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

作者： Danial Ansari S Ali A Moosavian Department of Mechanical Engineering Center of Excellence in Robotics and Control Advanced Robotics & Automated Systems (ARAS) Laboratory K. N. Toosi University of Technology Tehran Iran

In this research, the issue of trajectory tracking in task space of a robotic arm with rotational joints has been solved. For this purpose, a non-model based controller the modified jacobian-transpose is used which it’s performance has been improved by reinforcement learning. Traditionally, the settings of the error thresholds for this controller will require trial and error, but in this algorithm, reinforcement learning is used to adjust these parameters online and according to the conditions. The simulations for the desired trajectory indicate that the improvement of the trajectory tracking achieved by using proposed algorithm. Also, the superiority of this controller in noisy conditions compared to the reference Jacobian transpose controller has been shown.

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Simulator Design Using a General Purpose PC and Off-The-Shelf Interface Boards for GNSS/INS Integrated Navigation System 23

Simulator Design Using a General Purpose PC and Off-The-Shel...

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23rd International Conference on Control, Automation and systems, ICCAS 2023

作者： Son, Jae Hoon Lee, Yeong Hye Jurug, Junwoo Hwang, Yongtaek Hwang, Jiwoo Kim, Minsu Park, Gyeongmin Park, JunMin Yoo, Hoyoung Park, Chansik Oh, Sang Heon Lee, Sang Jeong Hwang, Dong-Hwan Chungnam National University Department of Electronics Engineering Daejeon34134 Korea Republic of Chungbuk National University Department of Intelligent Systems & Robotics Daejeon27867 Korea Republic of Microinfinity Co. Ltd. Advanced Technology Laboratory Daejeon34012 Korea Republic of

ISBN: (纸本)9788993215274

When a navigation systems are developed, lots of tests have to be performed. If a simulator is available which can generate signal and data of real environment, huge amount of time and cost can be reduced for development. In this paper, a simulator design method is proposed for GNSS/INS integrated navigation system using a general-purpose PC and OTS interface boards. In order to verify the proposed design method, a simulator of GPS L1 C/A and HG1700AG58 is implemented using a PC with intel i7-8700 CPU, USRP 2952-R, PCI-1780U-AE, FSCC/4-PCIe and LabVIEW2015. The implementation results show that GNSS signal and IMU data can be used for GNSS/INS integrated navigation system design. © 2023 ICROS.

关键词： Design

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Brain-Conditional Multimodal Synthesis: A Survey and Taxonomy

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2025年第5期6卷 1080-1099页

作者： Mai, Weijian Zhang, Jian Fang, Pengfei Zhang, Zhijun South China University of Technology School of Automation Science and Engineering Guangzhou510640 China Southeast University School of Computer Science and Engineering Nanjing210096 China South China University of Technology Key Library of Autonomous Systems and Network Control Ministry of Education The School of Automation Science and Engineering Guangzhou510640 China Institute for Super Robotics Huangpu Guangzhou510555 China Nanchang University Jiangxi Thousand Talents Plan Nanchang330031 China Jishou University College of Computer Science and Engineering Jishou416000 China Guangdong Artificial Intelligence and Digital Economy Laboratory Pazhou Lab Guangzhou510335 China Shaanxi University of Technology Shaanxi Provincial Key Laboratory of Industrial Automation School of Mechanical Engineering Hanzhong723001 China Changsha Normal University School of Information Science and Engineering Changsha410100 China Guangdong University of Petrochemical Technology School of Automation Science and Engineering Institute of Artificial Intelligence and Automation Maoming525000 China

In the era of artificial intelligence generated content (AIGC), conditional multimodal synthesis technologies (e.g., text-to-image) are dynamically reshaping the natural content. Brain signals, serving as potential reflections of how the brain interprets external information, exhibit a distinctive one-to-many correspondence with various external modalities. This correspondence makes brain signals emerge as a promising guiding condition for multimodal synthesis (e.g., image, text, and audio), which is crucial for developing practical brain–computer interface systems and unraveling complex mechanisms underlying human perception. This survey comprehensively examines the emerging field of brain-conditional multimodal synthesis, termed AIGC-brain, to delineate the current landscape and future directions. To begin, related neuroimaging datasets and generative models are introduced as the foundation of AIGC-brain decoding and analysis. Next, we present a comprehensive taxonomy according to AIGC-brain methodologies, followed by task-specific representative work and implementation details to facilitate in-depth comparison and analysis. Quality assessments are then introduced for both qualitative and quantitative evaluation. Finally, this survey explores insights gained, outlining current challenges and prospects of AIGC-brain. As a pioneering survey, this article paves the way for future advances in AIGC-brain research. © 2020 IEEE.

关键词： Taxonomies

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A Search Strategy and Vessel Detection in Maritime Environment Using Fixed-Wing UAVs

A Search Strategy and Vessel Detection in Maritime Environme...

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International Symposium on Underwater Technology

作者： Marijana Peti Ana Milas Natko Kraševac Marko Križmančić Ivan Lončar Nikola Mišković Stjepan Bogdan Laboratory for Robotics and Intelligent Control Systems (LARICS) Faculty of Electrical Engineering and Computing University of Zagreb Zagreb Croatia Laboratory for Underwater Systems and Technologies (LABUST) Faculty of Electrical Engineering and Computing University of Zagreb Zagreb Croatia

In this paper, we address the problem of autonomous search and vessel detection in an unknown GNSS-denied maritime environment with fixed-wing UAVs. The main challenge in such environments with limited localization, communication range, and the total number of UAVs and sensors is to implement an appropriate search strategy so that a target vessel can be detected as soon as possible. Thus we present informed and non-informed methods used to search the environment. The informed method relies on an obtained probabilistic map, while the non-informed method navigates the UAVs along predefined paths computed with respect to the environment. The vessel detection method is trained on synthetic data collected in the simulator with data annotation tools. Comparative experiments in simulation have shown that our combination of sensors, search methods and a vessel detection algorithm leads to a successful search for the target vessel in such challenging environments.

关键词： Location awareness Navigation Annotations Computational modeling Search problems Probabilistic logic Sensors

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A Portable and Integrated Traveling-Wave Electroosmosis Microfluidic Pumping System Driven by Triboelectric Nanogenerator

SSRN

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SSRN 2024年

作者： Zhou, Jian Tao, Ye Liu, Weiyu Sun, Tie Wu, Fangyu Shi, Changrui Ren, Yukun State Key Laboratory of Robotics and Systems Harbin Institute of Technology Harbin150001 China School of Electronics and Control Engineering Chang'an University Xi’an710064 China

The lab-on-a-chip system can simultaneously complete the preparation, reaction, separation, and detection of samples on a centi-scale platform by manipulating trace fluids. Traveling-wave electroosmosis (TWEO) technology, with the merit of electric signal-based flexible control over the fluid behavior, can achieve precise driving of fluids, which is an important requirement of the lab-on-a-chip system. However, the peripheral power equipment such as function generator required for TWEO limits the application in some occasions lacking power supply facilities, due to its large size and high cost. In this paper, we developed a brand-new portable and integrated TWEO microfluidic pumping system, wherein a front-end module of triboelectric nanogenerator (TENG) is in serial connection with the back-end microfluidic pumping chip, which greatly improves portability and reduces costs. The TENG can output a stable four consecutively 90°-phase-shifted alternating current voltage signals in a continuous rotational motion originated by its novel electrode structure. And the four-phase traveling potential waves are applied to four sets of electrode strips alternately distributed in the microchannel and thereby induce nonlinear electroosmotic slip on the electrode surface. Compared with traditional mechanical pumps, this system achieves stable pumping of electrolyte in the microchannel, but also realizes the almost instantaneous start, stop, and directional switching in response to a turn on, turn off, and turn in reverse of TENG, respectively. Finally, this system is integrated into a droplet microfluidic chip for the efficient fabrication of single emulsion droplets. This study presents a promising solution for the miniaturization, integration, and commercialization of lab-on-a-chip system. © 2024, The Authors. All rights reserved.

关键词： Lab-on-a-chip

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Sensor Placement Optimization using Random Sample Consensus for Best Views Estimation

Sensor Placement Optimization using Random Sample Consensus ...

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IEEE International Conference on Autonomous Robot systems and Competitions (ICARSC)

作者： Carlos M. Costa Germano Veiga Armando Sousa Ulrike Thomas Luís Rocha Centre for Robotics in Industry and Intelligent Systems of INESC TEC Portugal Faculty of Engineering of the University of Porto Portugal Robotics and Human Machine Interaction Laboratory Technical University of Chemnitz Germany

The estimation of a 3D sensor constellation for maximizing the observable surface area percentage of a given set of target objects is a challenging and combinatorial explosive problem that has a wide range of applications for perception tasks that may require gathering sensor information from multiple views due to environment occlusions. To tackle this problem, the Gazebo simulator was configured for accurately modeling 8 types of depth cameras with different hardware characteristics, such as image resolution, field of view, range of measurements and acquisition rate. Later on, several populations of depth sensors were deployed within 4 different testing environments targeting object recognition and bin picking applications with increasing level of occlusions and geometry complexity. The sensor populations were either uniformly or randomly inserted on a set of regions of interest in which useful sensor data could be retrieved and in which the real sensors could be installed or moved by a robotic arm. The proposed approach of using fusion of 3D point clouds from multiple sensors using color segmentation and voxel grid merging for fast surface area coverage computation, coupled with a random sample consensus algorithm for best views estimation, managed to quickly estimate useful sensor constellations for maximizing the observable surface area of a set of target objects, making it suitable to be used for deciding the type and spatial disposition of sensors and also guide movable 3D cameras for avoiding environment occlusions.

关键词： Sensor placement Three-dimensional displays Sociology Estimation Robot sensing systems Cameras Statistics

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Noise-Optimized Signal Processing for TENG-Based Touch Sensing Using I2C Integrated Circuits

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IEEE Sensors Journal 2025年

作者： Moger, Gourav Kakim, Alibek Mubarak, Assem Bushanov, Yersaiyn Kalimuldina, Gulnur Yeshmukhametov, Azamat Nazarbayev University Department of Robotics Engineering Astana Kazakhstan Nazarbayev University School of Engineering and Digital Sciences Department of Mechanical and Aerospace Engineering Astana Kazakhstan LLP MiraiTech Astana Kazakhstan Nazarbayev University Institute of Smart Systems and Artificial Intelligence Advanced Robotics and Mechatronics System laboratory Astana Kazakhstan

Triboelectric nanogenerator (TENG) sensors efficiently convert mechanical stimuli into electrical signals, making them well-suited for touch sensing due to their high sensitivity, durability, and self-powered operation. However, conventional signal acquisition methods introduce noise, affecting measurement accuracy. This paper presents a compact, Inter-Integrated Circuit (I2C)-based signal processing circuit designed to enhance signal fidelity while minimizing noise interference. The system’s performance was evaluated by analyzing sensor response across varying contact areas (50 mm² to 576 mm²) and drop heights, demonstrating a consistently high signal-to-noise ratio (SNR) across impact conditions. A high-frequency impact experiment further confirmed the PCB’s ability to distinguish sensor output from noise. Comparison with direct analog acquisition showed a significant enhancement in SNR, validating the PCB’s effectiveness in noise reduction. The system exhibited a rise time of 3.27 milliseconds, ensuring rapid detection of mechanical stimuli. Additionally, the measured latency of 88.9 ms between impact and signal detection falls within acceptable limits for realtime applications. These results establish the proposed PCB-based signal processing method as a practical solution for improving TENG sensor performance in touch-sensing applications requiring high accuracy and noise resilience. The compact, low-power design further enhances its suitability for integration into wearable electronics, interactive surfaces, and space-constrained systems where conventional bulky processing units are impractical. © 2001-2012 IEEE.

关键词： Network coding

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Dynamic Identification for a Manipulator Model based on Stribeck Friction using the Quasi-Newton Iterative Method

Dynamic Identification for a Manipulator Model based on Stri...

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2023 IEEE International Conference on robotics and Biomimetics, ROBIO 2023

作者： Xiao, Feng Zhang, Feilong Han, Bing Zhang, Hualiang Shenyang University of Technology School of Information Science and Engineering Shenyang110870 China University of Chinese Academy of Sciences Beijing100049 China Shenyang Institute of Automation Chinese Academy of Sciences Key Laboratory of Networked Control Systems Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110169 China School of Mechanical Engineering Zhejiang University State Key Laboratory of Fluid Power and Mechatronic Systems Hangzhou310027 China

ISBN: (纸本)9798350325706

The performance of dynamic control is intimately tied to modeling accuracy. However, traditional estimation methods and friction models, such as the least squares method and the Coulomb plus viscous model, fail to reflect the actual characteristics accurately. Particularly, the linear nature of the Coulomb plus viscous model overlooks the nonlinear static features of joint friction at slower velocities. To improve the rationality of the model structure, we integrate the Stribeck friction model into the Coulomb plus viscous model. However, introducing such nonlinearities compromises the applicability of the least squares method. As a countermeasure, we propose a new strategy that combines the least square method and the Quasi-Newton iterative method to identify the parameters of the modified nonlinear model. Additionally, the design of the excitation trajectory is critical to achieve high identification accuracy. We utilized the inverse of the smallest singular value of the observation matrix as the objective function. By minimizing it with the interior point method, we generate the excitation trajectory well-suited to stimulate dynamic characteristics. Then we leverage the discrepancies between the measured and estimated torques to assess the precision of the dynamic parameters of the manipulator. Remarkably, our proposed algorithm reduces the mean absolute error of the estimated torque by over 20.40%. Finally, an experiment of the industrial manipulator by hand guiding grab and drag is performed and shows that the proposed approach can provide the manipulator with comprehensive torque compensation. © 2023 IEEE.

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NA-CPG: A robust and stable rhythm generator for robot motion control

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Biomimetic Intelligence & robotics 2022年第4期2卷 30-38页

作者： Ru Tong Changlin Qiu Zhengxing Wu Jian Wang Min Tan Junzhi Yu State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049China Department of Advanced Manufacturing and Robotics College of EngineeringPeking UniversityBeijing 100871China

Central pattern generators(CPGs)have been widely applied in robot motion control for the spontaneous output of coherent periodic ***,the underlying CPG network exhibits good convergence performance only within a certain range of parameter spaces,and the coupling of oscillators affects the network output accuracy in complex topological ***,CPGs may diverge when parameters change drastically,and the divergence is irreversible,which is catastrophic for the control of robot ***,normalized asymmetric CPGs(NA-CPGs)that normalize the amplitude parameters of Hopf-based CPGs and add a constraint function and a frequency regulation mechanism are ***-CPGs can realize parameter decoupling,precise amplitude output,and stable and rapid convergence,as well as asymmetric output ***,it can effectively cope with large parameter changes to avoid network oscillations and *** optimize the parameters of the NA-CPG model,a reinforcement-learning-based online optimization method is further ***,a biomimetic robotic fish is illustrated to realize the whole optimization *** demonstrated that the designed NA-CPGs exhibit stable,secure,and accurate network outputs,and the proposed optimization method effectively improves the swimming speed and reduces the lateral swing of the multijoint robotic fish by 6.7%and 41.7%,*** proposed approach provides a significant improvement in CPG research and can be widely employed in the field of robot motion control.

关键词： Normalized asymmetric CPGs Rhythm generator Motion control Robotic fish

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Development and Optimization of a WebGL-Based Mechanical Model Simulation Platform 4th

Development and Optimization of a WebGL-Based Mechanical Mod...

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4th International Conference on Mechanical Design and Simulation, MDS 2024

作者： Wang, Xintong Tian, Hao Fang, Jingzhe Zhang, Hualiang Zhang, Tao Software College Shenyang University of Technology Liaoning Shenyang China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China School of Electrical Engineering Shenyang University of Technology Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang China

ISBN: (纸本)9789819778867

The need for mechanical model simulation platforms is growing as a result of the ongoing advancements in digital technology and the mechanical manufacturing sector. The application scope and efficacy of simulation platforms are severely limited by the issue of sluggish rendering performance, which frequently arises when obtaining high-quality rendering. When drawing high demand mechanical models, a lot of processing power is frequently needed, which makes real-time rendering speed unsatisfactory for practical purposes. In order to achieve real-time rendering and simulation of 3D robots, this experiment built and implemented a WebGL-based 3D simulation platform. Additionally, the simulation platform can be optimized by increasing frame rate and rendering speed without sacrificing rendering effect by building a mixed bounding box. © The Author(s) 2025.

关键词： Digital elevation model

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