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Cam Profile Optimization for a Piezoelectric-Based Sole Energy Harvester

Cam Profile Optimization for a Piezoelectric-Based Sole Ener...

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2024 IEEE International Conference on Robotics and Biomimetics, ROBIO 2024

作者： Liao, Haisu Ren, Zhongliang Wang, Yidi Wu, Xinyu Gao, Fei Southern University of Science and Technology Shenzhen518005 China Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Guangdong Provincial Key Laboratory of Robotics and Intelligent System Shenzhen518055 China Guangdong-Hong Kong-Macao Joint Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen518055 China

ISBN: (纸本)9781665481090

Harvesting energy from the human body to extend the operational time for low-power has gained significant attention. Recently, researchers have focused on biomechanical energy harvesting from human feet while walking. This paper presents an optimization of the cam profile for a piezoelectric-based sole energy harvester designed to be worn on the bottom of shoes to power electronic devices. Specifically, cams with linear polynomial and exponential functions were designed to actuate the piezoelectric transducers (PZTs). Force analysis revealed that the exponential function cam induces more significant deformation in the PZTs than the linear polynomial cam. Preliminary tests on a healthy subject validated this design, showing that the exponential function cam produced an average output power of 0.16mW at a walking speed of 5.5 km/h, indicating a 78% improvement over the linear polynomial cam. Moreover, the optimization rate increased with the growing walking speed. © 2024 IEEE.

关键词： Piezoelectric transducers

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Redundant-Manipulator Minimal Motion via Different-Precision Discrete-Time Zhang Neural Dynamics Algorithms Especially Ten-Instant One

Redundant-Manipulator Minimal Motion via Different-Precision...

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2021 China Automation Congress, CAC 2021

作者： Tang, Zanyu Guo, Jinjin Chen, Jianrong Zhang, Yunong School of Computer Science and Engineering Sun Yat-sen University Guangzhou China Jishou University Jishou China Guangdong Key Laboratory of Modern Control Technology Guangzhou China School of Public Health and Management Youjiang Medical University for Nationalities Baise China Key Laboratory of Machine Intelligence and Advanced Computing Ministry of Education Guangzhou China

ISBN: (纸本)9781665426473

As a significant and basic robotic sub-topic, the problem of optimal MPC (motion planning & control) of ordinarily redundant manipulator widely exists in many fields, such as industry and daily-life applications. Following previous work, the aim of this paper is at solving the problem of velocity-level minimal joint motion planning & control (VLMJMPC) in a way of discrete time. Firstly, the VLMJMPC problem is introduced and analyzed using Zhang neural dynamics (ZND) method, and the motion scheme is then given. Secondly, by using ZND and Lagrange-multiplier methods, a continuous-time (CT) model for real-time solving the problem is established. In order to realize on digital computers, we use a ten-instant Zhang time discretization (abbreviated as ZTD) general formula with the fifth-order precision to discretize the model, and a special algorithm with high precision is derived, developed and analyzed. Finally, five discrete-time ZND (DTZND) algorithms are further acquired by adopting this ten-instant ZTD formula and other ZTD formulas, and the corresponding theoretical analyses are given. Computer experiment results numerically verify the online effectiveness and correctness of the developed five DTZND algorithms. © 2021 IEEE

关键词： Redundant manipulators

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Lightweight Vision Transformer for Small Data Sets 38

Lightweight Vision Transformer for Small Data Sets

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38th Youth Academic Annual Conference of Chinese Association of Automation, YAC 2023

作者： Fang, Wenxing Su, Yanxu Institutes of Physical Science and Information Technology Anhui University Hefei China School of Artificial Intelligence Anhui University Hefei230601 China Southeast University Key Laboratory of Measurement and Control of Complex System of Engineering Ministry of Education Nanjing210096 China

ISBN: (纸本)9798350303636

With the rapid development of Transformers in the field of computer vision, models based on Transformers have become highly competitive architectures in the area. Although variants of Transformer models have achieved increasing accuracy on image classification tasks, the size of the training set and the number of parameters required by the models have increased dramatically. When dealing with small datasets, such models face problems such as overfitting and undergeneralization, leading to poor accuracy on the test set. We propose a new lightweight vision transformer (LVT) to address these issues. We reconstructed the backbone network, which learns the relationship between pixels through local window self-attention and global self-attention computation. We also use the attention pooling approach to fuse the token sequences generated by the backbone network more meticulously. We trained on the CIFAR-10 and CIFAR-100 datasets from scratch and compared them with a modern convolutional neural network. The experimental results show that LVT outperforms the modern convolutional neural network in terms of accuracy and efficiency. On the test set of CIFAR-10, we have obtained an accuracy of 96.83%, which indicates that our model can effectively solve the problems facing the training of small datasets and has a wide range of application prospects. © 2023 IEEE.

关键词： lightweight pooling self-attention windows

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Obstacle avoidance of manipulators based on improved artificial potential field method

Obstacle avoidance of manipulators based on improved artific...

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2019 IEEE International Conference on Robotics and Biomimetics, ROBIO 2019

作者： Li, Hao Wang, Zhiyang Ou, Yongsheng Chinese Academy of Sciences Shenzhen Institutes of Advanced Technology Shenzhen518055 China University of Chinese Academy of Sciences Beijing100049 China Guangdong Provincial Key Laboratory of Robotics and Intelligent System Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences China CAS Key Laboratory of Human-Machine Intelligence-Synergic Systems Shenzhen Institutes of Advanced Technology China

ISBN: (纸本)9781728163215

Obstacle avoidance is a key problem of robot motion planning. This paper introduces an improved method to realize obstacle avoidance of manipulators based on artificial potential field method which offers a relatively fast and effective way to solve the problem. We establish the attractive potential field function of the goal and the repulsive potential filed functions of obstacles in the workspace instead of the configuration space. Then a series of control points on the manipulator are chosen to be influenced by the total potential. A policy is proposed that only the end point is attracted to the goal while all selected points are repulsed by obstacles. Afterwards, we transfer the potential force of each point in workspace into the moment in configuration space to make the manipulator move by iteration of joint angles. The effectiveness of the method is confirmed by simulation experiments. © 2019 IEEE.

关键词： Motion planning

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Improved Capon Estimator for High-Resolution DOA Estimation and Its Statistical Analysis

Improved Capon Estimator for High-Resolution DOA Estimation ...

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作者： Zuo, Weiliang Xin, Jingmin Liu, Changnong Zheng, Nanning Sano, Akira National Engineering Research Center for Visual Information and Applications Institute of Artificial Intelligence and Robotics Xi'An Jiaotong University National Key Laboratory of Human-Machine Hybrid Augmented Intelligence Xi'an710049 China Data Center China Construction Bank Beijing100033 China Keio University Department of System Design Engineering Yokohama223-8522 Japan

Despite some efforts and attempts have been made to improve the direction-of-arrival (DOA) estimation performance of the standard Capon beamformer (SCB) in array processing, rigorous statistical performance analyses of these modified Capon estimators are still lacking. This paper studies an improved Capon estimator (ICE) for estimating the DOAs of multiple uncorrelated narrowband signals, where the higher-order inverse (sample) array covariance matrix is used in the Capon-like cost function. By establishing the relationship between this nonparametric estimator and the parametric and classic subspace-based MUSIC (multiple signal classification), it is clarified that as long as the power order of the inverse covariance matrix is increased to reduce the influence of signal subspace components in the ICE, the estimation performance of the ICE becomes equivalent to that of the MUSIC regardless of the signal-to-noise ratio (SNR). Furthermore the statistical performance of the ICE is analyzed, and the large-sample mean-squared-error (MSE) expression of the estimated DOA is derived. Finally the effectiveness and the theoretical analysis of the ICE are substantiated through numerical examples, where the Cramer-Rao lower bound (CRB) is used to evaluate the validity of the derived asymptotic MSE expression. © 2014 Chinese Association of Automation.

关键词： Multiple signal classification

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Review of machine-vision-based plant detection technologies for robotic weeding

Review of machine-vision-based plant detection technologies ...

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2019 IEEE International Conference on Robotics and Biomimetics, ROBIO 2019

作者： Li, Nan Zhang, Xiaoguang Zhang, Chunlong Ge, Luzhen He, Yong Wu, Xinyu Chinese Academy of Sciences Guangdong Provincial Key Laboratory of Robotics and Intelligent System Shenzhen Institutes of Advanced Technology Shenzhen518055 China CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen Institutes of Advanced Technology Shenzhen518055 China Shenzhen University Shenzhen518060 China China Agricultural University College of Engineering Beijing100083 China

ISBN: (纸本)9781728163215

controlling weeds with reduced reliance on herbicides is one of the main challenges to move toward a more sustainable agriculture. Robotic weeding is a thought to be a viable way to reduce the environmental loading of agrochemicals while keeping the operation efficiency high. One of the key technologies for performing robotic weeding is automatic detection of crops and weeds in fields. This paper presents an overview on various methods for detecting plants based on machine vision, mainly concentrating on two main challenges: dealing with changing light and crop/weed discrimination. To overcome the first challenge, both physical and algorithmic methods have been proposed. Physical methods can result in a more cumbersome machine while algorithmic methods are less robust. For crop/weed discrimination, deep-learning-based methods have shown obvious advantages over traditional methods based on hand-crafted features. However, traditional methods still hold some merits that can be leveraged to deep-learning-based methods. With the fast development of hardware technologies, researchers should take full advantage of advanced hardware to ease the algorithm design. In the future, the identification of crops and weeds can be more accurate and fine-grained with the support of online databases and computing resources based on the advances in artificial intelligence and communication technologies. © 2019 IEEE.

关键词： Crops

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Obstacle avoidance with reinforcement learning and adaptive resonance theory

Obstacle avoidance with reinforcement learning and adaptive ...

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2019 IEEE International Conference on Robotics and Biomimetics, ROBIO 2019

作者： Ye, Lingjian Zhou, Yimin Chinese Academy of Sciences Shenzhen Institutes of Advanced Technology Shenzhen518055 China Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences China CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen Institutes of Advanced Technology Shenzhen China

ISBN: (纸本)9781728163215

The reinforcement learning (RL) of the autonomous mobile agent is one of the actual research topics. It permits mobile agents to interact constantly with their environment and to avoid obstacles. First, this paper presents an algorithm which integrates Deep Deterministic Policy Gradient (DDPG) algorithm and Fuzzy Adaptive Resonance Theory (ART) in order to improve generalization performance of RL. Then the curiosity is introduced to integrate with the first proposed algorithm to solve the problem of slow convergence caused by Fuzzy ART. Results of the simulation experiments demonstrate the effectiveness of the proposed algorithm. It shows that the algorithms perform well in both low-dimension and high-dimension state space. © 2019 IEEE.

关键词： Reinforcement learning

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A differential public PUF design for lightweight authentication 16

A differential public PUF design for lightweight authenticat...

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2021 International Conference on Synthesis, Modeling, Analysis and Simulation Methods and Applications to Circuit Design, SMACD 2021 and 16th Conference on PhD Research in Microelectronics and Electronics, PRIME 2021

作者： Duan, Shengyu Sai, Gaole School of Computer Engineering and Science Shanghai University Shanghai200444 China State Key Laboratory of Computer Architecture Institute of Computing Technology Chinese Academy of Sciences China Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences China CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen Institutes of Advanced Technology China

ISBN: (纸本)9783800755899

Physical Unclonable Functions (PUFs) have emerged as a promising primitive to provide a hardware keyless security mechanism for integrated circuit applications. Public PUFs (PPUFs) address the crucial PUF vulnerability of requiring databases to store the secrete reference information. This paper investigates one of the PPUF families, differential PPUF (dPPUF), which exploits complexly interacted logic to create time gap between actual execution and simulation, and to prevent simulation attacks. Conventional dPPUFs have high costs. We observe the repressers have large impact on simulation time, but take a great proportion in current dPPUF structure. We thereby present a represser network with specially designed interconnection and shared logic, to maintain a high circuit complexity and to reduce the area cost. We show the proposed dPPUF has similar resilience over simulation attacks as the conventional design. Area cost can be reduced by up to 44%, and thus the proposed design can be used for lightweight authentication. © VDE VERLAG GMBH.

关键词： Authentication

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Hierarchical Roadmap Based Rapid Path Planning for High-DOF Mobile Manipulators in Complex Environments

Hierarchical Roadmap Based Rapid Path Planning for High-DOF ...

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2009 IEEE International Conference on Robotics and Biomimetics(2009 IEEE 机器人与仿生技术国际会议 ROBIO 2009)

作者： Hong Liu He Wen Yan Li Jingyan Xia Tianguang Chu Key Laboratory of Machine Perception and Intelligence and the Key Laboratory of Integrated Micro-sys Key Laboratory of Integrated Microsystem Shenzhen Graduate SchoolPeking UniversityShenzhen 518055 Intelligent Control Laboratory Center for Systems and ControlDepartment of Industrial Engineering a

ISBN: (纸本)9781424447749;9781424447756

The Probabilistic Roadmap method (PRM) has been widely used in the field of robot path planning and based on it, a great number of variants have been developed addressing for different purposes, e.g. the Lazy PRM method, the Dynamic Roadmap (DRM) method, and the Dynamic Bridge Builder method (DBB). In this paper, PRM is extended as well-a hierarchical roadmap based rapid path planner is presented, which combines DRM with DBB to achieve good planning performance in environments including moveable obstacles. Through observation, we find that how to determine precise location of a robot's end-effector is quite important for nearly all practical planning tasks. Moreover, the workspace that can be swept by its end-effector determines scope of action of a robot. In consideration of the safety factor, the velocity of planning should be limited. Accordingly, its scope of action must be limited during a certain time interval, as well. In this paper, a hierarchy sampling strategy oriented towards the end-effector position is employed. Initially only a fundamental global roadmap is constructed and visible. Then the scope of a manipulator, called manipulator space in this paper, is computed. Moveable obstacles lying inside the manipulation space are used to update the global roadmap and activate other two layers of nodes with Dynamic Bridge Builder. The approach has been implemented and tested in simulation, and results show that it meets the real-time demand well.

关键词： Path planning NIH Roadmap Initiative tag Road maps Robot TWO-LAYER power bridge Time intervals end effectors Factor of safety Environments Mobile manipulator Construction Workers

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AADL and Modelica model combination and model conversion based on CPS 4

AADL and Modelica model combination and model conversion bas...

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4th International Conference on Electronic Information Technology and Computer Engineering, EITCE 2020

作者： Zhu, Yifeng Cao, Zining Wang, Fujun Lu, Weiwei College of Computer Science and Technology Nanjing University of Aeronautics and Astronautics Nanjing China College of Computer Science and Technology Collaborative Innovation Center of Novel Software Technology and Industrialization Miit Key Laboratory of Pattern Analysis and Machine Intelligence Luoyang China Science and Technology on Electro-optic Control Laboratory Luoyang China

ISBN: (纸本)9781450387811

Cyber-Physical system (CPS), which realizes the close integration of physical resources and information resources, is a distributed and asynchronous dynamic hybrid system running in different time and space. In this paper, we use AADL to model information system and use Modelica to model physical system. However, they are all semi-formal models such that we cannot do future work about formal verification. To overcome this defect, we convert them to formal models like automaton through conversion algorithms and rules. Due to the fact of probabilistic events and resource consumption in CPS, this paper adopts the weighted probabilistic hybrid automaton as formal model, and adds the properties of probability and weight to the behavior annex of AADL. Then we conduct the rule and algorithm of the model conversion. In order to ensure consistency of further work about model checking, the paper prove the equivalence of the two models by bisimulation. Finally, the capability of modeling of the extended modeling language of AADL and the significance of conversion to automaton is illustrated by the aircraft system. © 2020 ACM.

关键词： Cyber Physical system

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