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IEEE International Conference on Automation Science and engineering (CASE)

作者： Yixiang Liu Qing Bi Xizhe Zang Yibin Li School of Control Science and Engineering Shandong University Jinan China State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin China Engineering Research Center of Intelligent Unmanned System Ministry of Education Jinan China Shandong Institute of Advanced Technology Chinese Academy of Sciences Jinan China

ISBN: (数字)9781728169040

ISBN: (纸本)9781728169057

Human walking gait is much more natural looking and energy efficient compared with biped robots. This paper presents a bio-inspired approach to realizing more human-like biped robotic walking. For this purpose, a biped robot actuated coordinately by pneumatic artificial muscles and springs is developed, capable of exploiting passive compliance of the mechanical system in locomotion. And a control scheme for human-like walking is designed based on finite state machine. Experiments show that the biped robot can walk stably on the treadmill even with some small obstacles. The realized gait has the important features of human walking, including heel strike and toe off, stretched knees, and variation in the height of the body's center of mass, which demonstrates the effectiveness of the proposed approach.

关键词： Conferences Automation Computer aided software engineering

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Grapevine Winter pruning automation: On potential pruning points detection through 2D plant modeling using grapevine segmentation

arXiv

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arXiv 2021年

作者： Fernandes, Miguel Scaldaferri, Antonello Fiameni, Giuseppe Teng, Tao Gatti, Matteo Poni, Stefano Semini, Claudio Caldwell, Darwin Chen, Fei Active Perception and Robot Interactive Learning Laboratory Department of Advanced Robotics Istituto Italiano di Tecnologia Via Morego 30 Genova16163 Italy Department of Informatics Bioengineering Robotics and System Engineering Università di Genoa Viale Causa 13 Genova16145 Italy Italy Department of Sustainable Crop Production Università Cattolica del Sacro Cuore Via Emilia Parmense 84 Piacenza29122 Italy lab Istituto Italiano di Tecnologia Via Morego 30 Genova16163 Italy Department of Mechanical and Automation Engineering T-Stone Robotics Institute Chinese University of Hong Kong Chung Chi Rd Ma Liu Shui Hong Kong

Grapevine winter pruning is a complex task, that requires skilled workers to execute it correctly. The complexity of this task is also the reason why it is time consuming. Considering that this operation takes about 80-120 hours/ha to be completed, and therefore is even more crucial in large-size vineyards, an automated system can help to speed up the process. To this end, this paper presents a novel multidisciplinary approach that tackles this challenging task by performing object segmentation on grapevine images, used to create a representative model of the grapevine plants. Second, a set of potential pruning points is generated from this plant representation. We will describe (a) a methodology for data acquisition and annotation, (b) a neural network fine-tuning for grapevine segmentation, (c) an image processing based method for creating the representative model of grapevines, starting from the inferred segmentation and (d) potential pruning points detection and localization, based on the plant model which is a simplification of the grapevine structure. With this approach, we are able to identify a significant set of potential pruning points on the canes, that can be used, with further selection, to derive the final set of the real pruning points. © 2021, CC BY.

关键词： Automation

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Trunk-branch contrastive network with multi-view deformable aggregation for multi-view action recognition

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Pattern Recognition 2025年

作者： Yingyuan Yang Guoyuan Liang Can Wang Xiaojun Wu Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen 518055 China University of Chinese Academy of Sciences Beijing 10049 China Guangdong Provincial Key Laboratory of Robotics and Intelligent System Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen 518055 China School of Mechanical Engineering and Automation Harbin Institute of Technology at Shenzhen Shenzhen 518055 China

Multi-view action recognition aims to identify actions in a given multi-view scene. Traditional studies initially extracted refined features from each view, followed by implemented paired interaction and integration, but they potentially overlooked the critical local features in each view. When observing objects from multiple perspectives, individuals typically form a comprehensive impression and subsequently fill in specific details. Drawing inspiration from this cognitive process, we propose a novel trunk-branch contrastive network (TBCNet) for RGB-based multi-view action recognition. Distinctively, TBCNet first obtains fused features in the trunk block and then implicitly supplements vital details provided by the branch block via contrastive learning, generating a more informative and comprehensive action representation. Within this framework, we construct two core components: the multi-view deformable aggregation (MVDA) and the trunk-branch contrastive learning. MVDA employed in the trunk block effectively facilitates multi-view feature fusion and adaptive cross-view spatio-temporal correlation, where a global aggregation module (GAM) is utilized to emphasize significant spatial information and a composite relative position bias (CRPB) is designed to capture the intra- and cross-view relative positions. Moreover, a trunk-branch contrastive loss is constructed between aggregated features and refined details from each view. By incorporating two distinct weights for positive and negative samples, a weighted trunk-branch contrastive loss is proposed to extract valuable information and emphasize subtle inter-class differences. The effectiveness of TBCNet is verified by extensive experiments on four datasets including NTU-RGB+D 60, NTU-RGB+D 120, PKU-MMD, and N-UCLA dataset. Compared to other RGB-based methods, our approach achieves state-of-the-art performance in cross-subject and cross-setting protocols.

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Towards precise pruning points detection using semantic-instance-aware plant models for grapevine winter pruning automation

arXiv

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arXiv 2021年

作者： Fernandes, Miguel Scaldaferri, Antonello Guadagna, Paolo Fiameni, Giuseppe Teng, Tao Gatti, Matteo Poni, Stefano Semini, Claudio Caldwell, Darwin Chen, Fei Active Perception and Robot Interactive Learning Laboratory Department of Advanced Robotics Istituto Italiano di Tecnologia Via Morego 30 Genova16163 Italy Department of Informatics Bioengineering Robotics and System Engineering Università di Genoa Viale Causa 13 Genova16145 Italy Department of Sustainable Crop Production Università Cattolica del Sacro Cuore Via Emilia Parmense 84 Piacenza29122 Italy Italy lab Istituto Italiano di Tecnologia Via Morego 30 Genova16163 Italy Department of Mechanical and Automation Engineering T-Stone Robotics Institute The Chinese University of Hong Kong Chung Chi Rd Ma Liu Shui Hong Kong

Grapevine winter pruning is a complex task, that requires skilled workers to execute it correctly. The complexity makes it time consuming. It is an operation that requires about 80-120 hours per hectare annually, making an automated robotic system that helps in speeding up the process a crucial tool in large-size vineyards. We will describe (a) a novel expert annotated dataset for grapevine segmentation, (b) a state of the art neural network implementation and (c) generation of pruning points following agronomic rules, leveraging the simplified structure of the plant. With this approach, we are able to generate a set of pruning points on the canes, paving the way towards a correct automation of grapevine winter pruning. © 2021, CC BY.

关键词： Automation

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Numerical and experimental studies of hydrodynamics of flapping foils

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Journal of Hydrodynamics 2018年第2期30卷 258-266页

作者： Kai Zhou Jun-kao Liu Wei-shan Chen College of Mechanical and Electronic Engineering Shandong Agricultural University Taian 271018 China State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin 150001 China

The flapping foil based on bionics is a sort of simplified models which imitate the motion of wings or fins of fish or birds. In this paper, a universal kinematic model with three degrees of freedom is adopted and the motion parallel to the flow direction is considered. The force coefficients, the torque coefficient, and the flow field characteristics are extracted and analyzed. Then the propulsive efficiency is calculated. The influence of the motion parameters on the hydrodynamic performance of the bionic foil is studied. The results show that the motion parameters play important roles in the hydrodynamic performance of the flapping foil. To validate the reliability of the numerical method used in this paper, an experiment platform is designed and verification experiments are carried out. Through the comparison, it is found that the numerical results compare well with the experimental results, to show that the adopted numerical method is reliable. The results of this paper provide a theoretical reference for the design of underwater vehicles based on the flapping propulsion.

关键词： Biological fluid dynamics flapping foil hydrodynamic performance numerical simulation

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Sampling-Based Path Planning in Heterogeneous Dimensionality-Reduced Spaces*

Sampling-Based Path Planning in Heterogeneous Dimensionality...

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Annual Conference of Industrial Electronics Society

作者： Wenjie Lu Huan Yu Hao Xiong Honghai Liu School of Mechanical Engineering and Automation Harbin Institute of Technology (Shenzhen) Shenzhen China School of Automation Beijing Institute of Technology Beijing China Key Laboratory of Robotics and System School of Mechanical Engineering and Automation Harbin Institute of Technology Shenzhen China

ISBN: (数字)9781728154145

ISBN: (纸本)9781728154152

Many sampling strategies often consider the goal and obstacle population to bias/restrict the search area, and they however become less effective when the robot has many degrees of freedom. This paper explores the nonhomogeneous restriction imposed by the obstacles and presents an improved SBP approach enhanced by heterogeneous dimensionality reduction of the full configuration space. Based on the projection residual, a new Dirichlet process (DP) mixture model is proposed to capture a number of Dimensionality-Reduced Spaces (DRSs), which offer the planning spaces with fewer dimensions than its single-DRS counterpart. Then, the sampling and planning procedures are unified with a proposed transversality condition, connecting sampled nodes across DRSs. At last, a quadratic programming is formulated and quickly solved to map the found path in DRSs to an output path in the full configuration space. Numerical simulations on path planning problems of a high-dimensional Intervention Autonomous Underwater Vehicle (I-AUV) have been conducted, showing the feasibility and efficiency of the proposed method.

关键词： Planning Mixture models Path planning Dimensionality reduction Cost function Sensitivity Indexes

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A Calibration Method of Navigation system Integrated with Kinect and Laser Scanner

A Calibration Method of Navigation System Integrated with Ki...

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IEEE International Conference on Real-time Computing and robotics (RCAR)

作者： Lu Zhou Xiujuan Bao Xinwei Chen Institute of Robotics and Automatic Information System (IRAIS) Tianjin Key Laboratory of Intelligent Robotics (tjKLIR) Nankai University Tianjin China College of Artificial Intelligence Nankai University Tianjin China Industrial Robot Application of Fujian University Engineering Research Center Minjiang University Fuzhou China

ISBN: (数字)9781728172934

ISBN: (纸本)9781728172941

This paper presents a new calibration method, which combines the advantages of Kinect large measurement range and high accuracy of laser scanner measurement. The proposed method innovatively designs a calibration objects with special shapes to complete the calibration of laser scanner. To achieve effective fusion between two kinds of sensor information, the laser scanner and Kinect are jointly calibrated to obtain the relative coordinate transform between them. Finally, a particle filter (PF) with the optimal importance function and importance weights is designed to fuse the measurements of the target's range and bearing from the laser scanner and Kinect. The experimental results show that the proposed method can achieve satisfactory tracking performances.

关键词： Calibration Cameras Distortion Robots Robot kinematics Laser radar Lasers

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Force Control in Flexible Object Grasping Based on Position Predictor

Force Control in Flexible Object Grasping Based on Position ...

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IEEE International Conference on robotics and Biomimetics

作者： Qirong Tang Shun Wu Haibo Tu Zhugang Chu Laboratory of Robotics and Multibody System School of Mechanical Engineering Tongji University Shanghai China

A novel manipulation method for grasping flexible objects with a simple rigid robot hand is proposed in this study. Based on a position predictor, it mainly focuses on force control during the object grasping. A desired force for grasping is given at first, then during the process of grasping it is converted to a predicted displacement. An online linear approximator for solving the predicted displacement iteratively is proposed. Here Model Predictive Control (MPC) is adopted to achieve accurate position control. Meanwhile a flexible model is designed for the simulation and verification. This method is verified in a flexible object contact situation and the result indicates that it can control the force precisely in flexible object grasping and achieve better performance compared with admittance control.

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Localization of near-field sources based on linear prediction and oblique projection operator

Localization of near-field sources based on linear predictio...

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作者： Zuo, Weiliang Xin, Jingmin Liu, Wenyi Zheng, Nanning Ohmori, Hiromitsu Sano, Akira Institute of Artificial Intelligence and Robotics National Engineering Laboratory for Visual Information Processing and Applications School of Artificial Intelligence Xi'An Jiaotong University Xi'an710049 China Department of System Design Engineering Keio University Yokohama223-8522 Japan

This paper investigates the localization of multiple near-field narrowband sources with a symmetric uniform linear array, and a new linear prediction approach based on the truncated singular value decomposition (LPATS) is proposed by taking an advantage of the anti-diagonal elements of the noiseless array covariance matrix. However, when the number of array snapshots is not sufficiently large enough, the 'saturation behavior' is usually encountered in most of the existing localization methods for the near-field sources, where the estimation errors of the estimated directions-of-arrival (DOAs) and ranges cannot decrease with the signal-to-noise ratio. In this paper, an oblique projection based alternating iterative scheme is presented to improve the accuracy of the estimated location parameters. Furthermore, the statistical analysis of the proposed LPATS is studied, and the asymptotic mean-square-error expressions of the estimation errors are derived for the DOAs and ranges. The effectiveness and the theoretical analysis of the proposed LPATS are verified through numerical examples, and the simulation results show that the LPATS provides good estimation performance for both the DOAs and ranges compared to some existing methods. © 1991-2012 IEEE.

关键词： Mean square error

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Bilateral Teleoperation of Wheeled Mobile Robots Subject to Lateral Sliding on Soft Terrains

Bilateral Teleoperation of Wheeled Mobile Robots Subject to ...

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Chinese Control Conference (CCC)

作者： Weihua Li Sanjun Liu Dianbo Ren Jianfeng Wang Haibo Gao School of Automotive Engineering Harbin Institute of Technology (Weihai) Weihai China Shanghai Aerospace Equipments Manufacturer Co Ltd Shanghai China State Key Laboratory of Robotics and System Harbin Institute of Technology Harbin China

ISBN: (数字)9789881563903

ISBN: (纸本)9781728165233

With the widespread applications of wheeled mobile robots (WMR) in various fields, new challenges have arisen in terms of designing its control system. A special challenge is the soft terrain which can induce both of the longitudinal slipping and the lateral sliding. This paper proposes a new method for haptic teleoperation control of a WMR with lateral sliding. In this teleoperation system, the linear velocity and the angular velocity of the WMR separately follow the master haptic interface's positions. Due to the functional benefits of displaying the lateral sliding information as haptic feedback to the operator, the lateral velocity is segregated and only perceived by the human operator. Then the teleoperator for the master robot and the slave WMR is designed based on the passivity theory. Experiments of the proposed controller demonstrate that this approach results in stable bilateral teleoperation with a satisfactory tracking performance.

关键词： Wheels Robot kinematics Haptic interfaces Mobile robots Force Kinematics

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