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International Conference on Guidance, Navigation and Control, ICGNC 2022

作者： Piao, Minnan Li, Haifeng Lu, Biao Wang, Yongshuai Huang, Jian College of Computer Science and Technology Civil Aviation University of China Tianjin300300 China Institute of Robotics and Automatic Information System College of Artificial Intelligence Nankai University Tianjin300350 China Beijing Automatic Control & Equipment Institute Beijing100074 China

ISBN: (纸本)9789811966125

Active control of aeroservoelasticity effect is critical for future aircraft. This paper concerns the flutter suppression problem for a benchmark active control technology (BACT) wind-tunnel model, which is subject to unmodelled dynamics, parameter perturbations, turbulence disturbances, and measurement noises. After analyzing the characteristics of the BACT model, the trailing edge velocity, which combines the information of the plunge and the pitch modes, is chosen as the controlled output. Several practical filters are employed to effectively attenuate the sensor noise and drift. Based on the filtered signal, we employ the active disturbance rejection control (ADRC) to compensate the multifarious uncertainties and achieve the flutter suppression. Furthermore, to facilitate parameter tuning, the nonsmooth H∞ synthesis method is employed. Finally, extensive simulation and comparison results validate the superiority of the proposed method. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Disturbance rejection

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Development and Analysis of a Versatile Dataset of Speech, Real and Synthesized, of Arabic Learners 3

Development and Analysis of a Versatile Dataset of Speech, R...

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3rd International Conference on Computing and Information Technology, ICCIT 2023

作者： Alsulaiman, Mansour Algabri, Mohammed Mathkour, Hassan Bencherif, Mohamed A. Muhammad, Ghulam Al-Gahtani, Saad Faisal, Mohammed Mekhtiche, Mohamed Amine Alfakih, Taha King Saud University College of Computer and Information Sciences Computer Engineering Department Riyadh Saudi Arabia AlMaarefa University College of Applied Sciences Computer Science and Information Systems Department Riyadh Saudi Arabia King Saud University College of Computer and Information Sciences Computer Science Department Riyadh Saudi Arabia Riyadh Saudi Arabia King Saud University Arabic Language Institute Saudi Arabia Center of Ai & Robotics Kuwait

ISBN: (纸本)9798350321487

computer-Aided Pronunciation Training (CAPT) systems are gaining popularity recently due to the advancements in deep neural networks (DNN) and machine learning and the availability of databases of speech of language learners. Unfortunately, research in Arabic CAPT systems suffer from the lack of CAPT datasets compared to other languages. In this paper, we present the details of and the ideas used in the development of a versatile dataset of speech, real and synthesized, of Arabic Learners. To develop the dataset, we utilized an existing Arabic speech corpus, King Saud University Speech Database (KSU-SD). KSU-SD's main application was a speaker recognition system, but it was designed to be useful in other applications such as CAPT systems. KSU-SD includes a large number of speakers from diverse nationalities (Saudis, Arabs, and Non-Arabs). KSU-SD contains the recording of about 60 non-native speakers from more than 20 nationalities, hence we selected it to build the non-native Arabic-CAPT corpus. The developed corpus consists of transcribed, segmented, and annotated speech, which makes it suitable for building Arabic CAPT systems. In addition to presenting the details of developing the dataset, we also present an analysis of the text and speech errors of the dataset. The dataset was verified by many CAPT systems. © 2023 IEEE.

关键词： Deep neural networks

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Adaptive Control Using a Quaternion Wavelet Neural Network

Adaptive Control Using a Quaternion Wavelet Neural Network

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International Workshop on Robot Motion and Control (RoMoCo)

作者： Gerardo Martínez-Terán Eduardo Bayro-Corrochano Dept. Electrical Engineering and Computer Science CINVESTAV Guadalajara Mexico Institute of Automatic Control and Robotics Poznan University of Technology

ISBN: (数字)9798350393965

ISBN: (纸本)9798350393972

robotics and haptic systems have allowed new and diverse applications in the field of medicine, such as assisted surgery and teleoperation which have increasingly stringent requirements for accuracy, convergence, and low computational consumption. In this paper an adaptive PID control law (Proportional Integral Derivative controller, PID), of indirect architecture is presented for movement paths in a haptic system of open chain, where the identification of the plant is through a quaternionic wavelet neural network (Quaternion Wavelet Neural Network, QWNN) for tune the PID values, this allows the optimal movement into the regions of the workspace.

关键词： Uncertainty Quaternions Neural networks Surgery Robustness Haptic interfaces Topology

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APriCoT: Action Primitives based on Contact-state Transition for In-Hand Tool Manipulation

arXiv

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arXiv 2024年

作者： Saito, Daichi Kanehira, Atsushi Sasabuchi, Kazuhiro Wake, Naoki Takamatsu, Jun Koike, Hideki Ikeuchi, Katsushi Department of Computer Science Tokyo Institute of Technology Tokyo Japan Applied Robotics Research Microsoft RedmondWA United States

In-hand tool manipulation is an operation that not only manipulates a tool within the hand (i.e., in-hand manipulation) but also achieves a grasp suitable for a task after the manipulation. This study aims to achieve an in-hand tool manipulation skill through deep reinforcement learning. The difficulty of learning the skill arises because this manipulation requires (A) exploring long-term contact-state changes to achieve the desired grasp and (B) highly-varied motions depending on the contact-state transition. (A) leads to a sparsity of a reward on a successful grasp, and (B) requires an RL agent to explore widely within the state-action space to learn highly-varied actions, leading to sample inefficiency. To address these issues, this study proposes Action Primitives based on Contact-state Transition (APriCoT). APriCoT decomposes the manipulation into short-term action primitives by describing the operation as a contact-state transition based on three action representations (detach, crossover, attach). In each action primitive, fingers are required to perform short-term and similar actions. By training a policy for each primitive, we can mitigate the issues from (A) and (B). This study focuses on a fundamental operation as an example of in-hand tool manipulation: rotating an elongated object grasped with a precision grasp by half a turn to achieve the initial grasp. Experimental results demonstrated that ours succeeded in both the rotation and the achievement of the desired grasp, unlike existing studies. Additionally, it was found that the policy was robust to changes in object shape. © 2024, CC BY.

关键词： Reinforcement learning

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Underwater Robot-To-Human Communication Via Motion: Implementation and Full-Loop Human Interface Evaluation 18th

Underwater Robot-To-Human Communication Via Motion: Implemen...

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18th robotics: science and Systems, RSS 2022

作者： Fulton, Michael Mehtaz, Muntaqim Sattar, Junaed Queeglay, Owen Deptartment of Computer Science & Engineering Minnesota Robotics Institute University of Minnesota Twin Cities United States Department of Electrical Engineering Stanford University United States

ISBN: (纸本)9780992374785

Autonomous underwater vehicles (AUVs) have long lagged behind other types of robots in supporting natural communication modes for human-robot interaction. Due to the limitations of the environment, most AUVs use digital displays or topside human-in-the-loop communications as their primary or only communication vectors. Natural methods for robotto-human communication such as robot "gestures" have been proposed, but never evaluated on non-simulated AUVs. In this paper, we enhance, implement and evaluate a robot-to-human communication system for AUVs called Robot Communication Via Motion (RCVM), which utilizes explicit motion phrases (kinemes) to communicate with a dive partner. We present a small pilot study that shows our implementation to be reasonably effective in person followed by a large-population study, comparing the communication effectiveness of our RCVM implementation to three baseline systems. Our results establish RCVM as an effective method of robot-to-human communication underwater and reveal the differences with more traditional communication vectors in how accurately communication is achieved at different viewpoints and types of information payloads. © 2022, MIT Press Journals. All rights reserved.

关键词： Autonomous underwater vehicles

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Conformal Decision Theory: Safe Autonomous Decisions from Imperfect Predictions

Conformal Decision Theory: Safe Autonomous Decisions from Im...

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IEEE International Conference on robotics and Automation (ICRA)

作者： Jordan Lekeufack Anastasios N. Angelopoulos Andrea Bajcsy Michael I. Jordan Jitendra Malik Department of Statistics UC Berkeley Department of Electrical Engineering and Computer Science UC Berkeley Robotics Institute Carnegie Mellon University

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

We introduce Conformal Decision Theory, a framework for producing safe autonomous decisions despite imperfect machine learning predictions. Examples of such decisions are ubiquitous, from robot planning algorithms that rely on pedestrian predictions, to calibrating autonomous manufacturing to exhibit high throughput and low error, to the choice of trusting a nominal policy versus switching to a safe backup policy at run-time. The decisions produced by our algorithms are safe in the sense that they come with provable statistical guarantees of having low risk without any assumptions on the world model whatsoever; the observations need not be I.I.D. and can even be adversarial. The theory extends results from conformal prediction to calibrate decisions directly, without requiring the construction of prediction sets. Experiments demonstrate the utility of our approach in robot motion planning around humans and robot manufacturing.

关键词： Robot motion Pedestrians Machine learning algorithms Decision theory Switches Prediction algorithms Throughput

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A Scalable Real-time Semantic Segmentation Network for Autonomous Driving 1

A Scalable Real-time Semantic Segmentation Network for Auton...

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1st Workshop on Advanced Multimedia Computing for Smart Manufacturing and Engineering, AMC-SME 2023

作者： Liu, Jun Wu, Chao Yuan, Geng Niu, Wei Zhang, Wenbin Song, Houbing Herbert Robotics Institute of School of Computer Science Carnegie Mellon University Pittsburgh United States Department of Electrical & Computer Engineering Northeastern University Boston United States School of Computing University of Georgia Athens United States Department of Computer Science Michigan Technological University Houghton United States Department of Information Systems University of Maryland Baltimore County Baltimore United States

ISBN: (纸本)9798400702730

Computational resources are limited on real-time embedded devices, so the available computing cost of deployment on the target platform must be considered. We develop a feature extraction module based on the MobileNet backbone that can be adjusted in terms of computational complexity and capacity using the depth multiplier parameter, classifier depth, and kernel depth. These three parameters allow us to control the count of channels within the network, effectively managing the model's capacity and computational requirements. To achieve semantic segmentation, we incorporate additional components, such as an extension module. This extension module typically includes 1x1 pointwise convolutional layers for pixel-level classification and a transposed convolutional layer for upsampling the output to the original input image size. By combining the feature extraction module with this extension module, we can create a complete architecture capable of performing semantic segmentation tasks. The feature extraction module provides the initial feature extraction and the extension module adds the necessary components for accurate pixel-wise classification and upsampling. Compared to Hardware-aware Neural Architecture Search (NAS), pruning, runtime pruning, and knowledge distillation methods, our model has several advantages in terms of modular design, structural controllability, ease of implementation, and cost-effectiveness. Our computational efficiency, as measured by FLOPS, is highly competitive. Our method is distinguished by solving the problem of MobileNet's inability to adjust the size and number of convolution kernels. It achieves this through adaptable parameter tuning, including MobileNet's depth multiplier, the kernel size in the FCN head's Separable Convolution layer, and the depth of the first Point-wise Convolution layer. These adjustments are customized to match hardware's max multiply-accumulates (MACs), optimizing network capacity and maximizing resource utilizat

关键词： Feature extraction

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A Novel Cable-Driven Soft Robot for Surgery

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Journal of Shanghai Jiaotong university(science) 2024年第1期29卷 60-72页

作者：李茹陈方俞文伟 IGARASH Tatsuo 舒雄鹏谢叻 Institute of Forming Technology and Equipment School of Materials Science and EngineeringShanghai Jiao Tong UniversityShanghai 200030China The Sixth People's Hospital Affiliated to Shanghai Jiao Tong University Shanghai 200233China Center for Frontier Medical Engineering Chiba UniversityChiba 263-8522Japan Seirei Sakura Citizen Hospital Chiba 285-8765Japan Institute of Medical Robotics Shanghai Jiao Tong UniversityShanghai 200030China School of Mathematics and Computer Science Quanzhou Normal UniversityQuanzhou 362000FujianChina

Robot-assisted laparoscopic radical prostatectomy(RARP)is widely used to treat prostate *** rigid instruments primarily used in RARP cannot overcome the problem of blind areas in surgery and lead to more trauma such as more incision for the passage of the instrument and additional tissue damage caused by rigid *** robots are relatively fexible and theoretically have infinite degrees of freedom which can overcome the problem of the rigid instrument.A soft robot system for single-port transvesical robot-assisted radical prostatectomy(STvRARP)is developed in this *** soft manipulator with 10 mm in diameter and a maximum bending angle of 270°has good fexibility and *** design and mechanical structure of the soft robot are *** kinematics of the soft manipulator is established and the inverse kinematics is compensated based on the characteristics of the designed soft *** master-slave control system of soft robot for surgery is built and the feasibility of the designed soft robot is verified.

关键词： soft robot kinematics model robot-assisted surgery

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A single-stream adaptive scene layout modeling method for scene recognition

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Neural Computing and Applications 2024年第22期36卷 13703-13714页

作者： Wang, Qun Zhu, Feng Lin, Zhiyuan Wang, Jianyu Li, Xiang Zhao, Pengfei Key Laboratory of Opto-Electronic Information Processing Chinese Academy of Sciences Shenyang110016 China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110016 China University of Chinese Academy of Sciences Beijing100049 China Faculty of Robot Science and Engineering Northeastern University Shenyang110016 China Faculty of Computer Science and Engineering Northeastern University Shenyang110016 China

Scene recognition has been the foundation of research in computer vision fields. Because scene images typically are composed of specific regions distributed in some layout, so modeling layouts of various scenes is a key clue for scene recognition. Existing methods usually require an additional stream to detect regions for subsequent modeling, which accumulate errors and may miss important information. Meanwhile, they use manual features to model relations between regions, which weakens the representation ability of layouts. In this paper, we propose a single-stream adaptive scene layout modeling approach based on a layout modeling module (LMM), which constructs layouts without additional detection streams and adaptively captures the relations to take advantage of graph attention network. LMM is directly concatenated to a convolutional neural network, where each pixel of the activation maps of the last convolutional layer is defined as a region that is the initial input node of the LMM. LMM first models the layout of each region, and then uses all regions with layout information to model the entire scene. Layout relations are encoded as edges, which are automatically analyzed according to region co-occurrence and relative position. Our work can be understood as optimizing features of the activation maps from a scene layout modeling perspective for scene recognition. Experimental results on MIT67, SUN397, and Places365 show that our single-stream model achieves competitive performance. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2024.

关键词： Convolutional neural networks

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Comparative Analysis among Categorical Shortest Path-finding Algorithms using OPSimDAZ

Comparative Analysis among Categorical Shortest Path-finding...

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International Conference on computer and Information Technology (ICCIT)

作者： Milton Bhowmick M. Akhtaruzzaman Department of Computer Science and Engineering Military Institute of Science and Technology (MIST) Dhaka Bangladesh Quantum Robotics and Automation Research Group (QRARG) Dhaka Bangladesh

ISBN: (数字)9798331519094

ISBN: (纸本)9798331519100

Efficient navigation of mobile robots is crucial for industrial applications. However, environmental obstacles can pose significant risks and hinder operational optimality. Thus, identifying the ideal algorithm through comparative analysis is imperative. This study examines five popular path planning algorithms; Dijkstra, BFS, A*, D* Lite, and Ant Colony Optimization (ACO); based on 2D grid simulation. The objective is to conduct performance analysis of these algorithms through a custom designed online simulation platform for visualization of path planning strategies. The methodology encompasses a thorough background study, environment setup, development of simulation platform, algorithm implementation, and result analysis with visualization. This study contributes by introducing a new simulation platform, and adding values to the existing knowledge of path planning analysis.

关键词： Visualization Ant colony optimization Navigation Heuristic algorithms Probabilistic logic Path planning Real-time systems Performance analysis Mobile robots Information technology

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