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5th IEEE International Conference on Smart Systems and Technologies, SST 2022

作者： Vuletić, Jelena Polić, Marsela Orsag, Matko University of Zagreb Faculty of EE&C Zagreb Croatia University of Zagreb LARICS Laboratory for Robotics and Intelligent Control Systems Faculty of Electrical Engineering and Computing Zagreb10000 Croatia

ISBN: (数字)9781665482158

ISBN: (纸本)9781665482158

In this paper, a deep learning based object detection model is developed for robotic applications in structured agricultural cultivation of sweet peppers (Capsicum annuum). We propose a realistic simulation based method for procedural generation of a labeled sweet pepper dataset. Realistic 3D models of fruit, leaves, and other relevant plant body parts are generated through photogrammetry, enabling generation of a large and relevant dataset. The dataset is labeled for both object detection and semantic segmentation by scene rendering in multiple layers and using artificial depth information. Smart augmentation techniques are deployed in procedural generation, as well as label filtering techniques for more realistic dataset labels. A MobileNet-SSD based deep learning model is trained through transfer learning on the generated dataset. The trained model is tested both in simulated environment, as well as on a relevant real-world setup. © 2022 IEEE.

关键词： Object detection

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Antenna Cross-correlation based Compressive Subspace Learning for Wideband Spectrum Sensing 19

Antenna Cross-correlation based Compressive Subspace Learnin...

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19th IEEE International Conference on Communication Technology, ICCT 2019

作者： Gong, Tierui Liu, Zhifeng Yang, Zhijia Wang, Gengshan Key Laboratory of Networked Control Systems State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110169 China University of Chinese Academy of Sciences Beijing100049 China

ISBN: (纸本)9781728105352

To address the performance degradation of wide-band spectrum sensing by sub-Nyquist sampling (SNS) in wireless fading channels, two compressive subspace learning (CSL) algorithms are proposed for signal subspace learning based on antenna cross-correlations for further improving the sensing performance. Both algorithms are developed based on different organizations of SNS samples, and both exploit space diversity and noise uncorrelations between antennas. We further establish the expressions for statistical covariance matrices (SCMs) obtained by SNS samples in the multi-antenna SNS cognitive radio system. Based on the derived SCM expressions, conditions to ensure SCMs without noise contamination are given. Simulations validate the derived conditions and show the improvement on sensing performance over related works. © 2019 IEEE.

关键词： Covariance matrix

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Robot map building in unknown dynamic environment based on hybrid dezert-smarandache model

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Information Technology Journal 2009年第3期8卷 284-292页

作者： Peng, Li Xinhan, Huang Min, Wang Intelligent Control and Robotics Laboratory Department of Control Science and Engineering Huazhong University of Science and Technology Wuhan 430074 China

In this study, a new method of information fusion DSmT (Dezert-Smarandache Theory) which is extended from Bayesian Theory and Dempster-Shafer Theory (DST) is introduced to solve the problem of robot map building in an unknown dynamic environment. The grid map method is adopted and a sonar sensor mathematical model is constructed based on DSmT. Meanwhile a few of general basic belief assignment functions (gbbaf) are constructed to deal with the uncertain and imprecise, sometimes even high conflicting information obtained by sonar sensors with the application of hybrid DSm model in the system and consideration of characteristics of sonar sensors. At last, Pioneer II mobile robot is used to carry out experiments of map building. The 2D general basic belief assignment (gbba) maps are structured and then correlative 3D gbba maps are built by openGL. The comparison of created ichnography with the real map testified the validity of hybrid DSm model for fusing imprecise information and map building proposed by this research. © 2009 Asian Network for Scientific Information.

关键词： Information fusion

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A new control method of quadruped robot walking on rough terrain based on linear inverted pendulum method

A new control method of quadruped robot walking on rough ter...

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IEEE International Conference on robotics and Biomimetics

作者： Xin Li Junyao Gao Qiang Huang Haojian Lu Zhe Xu Yi Liu Intelligent Robotics Institute Key Laboratory of Intelligent Control and Decision of Complex System Beijing China

ISBN: (纸本)9781479973989

This paper proposes a new method of linear inverted pendulum control, which is used to control the quadruped robot walking on regular uneven terrain such as ramp and stair, furthermore, this method can be applied to a more rugged terrain. This paper analyzes the dynamic parameters of a quadruped robot walking on the complex terrain, which means the supporting points of the robot lie in different heights relative to the level ground. In order to ensure the same leg length, there will be energy dissipation caused by the raise of the center of mass. Therefore this paper proposes a dual length linear inverted pendulum method (DLLIPM), which not only effectively reduces the energy dissipation, but also promotes the workspace utilization. In addition, Newton-Raphson algorithm is used to optimize the linear inverted pendulum movement, which makes the movement symmetrical and smooth. Finally this paper presents simulation results with DLLIPM on a quadruped robot with 16 degrees of freedom.

关键词： Legged locomotion Foot Trajectory Mathematical model Robot sensing systems

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Landing Area Prediction in Complex Terrains for Walking-assisted Lower-limb Exoskeleton Robot

Landing Area Prediction in Complex Terrains for Walking-assi...

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2023 International Conference on Biomimetic Intelligence and robotics

作者： Liu, Yuexun Liu, Du-Xin Ma, Yue Guo, Sheng Wu, Xinyu Robotics Research Center School of Mechanical Electronic and Control Engineering Beijing Jiaotong University Beijing100044 China Guangdong Provincial Key Laboratory of Robotics and Intelligent System Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen518055 China

With the expansion of application scenarios, the walking-assisted lower-limb exoskeleton robot urgently needs to improve its walking ability in complex terrains. However, due to the lack of environmental understanding ability and decision-making ability, the exoskeleton can not meet the need of people with lower-limb disability in complex terrains. To improve the walking abillity, this paper proposes a method of predicting the landing area in complex terrains for walking-assisted lower-limb exoskeleton robot. Multiple sensors were used to obtain the terrain information, step length, and stride length of human walking, and a multi-type input convolutional network was built to establish the mapping relationship to learn the decision-making mechanism of human standing in a complex environment. The result shows that the established network effectively predicts the landing area. Under the condition of full training, the predicted position deviation of the landing area is controlled within 6%, and the prediction rationality of the landing area can reach 90%. © 2023 The Authors. Published by Elsevier B.V.

关键词： Decision making

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High-precision Calibration of Camera and IMU on Manipulator for Bio-inspired Robotic System

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Journal of Bionic Engineering 2022年第2期19卷 299-313页

作者： Yinlong Zhang Wei Liang Sichao Zhang Xudong Yuan Xiaofang Xia Jindong Tan Zhibo Pang State Key Laboratory of Robotics Shenyang Institute of AutomationChinese Academy of SciencesShenyang 110016China Key Laboratory of Networked Control Systems Chinese Academy of SciencesShenyang 110016China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of SciencesShenyang 110169China The School of Computer Science and Technology Xidian UniversityXi’an 710071China Department of Mechanical Aerospace and Biomedical EngineeringUniversity of TennesseeKonxville 37996USA Department of Automation Technology ABB Corporate Research Sweden72178 VästerasSweden

Inspired by box jellyfish that has distributed and complementary perceptive system,we seek to equip manipulator with a camera and an Inertial Measurement Unit(IMU)to perceive ego motion and surrounding unstructured *** robot perception,a reliable and high-precision calibration between camera,IMU and manipulator is a critical *** paper introduces a novel calibration ***,we seek to correlate the spatial relationship between the sensing units and manipulator in a joint ***,the manipulator moving trajectory is elaborately designed in a spiral pattern that enables full excitations on yaw-pitch-roll rotations and x-y-z translations in a repeatable and consistent *** calibration has been evaluated on our collected visual inertial-manipulator *** systematic comparisons and analysis indicate the consistency,precision and effectiveness of our proposed calibration method.

关键词： Bio-inspired robotic system Monocular camera IMU Manipulator Calibration

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Sonar grid map building of mobile robots based on DSmT

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Information Technology Journal 2006年第2期5卷 267-272页

作者： Li, Xinde Huang, Xinhan Wang, Min Intelligent Control and Robotics Laboratory Department of Control Science and Engineering Huazhong University of Science and Technology Wuhan 430074 China

The research of self-location and map building among some entirely unknown environments is an important and popular subject of intelligent mobile robots. Someone compared it to the problem of chicken and egg. But the application of Sonar sensors with some advantages such as cheapness, simple-operation and convenient-disposal resulted in uncertain and imprecise knowledge acquired. Aimed to this, a new method of information fusion recently developed from Bayesian theory and Dempster-Shafer theory was applied and on the base of experiment, according to sonar's metrical characteristic, the general basic belief assignment functions were constructed for modeling of static environment. Finally, grid map of 3D building on-line for mobile robot was used to compare from the real environment by the experiment. By analyzing the result of comparison, the validity of this method was fully verified. © 2006 Asian Network for Scientific Information.

关键词： Mobile robots

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Domain-Invariant Similarity Activation Map Contrastive Learning for Retrieval-Based Long-Term Visual Localization

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IEEE/CAA Journal of Automatica Sinica 2022年第2期9卷 313-328页

作者： Hanjiang Hu Hesheng Wang Zhe Liu Weidong Chen Department of Automation Shanghai Jiao Tong UniversityShanghai 200240China IEEE Department of Automation Institute of Medical RoboticsKey Laboratory of System Control and Information Processing of Ministry of EducationKey Laboratory of Marine Intelligent Equipment and System of Ministry of EducationShanghai Jiao Tong UniversityShanghai 200240China Department of Computer Science and Technology University of CambridgeCambridge CB30FDUnited Kingdom

Visual localization is a crucial component in the application of mobile robot and autonomous *** retrieval is an efficient and effective technique in image-based localization *** to the drastic variability of environmental conditions,e.g.,illumination changes,retrievalbased visual localization is severely affected and becomes a challenging *** this work,a general architecture is first formulated probabilistically to extract domain-invariant features through multi-domain image ***,a novel gradientweighted similarity activation mapping loss(Grad-SAM)is incorporated for finer localization with high *** also propose a new adaptive triplet loss to boost the contrastive learning of the embedding in a self-supervised *** final coarse-to-fine image retrieval pipeline is implemented as the sequential combination of models with and without Grad-SAM *** experiments have been conducted to validate the effectiveness of the proposed approach on the CMU-Seasons *** strong generalization ability of our approach is verified with the RobotCar dataset using models pre-trained on urban parts of the CMU-Seasons *** performance is on par with or even outperforms the state-of-the-art image-based localization baselines in medium or high precision,especially under challenging environments with illumination variance,vegetation,and night-time ***,real-site experiments have been conducted to validate the efficiency and effectiveness of the coarse-to-fine strategy for localization.

关键词： Deep representation learning place recognition visual localization

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Method of Forming Paths for Uniform Surface Treatment for Objects of Complex Shape 25

Method of Forming Paths for Uniform Surface Treatment for Ob...

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25th IEEE International Conference of Young Professionals in Electron Devices and Materials, EDM 2024

作者： Grigorev, Ivan Mursalimov, Eduard Laboratory of Intelligent Information Systems for Marine Robots M.D. Ageev Institute of Marine Technology Problems FEB RAS Vladivostok Russia Laboratory of Robotics and Intelligent Control Systems Sevastopol State University Laboratory of Intelligent Information Systems for Marine Robots M.D. Ageev Institute of Marine Technology Problems FEB RAS Vladivostok Russia

ISBN: (纸本)9798350389234

In most cases, tool impact paths for surface treatment (painting, milling, laser hardening, etc.) represent a set of continuous spatial curves lying on the surface to be treated. For uniform processing, adjacent curves from this set must be equidistant from each other. This paper presents a new method for covering a given polygonal mesh with equidistant lines based on given initial lines (in the form of a set of vertices on this mesh) and a given distance between adjacent lines, that is measured by Euclidean distance. The method is based on constructing spheres from each vertex of the initial line and removing the vertices of the mesh that fall into at least one of the spheres: the desired equidistant line will be represented by not removed vertices lying on the spheres. To construct each subsequent equidistant line, the last constructed line is used as the initial one: thus, the entire mesh is covered along the surface, despite the fact that the distance between adjacent lines is measured in space. Due to this, the proposed method, unlike the existing ones, works with surfaces of any complexity and requires less computing resources. Ordering the points of the constructed lines, to obtain the reference points of the paths that can be executed by the manipulator, is also presented. © 2024 IEEE.

关键词： Spheres

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A Weighting Factors Autotuning Strategy for Model Predictive Torque control of Permanent Magnet Synchronous Motor Based on Adaptive Multi-Objective Black Hole Algorithm 42

A Weighting Factors Autotuning Strategy for Model Predictive...

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42nd Chinese control Conference, CCC 2023

作者： Zhou, Zixiang Wu, Tao School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China System Integration and Industrial Robotics Laboratory Wuhan430074 China

ISBN: (纸本)9789887581543

The rational design of weighting factors in the cost function for finite control set model predictive torque control (FCS-MPTC) has been a matter of great interest in power electronics and electrical drives. In order to solve this problem, a weighting factors autotuning strategy for FCS-MPTC of permanent magnet synchronous motor (PMSM) based on the adaptive multi-objective black hole algorithm (AMOBH) is proposed. In this paper, the design process of the FCS-MPTC algorithm is first analyzed in detail. Then, an AMOBH algorithm that can take into account both population convergence and population diversity is introduced, and based on this algorithm, the design problem of the weighting factors is successfully transformed into a multi-objective optimization problem by means of reconstructing the cost function and designing the motor operation information collected in real time as the objective functions of the multi-objective optimization algorithm. Simulation results show that the proposed method can find a set of weighting factor combinations suitable for different working condition requirements, and these weighting factors can effectively improve the operation performance of the PMSM system. © 2023 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Cost functions

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