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IEEE International Conference on robotics and Biomimetics

作者： Yang Zhou Wei Wang Han Zhang Chen Wang Gang Xu Guangming Xie College of Mechatronics and Control Engineering Shenzhen University Shenzhen China Department of Urban Studies and Planning Massachusetts Institute of Technology Cambridge MA USA 76315 Troop of the PLA Guangzhou China State Key Laboratory for turbulence and Complex Systems Peking University Beijing China Institute of Ocean Research Peking University Beijing China

ISBN: (纸本)9781728103785;9781728103778

Underwater wireless communication technology has been restricting the development of undersea resources for decades. We have proposed an effective underwater communication method (electrocommunication) for small underwater robots in our previous studies. In this article, we further study how electrode distance/spacing affects the communication range of electrocommunication between the robotic fish models. The working principle of electrocommunication is simplified by an electric dipole model. Based on the electric dipole model, the maximum theoretical distance of electrocommunication is derived as r=K 3 √(d 2 ) where d 2 is the distance between the receiving electrodes, and K is a constant related to the system and environmental parameters. Extensive experiments were conducted by varying the distance between the transmitting electrodes. The results show that the maximum experimental distance is basically consistent with the theoretical predictions, and that the communication distance is positively correlated with the electrode distance.

关键词： Electrodes Robots Receivers Transmitters Unmanned underwater vehicles Microcontrollers Underwater communication

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Learning to Manipulate Tools Using Deep Reinforcement Learning and Anchor Information

Learning to Manipulate Tools Using Deep Reinforcement Learni...

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IEEE International Conference on robotics and Biomimetics

作者： Junhang Wei Shaowei Cui Peng Hao Shuo Wang School of Future Technology University of Chinese Academy of Sciences Beijing China State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China University of Chinese Academy of Sciences Beijing China Center for Excellence in Brain Science and Intelligence Technology Chinese Academy of Sciences Shanghai China

ISBN: (纸本)9781665481106

Endowing robots with tool manipulation skills helps them accomplish challenging tasks. While robots manipulate tools to achieve goals, the alignment of tools and targets is a noise-sensitive and contact-rich task. However, it is difficult to access the accurate pose of the tool and the target. When there is unknown noise in the observations, reinforcement learning can't be sure to perform well. In this paper, we define the easier-to-obtain accurate task-related information as anchor information and introduce a tool manipulation method based on reinforcement learning and anchor information, which can perform well when the observations include unknown noise. To evaluate the method, we build a simulated environment ToolGym, which includes four different kinds of tools and different noise sampling functions for each tool. Finally, we compare our method with baseline methods to show the effectiveness of the proposed method.

关键词： Deep learning Biomimetics Reinforcement learning Grasping Fasteners End effectors Task analysis

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A construction strategy for cloud robotic system

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Sensor Letters 2014年第2期12卷 255-259页

作者： Liang, Yongquan Zhang, Zhenmei Fan, Jiancong Tang, Leiyu State Key Laboratory of Mining Disaster Prevention and Control Ministry of Science and Technology Shandong University of Science and Technology Qingdao China College of Information Science and Engineering Shandong University of Science and Technology Qingdao China College of Management Science and Engineering Shandong University of Finance and Economics Jinan China College of Mathematics and Systems Science Shandong University of Science and Technology Qingdao China

The technological developments of sensors, actuators, communication devices, and especially cloud computing, enable cloud robotics to be studied and designed. A cloud robot is a robot with lightweight inherent configurations, but connected to the cloud. Cloud robotics can offload computationintensive tasks to be executed in remote cloud. In this paper, we design two types of cloud robotic structures, called homoRobotSys and heteroRobotSys respectively. Different structures are designed to adapt to different task-relevant or configuration-relevant requirements. Simulation is developed to discuss time performances of cloud robotics. Comparisons between cloud robotics and networked robotics are also made. Copyright © 2014 American Scientific Publishers.

关键词： Cloud computing

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A real-time multi-constraints obstacle avoidance method using LiDAR

arXiv

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arXiv 2020年

作者： Chen, Wei Sun, Jian Li, Weishuo Zhao, Dapeng State Key Laboratory for Strength & Vibration of Mechanical Structures School of Aerospace Xi’an Jiaotong University Xi’an710049 China Shaanxi Engineering Laboratory for Vibration Control of Aerospace Structures Xi’an Jiaotong University Xi’an710049 China School of Mechanical Engineering Carnegie Mellon University 5000 Forbes Ave PittsburghPA15213 United States Robotics Institute School of Computer Science Carnegie Mellon University 5000 Forbes Ave PittsburghPA15213 United States

Obstacle avoidance is one of the essential and indispensable functions for autonomous mobile robots. Most of the existing solutions are typically based on single condition constraint and cannot incorporate sensor data in a real-time manner, which often fail to respond to unexpected moving obstacles in dynamic unknown environments. In this paper, a novel real-time multi-constraints obstacle avoidance method using Light Detection and Ranging(LiDAR) is proposed, which is able to, based on the latest estimation of the robot pose and environment, find the sub-goal defined by a multi-constraints function within the explored region and plan a corresponding optimal trajectory at each time step iteratively, so that the robot approaches the goal over time. Meanwhile, at each time step, the improved Ant Colony Optimization(ACO) algorithm is also used to re-plan optimal paths from the latest robot pose to the latest defined sub-goal position. While ensuring convergence, planning in this method is done by repeated local optimizations, so that the latest sensor data from LiDAR and derived environment information can be fully utilized at each step until the robot reaches the desired position. This method facilitates real-time performance, also has little requirement on memory space or computational power due to its nature, thus our method has huge potentials to benefit small low-cost autonomous platforms. The method is evaluated against several existing technologies in both simulation and real-world experiments. Copyright © 2020, The Authors. All rights reserved.

关键词： Optical radar

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Synchronous Motion Generation of Multiple Continuum Robots Based on a Jacobian-Estimation Strategy

Synchronous Motion Generation of Multiple Continuum Robots B...

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IEEE International Conference on robotics and Biomimetics

作者： Ning Tan Ruikun Hu Yuyang Wu Xinyu Zhang Fenglei Ni Zhenglong Sun School of Computer Science and Engineering Sun Yat-sen University Guangzhou PR China State Key Laboratory of Robotics and Systems (HIT) Harbin PR China Engineering Research Center of Software/Hardware Co-Design Technology and Application Ministry of Education (East China Normal University) Shanghai PR China School of Science and Engineering The Chinese University of Hong Kong Shenzhen China Shenzhen Institute of Artificial Intelligence and Robotics for Society Shenzhen China

ISBN: (纸本)9781665405362

In this paper, a novel model-free control scheme is proposed for synchronous motion control of multiple continuum robots. The control problem is formulated as two convex optimization routines in an adaptive and model-free closed-loop framework. The proposed approach is heading to address cooperative task execution for multiple continuum robots. The model-free feedback control guarantees the high portability for a wide range of continuum robots. Simulation studies are conducted on two kinds of tasks, which are cooperative task execution with two robots and simultaneously tracking control with three robots. Besides, the superiority of proposed approach is validated through comparisons with other methods. Simulation results prove the high accuracy and efficiency of this model-free feedback control scheme.

关键词： Jacobian matrices Adaptation models Tracking Simulation Conferences Convex functions Feedback control

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Visuotactile Feedback Parallel Gripper for Robotic Adaptive Grasping

Visuotactile Feedback Parallel Gripper for Robotic Adaptive ...

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IEEE International Conference on robotics and Biomimetics

作者： Boyue Zhang Shaowei Cui Chaofan Zhang Jingyi Hu Shuo Wang School of Artificial Intelligence University of Chinese Academy of Sciences Beijing China Institute of Automation Chinese Academy of Sciences Beijing China State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Center for Excellence in Brain Science and Intelligence Technology Chinese Academy of Sciences Shanghai China

ISBN: (纸本)9781665481106

In robot grasp and dexterous manipulation tasks, tactile sensing is important for the control adjustment of the manipulator. In this paper, we present a novel low-cost parallel gripper with high-resolution tactile sensing, named the GelStereo Gripper. Furthermore, an adaptive grasp strategy is proposed to endow the gripper with tactile-feedback grasp stability-maintaining ability. We install the gripper on our robot platform and conduct various grasp experiments by utilizing proposed control methods. Experimental results verify the reliability of the GelStereo gripper and also prove the effectiveness of the proposed strategy for experimental objects with different features.

关键词： Shape Pose estimation Force Tactile sensors Grasping Robot sensing systems Sensors

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A Detection Method for Densely Distributed Coal and Gangue with Uneven Particle Based on Deeplabv3+

SSRN

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SSRN 2024年

作者： Wang, Xi Guo, Yongcun Hu, Kun Jia, Xiaofen Gang, Cheng School of Mechanical Engineering Anhui University of Science and Technology Huainan232001 China State Key Laboratory of Mining Response and Disaster Prevention and Control in Deep Coal Mines Anhui University of Science and Technology Huainan232001 China School of Artificial Intelligence Anhui University of Science and Technology Huainan232001 China School of New Energy and Intelligent networked Automobile Anhui University of Science and Technology Hefei230000 China

A detection network for densely distributed coal and gangue with uneven particle size is proposed based on DeepLabV3+. Firstly, group convolution and 1×1 convolution are used in the encoder to reduce the model parameters, and deformable convolution is introduced to enhance the feature extraction capability for irregularly shaped targets. Then, two shallow feature maps and CA are introduced into the decoder, to enhance the network's focus on the edge detailed information of the adhesion target and the small target location information. Finally, relying on the self-collected multi-condition coal and gangue dataset, the method's effectiveness is demonstrated through comparative validation and test experiments, with an average F1-score of 0.983 and a detection speed of 32.5 FPS. The technique can be adapted to the poor working environment in coal mine production, and realizes the low-cost and high-efficiency identification and localization of coal and gangue. © 2024, The Authors. All rights reserved.

关键词： Coal

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Composite Robust controller Design for Robotic Arm Trajectory Tracking under Parametric Uncertainties

Composite Robust Controller Design for Robotic Arm Trajector...

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IEEE International Conference on robotics and Biomimetics

作者： Umair Javaid Michael Basin Muhammad Niaz Khan Robotic Institute Ningbo University of Technology Zhejiang China School of Robotics Ningbo University of Technology Zhejiang China School of Physical and Mathematical Sciences Autonomous University of Nuevo Leon San Nicolas de los Garza Mexico State Key Laboratory of Tribology Institute of Manufacturing Engineering Lab of Precision/Ultra-Precision Manufacturing Equipments and Control Tsinghua University Beijing China

ISBN: (数字)9798331509644

ISBN: (纸本)9798331509651

Robotic arms are critical for industrial automation. However, it requires a fast and accurate trajectory-tracking response despite the presence of system parametric uncertainties and time-dependent external disturbances. This paper addresses the robotic arm trajectory-tracking problem using a second- order sliding mode observer (SOSMO)-based integral sliding mode control (ISMC) scheme. Initially, we propose a SOSMO design to estimate total system perturbations. The observer estimation errors converge to a small tunable region around zero in finite time. Later, exploiting the SOSMO estimates, a robust ISMC is designed to improve the trajectory tracing performance of the system. We employ the Lyapunove stability theory to prove the convergence of observer estimation and closed-loop system state error to zero in finite time. Finally, comparative numerical simulation results validate the effectiveness and robust performance of the proposed composite control algorithm.

关键词： Uncertainty Trajectory tracking Service robots Perturbation methods Observers Manipulators Stability analysis Trajectory Closed loop systems Convergence

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Analytic Compact Model of Short-channel Cylindrical ballistic GAA MOSFET Including SDT effect

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Journal of Physics: Conference Series 2020年第1期1570卷

作者： He Cheng Chao Zhang Tiefeng Liu Zhijia Yang Zhipeng Zhang Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang 110016 China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang 110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang 110169 China

We have proposed an analytic compact model describing the drain current characteristics valid in all operating regions, for ultra-short channel cylindrical gate-all-around metal-oxide-semiconductor field-effect transistors considering source-to-drain tunnelling effect. The drain-induced barrier lowering had been incorporated from one two-dimensional analysis in our previous compact model. In this study, to represent the energy level profile along the device channel direction into the Wentzel-Kramers-Brillouin approximation by substituting a parabolic function, we can analytically derive the expressions of the transmission coefficients for source-to-drain tunneling. In the subthreshold region, the source-to-drain tunneling current then can be evaluated using the Landauer formula. Finally, a fully analytic compact model is proposed for representing the drain current in all operating regions. The results compared with non-equilibrium Green's function transport simulations can be obtained in a good agreement.

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Phase-Based Quantification of Sports Performance Metrics Using a Smart IoT Sensor

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IEEE Internet of Things Journal 2023年第18期10卷 15900-15911页

作者： Chen, Meng Szu, Hui Fang Lin, Hsin Yen Liu, Yifan Chan, Ho-Yin Wang, Yufan Zhao, Yuliang Zhang, Guanglie Yao, Jeffrey Da-Jeng Li, Wen Jung National Tsing Hua University Physical Education Office Hsinchu City300 Taiwan Kla Corporation Tainan City744 Taiwan Michigan State University Department of Electronic and Computer Engineering East LansingMI48824 United States Shanghai Jiao Tong University School of Mechanical Engineering Department of Industrial Engineering and Management Shanghai200240 China Northeastern University at Qinhuangdao Hebei Key Lab. of Micro-Nano Prec. Optical Sensing and Msrmt. Technol. Sch. of Control Engineering Qinhuangdao066004 China City University of Hong Kong Department of Mechanical Engineering Kowloon Tong Hong Kong City University of Hong Kong Shenzhen Research Institute CASŰCityU Joint Laboratory for Robotics Shenzhen518057 China National Tsing Hua University Department of Power Mechanical Engineering Hsinchu City300 Taiwan

Sports performance is often judged based on the results of a series of motions rather than observing and analyzing the detailed sequential motions that lead to the results. Hence, subjective feedback from the coaches is often ineffective in improving player performance. In this work, we custom-built a smart Internet of Things wristband motion sensor to implement data-based sports performance evaluation. A phase-based feature selection method is also proposed to assess the athletes' sequential detailed motion for selected sport activities. To demonstrate the merits of this technology, we quantified the quality of the sequential motions of a specific type of volleyball serve by analyzing 183 samples of motion data obtained from a total of 18 players. The general skill levels (i.e., elite, subelite, and amateur) of the players were identified by machine learning algorithms, with accuracies of up to 95%. Moreover, we adopted biomechanical principles to extract 11 motion-related performance metrics from various phases of the players' serve motion. We identified the distributions of these metrics across different skill levels and found eight key metrics that were highly correlated to the skill level of a players. We suggest that these metric distributions can be used as a reference for providing feedback to the coaches and players, to improve a player's skill in the future. This phased-based analysis method can potentially be applied across many sports to increase the effectiveness of athletes' training. © 2014 IEEE.

关键词： Internet of things

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