mode transformation control under stable equilibrium. Firstly, kinematics analysis and dynamics modeling of the robot are carried out to complete the motion description and dynamics description of the robot in Cartesian space. Then the robot is simplified into a wheeled inverted pendulum model, and the driving wheel and other parts are decoupled to analyze its dynamic characteristics. In this paper, LQR controller will be used to ensure the robot is always in a balanced state, and then priority task space control (PTSC) based on quadratic programming (QP) will be adopted to track the robot trajectory. Finally, the smooth transformation of the robot under two motion modes of two wheels and four wheels is completed by experiments, which verifies the effectiveness of the control algorithm designed in this paper. © 2023 IEEE.

关键词： Quadratic programming

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A Collision Avoidance Path Planning Method for 7-DOF Space Manipulator

A Collision Avoidance Path Planning Method for 7-DOF Space M...

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2023 IEEE International Conference on robotics and Biomimetics, ROBIO 2023

作者： Han, Xu Yang, Guocai Jin, Minghe Wang, Qi Harbin Institute of Technology State Key Laboratory of Robotics and System Heilong Jiang Harbin China Military Representative Office of the Equipment Department of the Aerospace Systems Department Changchun China

ISBN: (纸本)9798350325706

This paper proposes a collision avoidance path planning approach for redundant robotic arms based on the RRT algorithm. The study focuses on a 7-DOF robotic arm with an SSRMS configuration. The method involves improved RRT-based path planning in configuration space (C-space) and collision detection in Cartesian space. The results of collision detection are employed to guide the path planning process. Emulating the SSRMS configuration robotic arm, a kinematic model is established. By enhancing the RRT algorithm with the following points: probabilistic sampling towards the target configuration, guided exploration near existing tree nodes, parent node reassignment for new nodes, and the adoption of a bidirectional searching tree, the randomness of sampling is reduced and the planning process is accelerated. By continuously mapping points on the surface of the arm to both the base coordinate system and the self-collision coordinate system, collision detection and self-collision detection are performed in the Cartesian space using a combination of surface equations and projection methods. Finally, a series of simulation experiments were conducted to analyze the impact of various parameters, different obstacles and different methods on the planning process. This validation confirmed the feasibility and effectiveness of the approach. © 2023 IEEE.

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MRI Super-Resolution via Hybrid Information Enhancement Network based on Multi-Attention and Adaptive Convolution

MRI Super-Resolution via Hybrid Information Enhancement Netw...

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2024 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2024

作者： Ma, Jixin Yu, Hongjian Du, Zhijiang Hua, Xin Li, Zibo Zhao, Hui Harbin Institute of Technology State Key Laboratory of Robotics and System Harbin China The 6th Medical Center Chinese Pla General Hospital Senior Department of Otolaryngology Head and Neck Surgery Beijing China

ISBN: (纸本)9798350386226

Deep learning-based super-resolution (SR) reconstruction is a critical approach which is used to generate high-resolution images from corresponding low-resolution images. However, the CNN-based methods are ineffective in capturing global information, whereas the Transformer-based methods have limited ability to model long-range dependencies caused by window self-attention. Besides, it is a challenging task to recover lost high-frequency information from downsampled images. In this paper, a Hybrid Information Enhanced Network (HIEN) is proposed for MRI super-resolution task. Specifically, we propose a Spatial-Channel Hybrid Attention (SCHA) to enhance specific semantics representation by combining spatial and channel self-attention together. To recover more high-frequency components, we propose a Dynamic High-Frequency Pass Filter (DHPF) to preserve high-frequency information adaptively in pixel-wise. The results of our extensive experiments indicate that HIEN outperforms other state-of-the-art methods. © 2024 IEEE.

关键词： Image reconstruction

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Transformer-Enhanced Motion Planner: Attention-Guided Sampling for state-Specific Decision Making

arXiv

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arXiv 2024年

作者： Zhuang, Lei Zhao, Jingdong Li, Yuntao Xu, Zichun Zhao, Liangliang Liu, Hong The State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin150001 China

Sampling-based motion planning (SBMP) algorithms are renowned for their robust global search capabilities. However, the inherent randomness in their sampling mechanisms often result in inconsistent path quality and limited search efficiency. In response to these challenges, this work proposes a novel deep learning-based motion planning framework, named Transformer-Enhanced Motion Planner (TEMP), which synergizes an Environmental Information Semantic Encoder (EISE) with a Motion Planning Transformer (MPT). EISE converts environmental data into semantic environmental information (SEI), providing MPT with an enriched environmental comprehension. MPT leverages an attention mechanism to dynamically recalibrate its focus on SEI, task objectives, and historical planning data, refining the sampling node generation. To demonstrate the capabilities of TEMP, we train our model using a dataset comprised of planning results produced by the RRT*. EISE and MPT are collaboratively trained, enabling EISE to autonomously learn and extract patterns from environmental data, thereby forming semantic representations that MPT could more effectively interpret and utilize for motion planning. Subsequently, we conducted a systematic evaluation of TEMP's efficacy across diverse task dimensions, which demonstrates that TEMP achieves exceptional performance metrics and a heightened degree of generalizability compared to state-of-the-art SBMPs. Copyright © 2024, The Authors. All rights reserved.

关键词： Motion planning

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"Volume Transfer": A New Design Concept for Fabric-Based Pneumatic Exosuits

arXiv

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arXiv 2024年

作者： Liu, Chendong Yang, Dapeng Chen, Jiachen Dai, Yiming Jiang, Li Liu, Hong Liu, C. Yang, D. Chen, J. Dai, Y. Jiang, L. Liu, H. State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin150001 China

The fabric-based pneumatic exosuit is now a hot research topic because it is lighter and softer than traditional exoskeletons. Existing research focused more on the mechanical properties of the exosuit (e.g., torque and speed), but less on its wearability (e.g., appearance and comfort). This work presents a new design concept for fabric-based pneumatic exosuits: "Volume Transfer", which means transferring the volume of pneumatic actuators beyond the garment's profile to the inside. This allows for a concealed appearance and a larger stress area while maintaining adequate torques. In order to verify this concept, we develop a fabric-based pneumatic exosuit for knee extension assistance. Its profile is only 26mm and its stress area wraps around almost half of the leg. We use a mathematical model and simulation to determine the parameters of the exosuit, avoiding multiple iterations of the prototype. Experiment results show that the exosuit can generate a torque of 7.6Nm at a pressure of 90kPa and produce a significant reduction in the electromyography activity of the knee extensor muscles. We believe that "Volume Transfer" could be utilized prevalently in future fabric-based pneumatic exosuit designs to achieve a significant improvement in wearability. Copyright © 2024, The Authors. All rights reserved.

关键词： Pneumatic actuators

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Target-driven Object Grasping Method for Mobile Manipulator in Clutter

Target-driven Object Grasping Method for Mobile Manipulator ...

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2022 IEEE International Conference on Unmanned systems, ICUS 2022

作者： Yu, Xinkai Gao, Yongzhuo Dong, Wei Li, Mingyang Liu, Huajian Wang, Chao Harbin Institute of Technology State Key Laboratory of Robotics and System Harbin China Beijing Institute of Control Engineering Beijing China

ISBN: (数字)9781665484565

ISBN: (纸本)9781665484565

The demand for mobile manipulator in the military field is strong, but there is no product that can achieve autonomous grasping in a cluttered environment. In this paper, a target-driven grasp pose detection algorithm is proposed, which can be used to detect the grasp pose of a specified target object in a cluttered environment. After that, based on the lightweight requirements of the military, a mobile manipulator platform is built, and the forward and inverse kinematics model of the mobile manipulator is established. At the same time, a vehicle-arm coordination algorithm is designed to make the grasping efficiency higher. Finally, we use the mobile manipulator to perform autonomous grasping in a cluttered environment to verify the system functionality. © 2022 IEEE.

关键词： Manipulators

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Fast-Poly: A Fast Polyhedral Framework For 3D Multi-Object Tracking

arXiv

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arXiv 2024年

作者： Li, Xiaoyu Liu, Dedong Wu, Yitao Wu, Xian Zhao, Lijun Gao, Jinghan State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin150006 China

3D Multi-Object Tracking (MOT) captures stable and comprehensive motion states of surrounding obstacles, essential for robotic perception. However, current 3D trackers face issues with accuracy and latency consistency. In this paper, we propose Fast-Poly, a fast and effective filter-based method for 3D MOT. Building upon our previous work Poly-MOT, Fast-Poly addresses object rotational anisotropy in 3D space, enhances local computation densification, and leverages parallelization technique, improving inference speed and precision. Fast-Poly is extensively tested on two large-scale tracking benchmarks with Python implementation. On the nuScenes dataset, FastPoly achieves new state-of-the-art performance with 75.8% AMOTA among all methods and can run at 34.2 FPS on a personal CPU. On the Waymo dataset, Fast-Poly exhibits competitive accuracy with 63.6% MOTA and impressive inference speed (35.5 FPS). The source code is publicly available at https://***/lixiaoyu2000/FastPoly. © 2024, CC BY-NC-SA.

关键词： Object detection

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