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SSRN 2023年

作者： Xia, Changqing Xia, Tianhao Wang, Renjun Jin, Xi Xu, Chi Li, Dong Zeng, Peng State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110169 China Shenyang University of Chemical Technology Shenyang110142 China Shenyang University of Technology Shenyang110870 China

Satisfying the deterministic demand of industrial tasks is difficult because of the heterogeneity of devices and unclear affinity between tasks and platforms in industrial edge computing scenarios. To address this problem, this study proposes an entropyweight-scheduling method based on resource quantification. First, we analyzed the affinity problem in cross-platform operation of tasks and expanded the scheduling evaluation indicators in the existing real-time systems by analyzing the matching relationship between the attributes of various tasks and characteristics of the platform based on resource quantification. Next, we combined the entropy weight method to process the information entropy of all scheduling evaluation indicators and calculated the weighted summation results to assign the optimal scheduling device to each task. Finally, the entropy-weight-scheduling algorithm based on resource quantification was designed to analyze the scheduling performance of the algorithm under various parameter configurations. The experimental analysis indicated that the scheduling method based on resource quantification could effectively optimize the resource demand relationship between tasks and platforms, and the scheduling success rate of the proposed algorithm was 5.1%,7.7%, and 34.5% higher than those of MTT-SS, D-Quantify, and RRA algorithms, respectively. © 2023, The Authors. All rights reserved.

关键词： Scheduling algorithms

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State-of-Charge (SOC) Estimation of Lithium-Ion Battery Based on Unscented Kalman Filtering

State-of-Charge (SOC) Estimation of Lithium-Ion Battery Base...

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IEEE Advanced Information Management,Communicates,Electronic and Automation control Conference (IMCEC)

作者： Mengfan Miao Ligang Li Zhongfeng Wang Jing Jiang College of Automation and Electrical Engineering Shenyang Ligong University Liaoning China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China

ISBN: (数字)9798350316537

ISBN: (纸本)9798350316544

Real-time estimation of State of Charge (SOC) for lithium-ion batteries is one of the core technologies in Battery Management Systems (BMS). Accurate SOC estimation is fundamental for managing lithium-ion batteries. In this study, a second-order RC equivalent circuit model is established, and parameter identification methods are employed to determine the model parameters. The identified parameters are then incorporated back into the second-order RC model. The accuracy of these parameters and the model is validated through Hybrid Pulse Power Characteristic (HPPC) tests. Finally, the Unscented Kalman Filtering algorithm (UKF) is utilized to estimate battery SOC. Experimental results demonstrate that SOC estimation based on UKF exhibits high precision and stability.

关键词： Lithium-ion batteries Accuracy Parameter estimation Simulation Estimation Data models Stability analysis

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A localizability estimation method for mobile robots based on 3D point cloud feature

A localizability estimation method for mobile robots based o...

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2021 IEEE International Conference on Real-Time Computing and robotics, RCAR 2021

作者： Liu, Ying Wang, Jingchuan Huang, Yi Institute of Medical Robotics Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Department of Automation Shanghai200240 China Nanjing Kingyoung Intelligent Technology CO. LTD.

ISBN: (纸本)9781665436786

This paper introduces the theoretical analysis and derivation of localizability estimation for mobile robots based on point cloud observation. Combined with the observation model, the pre-established point cloud map is firstly clustered and segmented with a newly proposed method considering multiple constraints on depth map. Then localizability is set to be equal to the strength of the constraints associated with 3D point cloud features. In addition, based on the method of using information matrix theory, this paper integrates the Fisher's information matrix and point cloud features to estimate localizability. © 2021 IEEE.

关键词： Mobile robots

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Adaptive Block Elevation Mapping for Large-scale Scene

Adaptive Block Elevation Mapping for Large-scale Scene

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IEEE International Conference on robotics and Biomimetics

作者： Yang Zhou Shiqiang Zhu Huang Huang Yuehua Li Jason Gu Research Center for Intelligent Robotics Research Institute of Interdisciplinary Innovation Zhejiang Laboratory Hangzhou China Zhejiang Engineering Research Center for Intelligent Robotics Hangzhou China Beijing Institute of Control Engineering Beijing China Beijing Research Institute of Zhejiang Laboratory Beijing China Department of Electrical and Computer Engineering Dalhousie University Halifax NS Canada

ISBN: (纸本)9781665481106

Dense map that contains the surrounding geometry and vision information of a robot is widely used for path planning, navigation, obstacle avoidance and other applications. Considering the performance of the processing unit mounted on the robot is limited, mapping algorithm has to make compromise by sacrificing speed and precision. It will be more challenging when the dense mapping scene is very large because the memory consumption will be greatly increased and the map is difficult to be extended if beyonding the initial map. To suppress the negative impact from the increased map scale, we proposed a novel block mapping approach to generate the dense map in large scale of scene. In this work, the elevation map is selected as the base dense map. The entire elevation map is segmented into numerous block maps of which size is much smaller than that of the entire map. The present moment of lidar and vision measurements are used to generate the local elevation map. The local elevation map is used to update block maps which are adaptively generated along the motion trajectory. A memory-disk interaction mechanism, which the block maps will be loaded to memory or saved to local disk when needed, is introduced. Our block mapping approach is tested on the KITTI datasets, and the results demonstrate that the mapping approach can stably operate in a large scale of scene with a much smaller consumption of memory.

关键词： Geometry Laser radar Navigation Motion segmentation Memory management Robot sensing systems Trajectory

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A Haptic Exploration and Surface Classification of Objects with Four Typical Surface Properties 8

A Haptic Exploration and Surface Classification of Objects w...

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8th IEEE International Conference on Advanced robotics and Mechatronics, ICARM 2023

作者： Qi, Peng Wu, Yunfeng Yao, Tianliang Lu, Bo Sun, Yi Dai, Jian S. College of Electronics and Information Engineering Tongji University Department of Control Science and Engineering Shanghai China Robotics and Microsystems Center School of Mechanical and Electric Engineering Soochow University Jiangsu Suzhou China Ecole Polytechnique Federale de Lausanne Laboratory of Intelligent Systems Lausanne1015 Switzerland College of Engineering Southern University of Science and Technology Department of Mechanical and Energy Engineering Shenzhen518055 China School of Natural Mathematical and Engineering Sciences King's College London United Kingdom

ISBN: (纸本)9798350300178

To effectively interact with the physical world, an intelligent robot is required to have the ability to obtain the detailed features of an unknown object. Visual devices are commonly used to detect the global geometry of an object;however, detailed information such as surface properties cannot be identified using these devices. The current study proposes an efficient haptic exploration method to recognize the physical properties of surfaces using an intelligent fingertip. Our surface-following algorithm utilizes the normal force vector and the tangential force vector at the contact point between the fingertip and the target object to predict the moving direction and implement the surface exploration. And a correction index K is introduced to adjust the sliding velocity. The algorithm is proved to be robust and high performance both in simulation and lab experiments. Finally, we propose and explore a haptic prediction neural network, which enables our robot to have an accurate feel through physical interaction. In the classification experiment of four types of objects with different surface properties, the average accuracy of the proposed model is 90.2%. © 2023 IEEE.

关键词： Surface properties

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Disturbance-resistant Camera-LiDAR Fusion for Robust Three-dimentional Object Detection

Disturbance-resistant Camera-LiDAR Fusion for Robust Three-d...

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IEEE International Conference on robotics and Biomimetics

作者： Zhihan Zhu Xubin Lin Zerong Su Shixin Mao Haifei Zhu Xuefeng Zhou Biomimetic and Intelligent Robotics Lab (BIRL) Guangdong University of Technology Guangzhou China Guangdong Key Laboratory of Modern Control Technology Guangdong Institute of Intelligent Manufacturing Guangzhou China Jiutian Innovation (Guangdong) Intelligent Technology Co. Ltd Foshan Guangdong China

ISBN: (纸本)9781665481106

Three-dimentional object detection using monocular cameras and LiDAR fusion presupposes that the accuracy of extrinsic calibration between cameras and LiDAR is satisfactory. However, in engineering, the Camera-LiDAR calibration error is always quite large. In this paper, the fusion problem of LiDAR-camera with perturbed calibration parameters is investigated, and a soft-association method is proposed for heterogeneous sensor data association. Experiments with the KITTI datasets are carried out to verify our proposed method. Under 6 degrees of freedom bias perturbations, the intersection-over-union score obtained from our method is higher than that of the traditional method. In addition, our method allows valid correlations with translation errors of $\pm 15$ mm and rotation errors of $\pm 0.06$ rad, and our algorithm is successfully deployed on low resolution LiDAR and camera platforms.

关键词： Laser radar Three-dimensional displays Correlation Semantic segmentation Semantics Object detection Sensor fusion

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A Large Capacity Expansion and Robust Recognition Method of Dot-Dispersing Coded Targets with Binary Step-Response Serial Encoding

SSRN

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SSRN 2023年

作者： Song, Limei Zheng, Tenglong Li, Yunpeng Deng, Sanpeng Yang, Yangang Zhu, Xinjun Tianjin Key Laboratory of Intelligent Control of Electrical Equipment Tiangong University Tianjin300387 China School of Control Science and Engineering Tiangong University Tianjin300387 China School of Mechanical Engineering Tiangong University Tianjin300387 China School of Artificial Intelligence Tiangong University Tianjin300387 China School of Mechanical Engineering Tianjin University of Technology and Education Tianjin300222 China Institute of Robotics and Intelligent Equipment Tianjin University of Technology and Education Tianjin300222 China Tianjin Key Laboratory of Intelligent Robot Technology and Application Tianjin300350 China Tianjin Bonus Robotics Technology Co. Ltd Tianjin300350 China

In close-range photogrammetry, it is difficult to meet the measurement requirements of large scenes in actual engineering due to the limited capacity of coded targets. To expand the capacity of the coded target, we propose a binary step-response serial-coded target (BSSCT). The BSSCT introduces periodic binary wave information as an additional feature in the dot-dispersing coded target. Also, a robust recognition algorithm for the BSSCT is developed, the P2-Invariant, and the step period is used for decoding. The capacity of the coded target reaches 7 magnitudes without increasing the auxiliary points. Under different lighting conditions and viewing angles, the measurement experiments show that the BSSCT outperforms other state-of-the-art coded targets. Our BSSCT is a promising standard method for large field system calibration and object measurement. © 2023, The Authors. All rights reserved.

关键词： Signal encoding

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Marker or Markerless? Mode-Switchable Optical Tactile Sensing for Diverse Robot Tasks

arXiv

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arXiv 2024年

作者： Ou, Ni Chen, Zhuo Luo, Shan The State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology Beijing100081 China The Robot Perception Lab. Centre for Robotics Research Department of Engineering King’s College London LondonWC2R 2LS United Kingdom

Optical tactile sensors play a pivotal role in robot perception and manipulation tasks. The membrane of these sensors can be painted with markers or remain markerless, enabling them to function in either marker or markerless mode. However, this uni-modal selection means the sensor is only suitable for either manipulation or perception tasks. While markers are vital for manipulation, they can also obstruct the camera, thereby impeding perception. The dilemma of selecting between marker and markerless modes presents a significant obstacle. To address this issue, we propose a novel mode-switchable optical tactile sensing approach that facilitates transitions between the two modes. The marker-to-markerless transition is achieved through a generative model, whereas its inverse transition is realized using a sparsely supervised regressive model. Our approach allows a single-mode optical sensor to operate effectively in both marker and markerless modes without the need for additional hardware, making it well-suited for both perception and manipulation tasks. Extensive experiments validate the effectiveness of our method. For perception tasks, our approach decreases the number of categories that include misclassified samples by 2 and improves contact area segmentation IoU by 3.53%. For manipulation tasks, our method attains a high success rate of 92.59% in slip detection. Code, dataset and demo videos are available at the project website https://***/Marker-Markerless-Transition/ Copyright © 2024, The Authors. All rights reserved.

关键词： Tactile sensors

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Intention-Aware Planner for Robust and Safe Aerial Tracking

arXiv

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arXiv 2023年

作者： Ren, Qiuyu Yu, Huan Dai, Jiajun Zheng, Zhi Meng, Jun Xu, Li Xu, Chao Gao, Fei Cao, Yanjun The State Key Laboratory of Industrial Control Technology College of Control Science and Engineering Zhejiang University Hangzhou310027 China Huzhou Institute Zhejiang University Huzhou313000 China Huzhou Laboratory of Autonomous Intelligent Systems Huzhou313000 China The Robotics Institute Zhejiang University Yuyao315400 China College of Electrical Engineering Zhejiang University Hangzhou310027 China

Autonomous target tracking with quadrotors has wide applications in many scenarios, such as cinematographic follow-up shooting or suspect chasing. Target motion prediction is necessary when designing the tracking planner. However, the widely used constant velocity or constant rotation assumption can not fully capture the dynamics of the target. The tracker may fail when the target happens to move aggressively, such as sudden turn or deceleration. In this paper, we propose an intention-aware planner by additionally considering the intention of the target to enhance safety and robustness in aerial tracking applications. Firstly, a designated intention prediction method is proposed, which combines a user-defined potential assessment function and a state observation function. A reachable region is generated to specifically evaluate the turning intentions. Then we design an intention-driven hybrid A* method to predict the future possible positions for the target. Finally, an intention-aware optimization approach is designed to generate a spatial-temporal optimal trajectory, allowing the tracker to perceive unexpected situations from the target. Benchmark comparisons and real-world experiments are conducted to validate the performance of our method. Copyright © 2023, The Authors. All rights reserved.

关键词： Aircraft detection

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T3: Multi-modal Tailless Triple-Flapping-Wing Robot for Efficient Aerial and Terrestrial Locomotion

arXiv

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arXiv 2025年

作者： Xu, Xiangyu Zheng, Zhi Wang, Jin Chen, Yikai Huang, Jingyang Wu, Ruixin Yu, Huan Lu, Guodong The State Key Laboratory of Fluid Power and Mechatronic Systems School of Mechanical Engineering Zhejiang University Hangzhou310058 China Zhejiang Key Laboratory of Industrial Big Data and Robot Intelligent Systems Zhejiang University Hangzhou310058 China Robotics Research Center of Yuyao City Ningbo315400 China College of Control Science and Engineering Zhejiang University Hangzhou310027 China

Flapping-wing robots offer great versatility;however, achieving efficient multi-modal locomotion remains challenging. This paper presents the design, modeling, and experimentation of T3, a novel tailless flapping-wing robot with three pairs of independently actuated wings. Inspired by juvenile water striders, T3 incorporates bio-inspired elastic passive legs that effectively transmit vibrations generated during wing flapping, enabling ground movement without additional motors. This novel mechanism facilitates efficient multi-modal locomotion while minimizing actuator usage, reducing complexity, and enhancing performance. An SE(3)-based controller ensures precise trajectory tracking and seamless mode transition. To validate T3’s effectiveness, we developed a fully functional prototype and conducted targeted modeling, real-world experiments, and benchmark comparisons. The results demonstrate the robot’s and controller’s outstanding performance, underscoring the potential of multi-modal flapping-wing technologies for future aerial-ground robotic applications. Copyright © 2025, The Authors. All rights reserved.

关键词： Antenna grounds

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