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

作者： Ha, Jin-Ung Kim, Hyun-Woo Cho, Myungjin Lee, Min-Chul Kyushu Institute of Technology Department of Computer Science and Networks Fukuoka Iizuka820-8502 Japan School of ICT Robotics and Mechanical Engineering Iitc Hankyong National University Kyonggi-do Anseong17579 Korea Republic of

ISBN: (纸本)9788993215274

In this paper, we propose a method to improve the recognition rate of ArUco markers under photon-starved conditions by using preprocessing such as photon counting algorithm and histogram equalization to estimate the exact three-dimensional(3D) location of improved objects. In the conventional ArUco marker recognition technology, the recognition rate of ArUco markers decreases under photon-starved conditions, and the exact 3D location of the object cannot be estimated. In the conventional ArUco marker recognition technology, the photon counting algorithm can be used to estimate the 3D location of objects by recognizing ArUco markers under photon-starved conditions. However, the photon counting algorithm has the problem that the computation speed is slowed down when there are many photons to estimate, and the recognition rate of the ArUco marker is reduced when there are few photons to estimate. To solve these problems of the photon counting algorithm and improve the recognition rate of ArUco markers, we apply histogram equalization to ArUco markers with the photon counting algorithm. To verify the feasibility of the proposed method, we implement simulations using the Open Manipulator-X platform and show performance metrics such as Peak Signal-to-Noise Ratio (PSNR). © 2023 ICROS.

关键词： Photons

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GelPixel: A Single-Pixel-Based Tactile Sensor

GelPixel: A Single-Pixel-Based Tactile Sensor

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2023 IEEE International Conference on Real-Time Computing and robotics, RCAR 2023

作者： Huang, Binhua Li, Xiaoyu Sumari, Putra Ye, Chaoxiang Zhou, Zhenning Yin, Meng Yi, Zhengkun Wu, Xinyu Shenzhen Institute of Artificial Intelligence and Robotics for Society Siat Branch Shenzhen518055 China Universiti Sains Malaysia School of Computer Science 11800 Malaysia Chinese Academy of Sciences Guangdong Provincial Key Laboratory of Robotics and Intelligent System Shenzhen Institute of Advanced Technology Shenzhen518055 China

ISBN: (纸本)9798350327182

In this paper, we present the design and development of a novel optical tactile sensor that uses a single-pixel color light-to-frequency converter (TCS3200) and spectral decoding to recognize presses at different positions. This innovative approach overcomes the limitations associated with camera-based sensors, such as increased manufacturing costs and shape restrictions, enabling potential integration as a skin-like layer over a robot's body. Our proposed direct light propagation structure demonstrates enhanced sensitivity and a broader measuring range compared to traditional reflection structures. Using Ecoflex as the elastomer, the sensor's design incorporates a three-layer structure, including an LED layer, an elastomer layer, and a color sensor layer. Experimental results demonstrate that the proposed sensor performs well in localization tasks, achieving over 95% accuracy using multi-target regression for rendering poked positions. This study demonstrates the potential of single-pixel-based tactile sensors in various applications and provides a foundation for further exploration in this area. © 2023 IEEE.

关键词： Tactile sensors

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Optical Evanescent Field for Direct Observation of Sub-100nm Particle Motion on Glass Surface 1

Optical Evanescent Field for Direct Observation of Sub-100nm...

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1st International Conference on robotics, Engineering, science, and technology, RESTCON 2024

作者： Khajornrungruang, Panart Permpatdechakul, Thitipat Suzuki, Keisuke Blattler, Aran Terayama, Yutaka Goto, Daiki Phaisalpanumas, Pipat Bun-Athuek, Natthaphon Phunopas, Amornphun Kyushu Institute of Technology Iizuka-Shi Mechanical Science and Technology Division Dept. of Intelligent and Control System Faculty of Computer Science and Systems Engineering Fukuoka Japan Kyushu Institute of Technology Iizuka-Shi Mechanical Information Science and Technology Division Dept. of Interdisciplinary Informatics Graduate School of Computer Science and Systems Engineering Fukuoka Japan King Mongkut's University of Technology North Bangkok Bangsue Faculty of Engineering Dept. of Production and Robotics Engineering Bangkok Thailand Kyushu Institute of Technology Iizuka-Shi Mechanical Science and Technology Course Dept. of Intelligent and Control System Graduate School of Computer Science and Systems Engineering Fukuoka Japan King Mongkut's University of Technology North Bangkok Bangsue Faculty of Engineering Dept. of Industiral Engineering Bangkok Thailand King Mongkut's University of Technology North Bangkok Bangsue College of Industrial Technology Dept. of Mechanical Engineering Technology Bangkok Thailand

ISBN: (纸本)9798350348842

To directly investigate the dynamic nanoscale phenomenon on the surface being processed in wet conditions such as precision polishing, and cleaning in semiconductor industrial, an optical method for visualization and observation of each sub-100 nm sized particle that is moving on an interface such as a silica glass surface by applying an evanescent field have been proposing. Subsequently, we developed an experimental apparatus equipped with an optical microscopy system for verifying the moving particle observation method in a laboratory scale. This article introduces some experimentally direct observation results of duplicated wet processes. © 2024 IEEE.

关键词： Visualization

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A New Noise-Tolerant Dual-Neural-Network Scheme for Robust Kinematic Control of Robotic Arms With Unknown Models

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IEEE/CAA Journal of Automatica Sinica 2022年第10期9卷 1778-1791页

作者： Ning Tan Peng Yu Zhiyan Zhong Fenglei Ni IEEE the School of Computer Science and Engineering&Key Laboratory of Machine Intelligence and Advanced Computing Ministry of EducationSun Yat-sen UniversityGuangzhou 510006China the School of Automation Guangdong Polytechnic Normal UniversityGuangzhou 510665China the State Key Laboratory of Robotics and Systems Harbin Institute of Technology(HIT)Harbin 150080China

Taking advantage of their inherent dexterity,robotic arms are competent in completing many tasks *** a result of the modeling complexity and kinematic uncertainty of robotic arms,model-free control paradigm has been proposed and investigated ***,robust model-free control of robotic arms in the presence of noise interference remains a problem worth *** this paper,we first propose a new kind of zeroing neural network(ZNN),i.e.,integration-enhanced noise-tolerant ZNN(IENT-ZNN)with integration-enhanced noisetolerant ***,a unified dual IENT-ZNN scheme based on the proposed IENT-ZNN is presented for the kinematic control problem of both rigid-link and continuum robotic arms,which improves the performance of robotic arms with the disturbance of noise,without knowing the structural parameters of the robotic *** finite-time convergence and robustness of the proposed control scheme are proven by theoretical ***,simulation studies and experimental demonstrations verify that the proposed control scheme is feasible in the kinematic control of different robotic arms and can achieve better results in terms of accuracy and robustness.

关键词： Dual zeroing neural networks(ZNN) finite-time convergence model-free robot control robustness analysis

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Informative Sensor Planning for a Single-Axis Gimbaled Camera on a Fixed-Wing UAV

Informative Sensor Planning for a Single-Axis Gimbaled Camer...

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IEEE International Conference on Automation science and Engineering (CASE)

作者： Aditya Parandekar Brady Moon Nayana Suvarna Sebastian Scherer Birla Institute of Technology and Science Sancoale Goa India Robotics Institute School of Computer Science at Carnegie Mellon University Pittsburgh PA USA

ISBN: (数字)9798350358513

ISBN: (纸本)9798350358520

Uncrewed Aerial Vehicles (UAVs) are a leading choice of platforms for a variety of information-gathering applications. Sensor planning can enhance the efficiency and success of these types of missions when coupled with a higher-level informative path-planning algorithm. This paper aims to address these data acquisition challenges by developing an informative non-myopic sensor planning framework for a single-axis gimbal coupled with an informative path planner to maximize information gain over a prior information map. This is done by finding reduced sensor sweep bounds over a planning horizon such that regions of higher confidence are prioritized. This novel sensor planning framework is evaluated against a predefined sensor sweep and no sensor planning baselines as well as validated in two simulation environments. In our results, we observe an improvement in the performance by 21.88% and 13.34% for the no sensor planning and predefined sensor sweep baselines respectively.

关键词： computer aided software engineering Automation Data acquisition Autonomous aerial vehicles Cameras Planning

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Optimal Energy Storage Operation under Demand Uncertainty: A Prospect Theory Analysis 14

Optimal Energy Storage Operation under Demand Uncertainty: A...

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14th IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids, SmartGridComm 2023

作者： Huang, Qisheng Xu, Jin Sun, Peng Liu, Bo Courcoubetis, Costas Harbin Institute of Technology Shenzhen School of Mechanical Engineering and Automation Shenzhen518055 China Huazhong University of Science and Technology School of Management Wuhan China Hunan University College of Computer Science and Electronic Engineering Changsha410082 China Shenzhen Institute of Artificial Intelligence and Robotics for Society Shenzhen China The Chinese University of Hong Kong Shenzhen School of Data Science Shenzhen518712 China

ISBN: (纸本)9781665455541

In this paper, we study the consumer's optimal energy storage operation problem under demand uncertainty. Each consumer can purchase energy storage service from an independent energy storage aggregator to shift demand from peak periods to off-peak periods under time-of-use (ToU) pricing. Previous studies on energy storage operation and investment mainly focused on the expected cost-minimization problem of a risk-neutral consumer based on the expected utility theory (EUT). We propose a prospect theory (PT) model from behavioral economics to understand the consumer's realistic energy storage operation behaviors considering their risk preferences. Although it is challenging to solve the PT-based non-convex optimization problem, we are able to characterize the optimal solution by exploiting the unimodal structure of the objective function. Theoretical and numerical results show that the consumer's risk preferences have a significant impact on his decisions: 1) a PT-consumer with a low reference point is more willing to use energy storage to reduce risk compared with the EUT benchmark;and 2) a PT consumer is more willing to use the energy storage when the probability of high demand is small, due to the probability distortion. © 2023 IEEE.

关键词： Energy storage

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ProRes: Exploring Degradation-aware Visual Prompt for Universal Image Restoration

arXiv

引用

arXiv 2023年

作者： Ma, Jiaqi Cheng, Tianheng Wang, Guoli Zhang, Qian Wang, Xinggang Zhang, Lefei School of Computer Science Wuhan University China School of EIC Huazhong University of Science & Technology China Horizon Robotics China

Image restoration aims to reconstruct degraded images, e.g., denoising or deblurring. Existing works focus on designing task-specific methods and there are inadequate attempts at universal methods. However, simply unifying multiple tasks into one universal architecture suffers from uncontrollable and undesired predictions. To address those issues, we explore prompt learning in universal architectures for image restoration tasks. In this paper, we present Degradation-aware Visual Prompts, which encode various types of image degradation, e.g., noise and blur, into unified visual prompts. These degradation-aware prompts provide control over image processing and allow weighted combinations for customized image restoration as shown in Fig. 1. We then leverage degradation-aware visual Prompts to establish a controllable and universal model for image Restoration, called ProRes, which is applicable to an extensive range of image restoration tasks. ProRes leverages the vanilla Vision Transformer (ViT) without any task-specific designs. Furthermore, the pre-trained ProRes can easily adapt to new tasks through efficient prompt tuning with only a few images. Without bells and whistles, ProRes achieves competitive performance compared to task-specific methods and experiments can demonstrate its ability for controllable restoration and adaptation for new tasks. The code and models will be released in https://***/leonmakise/ProRes. © 2023, CC BY.

关键词： Image reconstruction

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Effective Carbon Tax Learning via Cap and Trade 5

Effective Carbon Tax Learning via Cap and Trade

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5th IEEE International Electrical and Energy Conference, CIEEC 2022

作者： Liang, Jinhao Jiang, Wenqian Wu, Chenye Xidian University School of Computer Science and Technology Shaanxi Xi'an China The Chinese University of Hong Kong Shenzhen and Shenzhen Institute of Artificial Intelligence and Robotics for Society School of Science and Engineering Guangdong Shenzhen China

ISBN: (数字)9781665411042

ISBN: (纸本)9781665411042

Global warming warrants the global adoption of carbon reduction schemes, among which the two most popular ones are carbon tax (CT) and the cap-and-trade (CAT) program with quite different implementations. CT levies taxes on the energy generation while CAT directly limits the total carbon emission in the system. Hence, in practice, CAT is more adjustable than CT due to the long legislation process for altering tax rate, though CT is much easier to implement. In this paper, we seek to learn the most effective tax rate through CAT programs by establishing the equivalence between CT and CAT. Through bridging the two schemes, we use numerical study to highlight the different dynamics for the schemes to converge to the equivalent point. © 2022 IEEE.

关键词： Taxation

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Jigsaw-Based Benchmarking for Learning Robotic Manipulation 8

Jigsaw-Based Benchmarking for Learning Robotic Manipulation

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

作者： Liu, Xiaobo Wan, Fang Ge, Sheng Wang, Haokun Sun, Haoran Song, Chaoyang Southern University of Science and Technology Department of Mechanical and Energy Engineering Guangdong Shenzhen518055 China School of Design Southern University of Science and Technology Guangdong Shenzhen518055 China Hong Kong University of Science and Technology Robotics & Autonomous Systems Thrust System Hub Hong Kong Hong Kong The University of Hong Kong Department of Computer Science Hong Kong Hong Kong

ISBN: (纸本)9798350300178

Benchmarking provides experimental evidence of the scientific baseline to enhance the progression of fundamental research, which is also applicable to robotics. In this paper, we propose a method to benchmark metrics of robotic manipulation, which addresses the spatial-temporal reasoning skills for robot learning with the jigsaw game. In particular, our approach exploits a simple set of jigsaw pieces by designing a structured protocol, which can be highly customizable according to a wide range of task specifications. Researchers can selectively adopt the proposed protocol to benchmark their research outputs, on a comparable scale in the functional, task, and system-level of details. The purpose is to provide a potential look-up table for learning-based robot manipulation, commonly available in other engineering disciplines, to facilitate the adoption of robotics through calculated, empirical, and systematic experimental evidence. © 2023 IEEE.

关键词： Benchmarking

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An Adversarial Approach to Register Extreme Resolution Tissue Cleared 3D Brain Images

arXiv

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arXiv 2025年

作者： Nazib, Abdullah Fookes, Clinton Perrin, Dimitri School of Computer Science Queensland University of Technology BrisbaneQLD Australia School of Electrical Engineering and Robotics Queensland University of Technology BrisbaneQLD Australia Centre for Data Science Queensland University of Technology BrisbaneQLD Australia

We developed a generative patch based 3D image registration model that can register very high resolution images obtained from a biochemical process name tissue clearing. Tissue clearing process removes lipids and fats from the tissue and make the tissue transparent. When cleared tissues are imaged with Light-sheet fluorescent microscopy, the resulting images give a clear window to the cellular activities and dynamics inside the *** the images obtained are very rich with cellular information and hence their resolution is extremely high (eg .2560 × 2160 × 676). Analyzing images with such high resolution is a difficult task for any image analysis *** registration is a common step in image analysis pipeline when comparison between images are required. Traditional image registration methods fail to register images with such extant. In this paper we addressed this very high resolution image registration issue by proposing a patch-based generative network named InvGAN. Our proposed network can register very high resolution tissue cleared images. The tissue cleared dataset used in this paper are obtained from a tissue clearing protocol named CUBIC. We compared our method both with traditional and deep-learning based registration *** different versions of CUBIC dataset are used, representing two different resolutions 25% and 100% respectively. Experiments on two different resolutions clearly show the impact of resolution on the registration quality. At 25% resolution, our method achieves comparable registration accuracy with very short time (7 minutes approximately). At 100% resolution, most of the traditional registration methods fail except Elastix registration *** takes 28 hours to register where proposed InvGAN takes only 10 minutes. © 2025, CC BY.

关键词： Image registration

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