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Micro and Nanotechnology for Power Generation and Energy Conversion Applications (PowerMEMS)

作者： Kaijun Lin Manjuan Huang Xiaowei Feng Zhenming Li Wei Liu Huicong Liu School of Mechanical and Electrical Engineering Jiangsu Provincial Key Laboratory of Advanced Robotics Soochow University Suzhou CHINA Energy Storage and Electrotechnics Department China Electric Power Research Institute Limited Company Beijing CHINA

ISBN: (数字)9798350380200

ISBN: (纸本)9798350380217

This paper presents an impact-induced frequency up-conversion piezoelectric energy harvester (FUC-PEH) to improve low-frequency output performance. The FUC-PEH includes a high-frequency piezoelectric cantilever (HFPC) with resonant frequency of 210 Hz and a low-frequency S-shaped stainless-steel cantilever (LFSC) with resonant frequency of 30 Hz. The HFPC is manufactured using MEMS metal-substrate lead zirconate titanate (PZT) thick film technology. The peak open-circuit voltage of FUC-PEH reaches 54.6 V over a drive frequency range of 10 to 60 Hz, which is $80 \%$ higher than that of a single HFPC in resonant state. It is expected to replace primary batteries and used as the power source for wireless sensor nodes. In addition, the low-frequency I-shaped stainless-steel cantilever (LFC-I), II-shaped cantilever (LFC-II) and III-shaped cantilever (LFC-III) are fabricated to explore the influence of the stiffness of low-frequency cantilever, the size of proof mass and the gap distance on the output performance of FUC-PEH.

关键词： Wireless communication Vibrations Wireless sensor networks Resonant frequency Voltage Bandwidth Thick films Resonance Lead zirconate titanate Testing

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BaSeNet: A Learning-based Mobile Manipulator Base Pose Sequence Planning for Pickup Tasks

BaSeNet: A Learning-based Mobile Manipulator Base Pose Seque...

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IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

作者： Lakshadeep Naik Sinan Kalkan Sune L. Sørensen Mikkel B. Kjærgaard Norbert Krüger SDU Robotics Mærsk Mc-Kinney Møller Institute (MMMI) Faculty of Engineering University of Southern Denmark Odense M Denmark Department of Computer Engineering and ROMER Robotics Center Middle East Technical University (METU) Ankara Turkey SDU Software Engineering Mærsk Mc-Kinney Møller Institute (MMMI) Faculty of Engineering University of Southern Denmark Odense M Denmark Danish Institute for Advanced Studies (DIAS) Odense M Denmark

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

In many applications, a mobile manipulator robot is required to grasp a set of objects distributed in space. This may not be feasible from a single base pose and the robot must plan the sequence of base poses for grasping all objects, minimizing the total navigation and grasping time. This is a Combinatorial Optimization problem that can be solved using exact methods, which provide optimal solutions but are computationally expensive, or approximate methods, which offer computationally efficient but sub-optimal solutions. Recent studies have shown that learning-based methods can solve Combinatorial Optimization problems, providing near-optimal and computationally efficient *** this work, we present BaSeNet - a learning-based approach to plan the sequence of base poses for the robot to grasp all the objects in the scene. We propose a Reinforcement Learning based solution that learns the base poses for grasping individual objects and the sequence in which the objects should be grasped to minimize the total navigation and grasping costs using Layered Learning. As the problem has a varying number of states and actions, we represent states and actions as a graph and use Graph Neural Networks for learning. We show that the proposed method can produce comparable solutions to exact and approximate methods with significantly less computation time. The code and Reinforcement Learning environments will be made available on the project webpage * .

关键词： Learning systems Navigation Grasping Reinforcement learning Manipulators Graph neural networks Computational efficiency Planning Optimization Intelligent robots

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Marker Correspondence Initialization in an IR Motion Capturing System

Marker Correspondence Initialization in an IR Motion Capturi...

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RSI/ISM International Conference on robotics and Mechatronics (ICROM)

作者： M. M. Kalantari R. Khorrambakht M. R. Dindarloo S. A. Khalilpour H. D. Taghirad P. Cardou Advanced Robotics and Automated Systems (ARAS) Faculty of Electrical Engineering K. N. Toosi University of Technology Tehran Iran Department of Mechanical Engineering Robotics Laboratory Laval University Quebec City Canada

ISBN: (纸本)9781665454537

Marker-based motion capturing (MoCap) systems are of great importance among the different visual referencing systems, because of their robustness, speed, and precision. Due to the lack of highly descriptive visual features in captured images in such systems, establishing the correspondences between the multi-view observations of the markers is a major challenge. This problem is even more challenging when there is no preceding or low reliable data on the markers’ positions. Under these conditions, the correspondences have to be found from a large space of possible matches. This paper aims to provide a solution for this correspondence initialization problem in multi-view tracking systems based on graph theory and Girvan-Newman community detection. The validity and robustness of the algorithm are verified via experimental analysis.

关键词： Visualization Mechatronics Tracking Reliability theory Robustness Graph theory Robots

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Research on Robot’s Understanding of Different Concepts and Autonomous Planning

Research on Robot’s Understanding of Different Concepts and...

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

作者： Bao Shi Yongsheng Ou Hongshen Zhao Kaimin Cao Degang Wang School of Control Science and Engineering Dalian University of Technology Dalian China Chinese Academy of Sciences Shenzhen Institutes of Advanced Technology Shenzhen China Robotics Laboratory China Nanhu Academy of Electronics and Information Technology China

ISBN: (数字)9798350372601

ISBN: (纸本)9798350372618

Robots have many significant advantages in understanding abstract concepts and collaborating autonomously with humans. These advantages can not only improve the generalization ability of robots, but also can be applied in industrial automation, health care, customer service and other fields. It will further have a profound impact in promoting the development of science and technology, improving production efficiency, and improving the quality of human life. Therefore, this paper explores robots’ understanding of abstract concepts and autonomous services for new tasks based on large language model (LLM). First, we use the ability of LLM to recognize world concepts to explore the implicit correlation between abstract task instructions and execution sequences, and build an autonomous planning framework (AutoPlanFrame-LLM). Then, apply the above-mentioned autonomous planning framework to new tasks to realize the robot’s understanding and generalization of new tasks. Finally, the method proposed in this article is tested based on a UR5 robot. Experiments show that the framework proposed in this article can help robots understand the requirements of abstract tasks and achieve autonomous services based on human needs in new tasks. Here, it should be noted that each task requirement given in this article is expressed in an abstract form to avoid generating too many hints of surface information in the text. In this way, it can not only increase the robot’s in-depth understanding of task instructions, but also help the robot understand and plan new task concepts.

关键词： Visualization Correlation Accuracy Service robots Large language models Production Real-time systems

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Future-Focused Control Barrier Functions for Autonomous Vehicle Control

Future-Focused Control Barrier Functions for Autonomous Vehi...

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American Control Conference (ACC)

作者： Mitchell Black Mrdjan Jankovic Abhishek Sharma Dimitra Panagou Department of Aerospace Engineering University of Michigan Ann Arbor MI USA Ford Research and Advanced Engineering Dearborn MI USA Dept. of Robotics and Dept. of Aerospace Engineering Univ. of Michigan Ann Arbor MI USA

In this paper, we introduce a class of future-focused control barrier functions (ff-CBF) aimed at improving traditionally myopic CBF based control design and study their efficacy in the context of an unsignaled four-way intersection crossing problem for collections of both communicating and non-communicating autonomous vehicles. Our novel ff-CBF encodes that vehicles take control actions that avoid collisions predicted under a zero-acceleration policy over an arbitrarily long future time interval. In this sense the ff-CBF defines a virtual barrier, a loosening of which we propose in the form of a relaxed future-focused CBF (rff-CBF) that allows a relaxation of the virtual ff-CBF barrier far from the physical barrier between vehicles. We study the performance of ff-CBF and rff-CBF based controllers on communicating vehicles via a series of simulated trials of the intersection scenario, and in particular highlight how the rff-CBF based controller empirically outperforms a benchmark controller from the literature by improving intersection throughput while preserving safety and feasibility. Finally, we demonstrate our proposed ff-CBF control law on an intersection scenario in the laboratory environment with a collection of 5 non-communicating AION ground rovers.

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A Resource Optimization Approach Based on Deep Integration of Vision-Motion System for Sustainable Agriculture

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IEEE Transactions on Consumer Electronics 2025年

作者： Cheng, Minghao Zhou, Nan Bhatti, Mughair Aslam Li, Di Wang, Shiyong Alasiry, Areej Marzougui, Mehrez South China University of Technology School of Mechanical and Automotive Engineering Guangzhou510640 China Peng Cheng Laboratory Department of Strategic and Advanced Interdisciplinary Shenzhen518000 China Department of Robotics and AI Pakistan King Khalid University College of ComputerScience Abha61413 Saudi Arabia

The integration of vision and motion systems represents a critical phase in the intelligent transformation of consumer electronics aimed at enhancing productivity. However, owing to the operational modes and distributional characteristics inherent in existing systems, achieving large-scale, stable, and consistent agricultural applications on consumer electronics remains a significant challenge. To address this problem, this paper proposes a unified resource optimization approach for different configurations of agricultural consumer electronics to achieve deep integration of vision and motion systems. The optimization is mainly at two levels: on the one hand, we design a velocity observer for the vision-motion integrated system represented by the visual servoing system, which makes native changes to the characteristics of the visual servoing’s non-real-time instruction issuance. By converting long-time commands with uncertain period to short-time commands with certain period, the design difficulty of real-time trajectory planning of the real underlying motion controller is simplified. On the other hand, in image-based visual servoing (IBVS) system, the mixture parameter of the image Jacobian matrix also affect the control performance of the visual servoing system. For most IBVS-based agricultural applications, there is a lack of a systematic approach to ensure that the mixture parameter is adaptively and continuously varied. To solve this problem, this paper proposes a fuzzy logic-based method to adaptively adjust this parameter and ensure its continuity by introducing a suitable membership function. The experimental results of visual servoing based on the consumer electronics show that our proposed method can significantly improve the integrated vision-motion controllability, and can trade-off the convergence efficiency and feature retention constraints to effectively improve the overall efficiency of the system operation. © 1975-2011 IEEE.

关键词： Visual servoing

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Kinematic and Dynamic Analysis of CPR-A: An Aerial Cable Suspended Parallel Robot

Kinematic and Dynamic Analysis of CPR-A: An Aerial Cable Sus...

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RSI/ISM International Conference on robotics and Mechatronics (ICROM)

作者： A. Rashvand Ehsan Damghani H. D. Taghirad Advanced Robotics and Automated Systems (ARAS) Faculty of Electrical Engineering K.N. Toosi University of Technology Tehran Iran Faculty of Mechanical Engineering K.N. Toosi University of Technology Tehran Iran

This paper presents a comprehensive analysis of the kinematics, dynamics, and inverse dynamic control of the Cable-Suspended Parallel Robot (CPR-A). The CPR-A system is a cable-driven robot employing two ropes fixed at the upper corners of a 3D workspace. By controlling the angular positions of three motors, the robot can precisely manipulate the motion of a camera carrier in Cartesian space. The study defines the desired trajectory of the camera’s motion and analyzes the system’s kinematics. The inverse kinematics problem is solved, and a closed-form solution for forward kinematics is given, contributing to the novelty of this research. The paper investigates the Jacobian analysis, which is essential for understanding the relationship between joint variable velocities and the robot’s end-effector motion. The dynamic analysis focuses on deriving the mass matrix, Coriolis and centrifugal, and gravity vectors for the CPR-A system. The study incorporates the mass of cables to achieve more accurate dynamics results. Furthermore, the implications of inverse dynamic control in shaping error free tracking performances are explored. Simulation results validate the analytical solutions, showcasing accurate tracking of desired trajectories.

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Deeper Introspective SLAM: How to Avoid Tracking Failures Over Longer Routes?

Deeper Introspective SLAM: How to Avoid Tracking Failures Ov...

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IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

作者： Kanwal Naveed Muhammad Latif Anjum Wajahat Hussain Donghwan Lee Robotics & Machine Intelligence (ROMI) Lab School of Electrical Engineering and Computer Science (SEECS) National University of Sciences and Technology Islamabad Pakistan Reinforcement Learning Research Lab School of Electrical Engineering Korea Advanced Institute of Science and Technology (KAIST) Daejeon South Korea

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

Large scale active exploration has recently revealed limitations of visual SLAM’s tracking ability. Active view planning methods based on reinforcement learning have been proposed to improve visual tracking *** this work, we expose the limitations of deep reinforcement learning-based visual SLAM over longer routes. We demonstrate that additional modalities (depth, scene layout) offer little improvement. Furthermore, reward shaping is not the main reason behind the shortsightedness of the state-of-the-art visual SLAM tracker. We propose a novel video vision transformer-based architecture that improves the farsightedness of the visual tracker, which results in the completion of longer routes with efficient *** of 60 challenging routes, our approach manages to complete 56 routes, which is a three-fold improvement over the state-of-the-art active view mapping (DI-SLAM) baseline. Interestingly, ORB-SLAM3 was unable to complete a single route without tracking failure. Our code is available at https://***/w935spuz.

关键词： Visualization Simultaneous localization and mapping Codes Layout Transformers Deep reinforcement learning Robustness Planning Intelligent robots

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Forward Kinematics Development of a 3-RRS Parallel Manipulator for Real-Time Control

Forward Kinematics Development of a 3-RRS Parallel Manipulat...

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RSI/ISM International Conference on robotics and Mechatronics (ICROM)

作者： S. Ali A. Moosavian Omid Mahdizadeh Sina Hallajian Sara Ashrafi Mohammad Jamali Vahid Akbari Department of Mechanical Engineering Center of Excellence in Robotics and Control Advanced Robotics and Automated Systems (ARAS) Lab. K. N. Toosi University of Technology Tehran Iran

ISBN: (纸本)9781665454537

In control of parallel robots, forward kinematics calculation is mainly required. In some studies, obtained equations are solved numerically with massive calculations that is not acceptable for control implementations. This paper introduces a new method to extract forward kinematics for a 3- RRS robot. This method calculates the kinematics of passive joints with two separated equations, which can be solved to decrease the total computation demands. Also, a new weight compensation mechanism is proposed to improve the dynamic response by a linear pneumatic actuator placed between the ground and the end-effector. On the other hand, to use various control algorithms, the position of the rolling ball on the end- effector (moving platform) must be measured. This is performed using Convolutional Neural Networks (CNNs) as image processing algorithms. Since the system must work quickly for a high-frequency task, the proposed image processing algorithm can provide the desired fast feedback. Experimental results reveal the merits of the above-described proposed modules.

关键词： Pneumatic actuators Image processing Heuristic algorithms Kinematics Position measurement Pneumatic systems Mathematical models

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Mode-switching single-pixel imaging via a high-performance perovskite-Si dual-mode photodetector

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Photonics Research 2024年第12期12卷 2873-2880页

作者： YUJIN LIU DONGXU LIN JINGYANG XING HANYAN ZHAO HONGLING WAN HAO WANG ZHONG JI XUELI CHEN Innovation Center for Advanced Medical Imaging and Intelligent Medicine Guangzhou Institute of TechnologyXidian UniversityGuangzhou 510555China Shenzhen Key Laboratory of Intelligent Robotics and Flexible Manufacturing Systems Department of Mechanical and Energy EngineeringSUSTech Energy Institute for Carbon NeutralitySouthern University of Science and TechnologyShenzhen 518055China Center for Biomedical-Photonics and Molecular Imaging Advanced Diagnostic-Therapy Technology and Equipment Key Laboratory of Higher Education Institutions in Shaanxi ProvinceSchool of Life Science and TechnologyXidian UniversityXi’an 710126China

Visible–near-infrared(VIS-NIR)dual-mode imaging can expand the human perception ***,the development of dual-mode image sensors is still challenging due to complex fabrication processes and readout circuit ***,we design a simple-structured(perovskite-Au/Si/Ag)dual-mode *** unique asymmetric electrode design allows the device to support two operating modes at zero *** device exhibits a detection range covering 400–1100 nm under top illumination mode,with a peak specific detectivity of up to 5.56×1013 *** bottom illumination mode,the device demonstrates pronounced narrowband NIR response *** importantly,we develop a dual-mode single-pixel imaging system based on this device,bypassing the fabrication processes of high-density array image *** system exhibits excellent VISNIR dual-mode imaging results,effectively separating NIR and VIS information and enhancing infrared details in the fused ***,we discover that the system can effectively suppress ringing artifacts,achieving infrared information perception at a low sampling rate,which can accelerate the imaging speed by∼16 times(reduced from∼3.2 s to∼0.2 s).Our proposed dual-mode single-pixel imaging technology offers new means for material identification and intelligent perception.

关键词： mode illumination details

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