检索结果-内蒙古大学图书馆

2nd International Conference on Computer Vision and Internet of Things (ICCVIoT 2024)

作者： Fredj Ahmed Gurram Srinivasa Danie John Shajin Prince Bini D National School of Advanced Sciences and Technologies of Borj Cedria Ben Arous Tunisia Robotics Engineering Karunya Institute of Technology and Sciences Coimbatore India Electronics and Communication Engineering Karunya Institute of Technology and Sciences Coimbatore India

ISBN: (数字)9781837242535

Children with Autism Spectrum Disorder (ASD) often struggle with emotional recognition and expression, which can hinder their social interactions and communication skills. Detecting emotions in children with Autism Spectrum Disorder is crucial for understanding their emotional states, as these children often face challenges in recognizing and expressing feelings. This paper explores the facial emotions and EEG signals for emotion detection with machine learning, deep learning, and physiological signal. The results show substantial accuracy in recognizing emotions by utilizing multimodal data and powerful algorithms, providing insightful information for educators and caregivers. Our goal in modifying YOLO for emotion identification is to take use of its accuracy and speed in dynamic contexts like real-time video streams. The study assesses how effectively the YOLO architectures—more especially, YOLOv5s, YOLOv7-tiny, and YOLOv8s—perform on a customized dataset intended for the identification of emotions in kids with ASD. The results demonstrate the models' efficacy in precisely recognizing emotional expressions, which supports therapeutic interventions for kids with ASD.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Diffusiophoresis in the presence of a pH gradient

引用

Physical Review Fluids 2022年第11期7卷 110513-110513页

作者： Suin Shim Janine K. Nunes Guang Chen Howard A. Stone Department of Mechanical and Aerospace Engineering Princeton University Princeton New Jersey 08544 USA Department of Advanced Manufacturing and Robotics College of Engineering Peking University Beijing 100871 China

Diffusiophoresis is the spontaneous motion of particles under gradients of solutes. In electrolyte-driven diffusiophoresis, the zeta potential of the particles is an important surface property that characterizes diffusiophoretic mobility. However, the zeta potential is not a fixed material property and colloidal surfaces often show varying potentials depending on the physicochemical properties of the surrounding fluid, e.g., solute type, ionic strength, and pH. In this paper, we study experimentally and theoretically pH-dependent diffusiophoresis of polystyrene particles using a dead-end pore geometry. In particular, the influence of the isoelectric point (pI) on diffusiophoresis is demonstrated in the absence and presence of wall diffusioosmosis. Throughout the paper, we show with experiments and model calculations how the pH-dependent diffusiophoresis and diffusioosmosis influence the particle motion in dead-end pore configurations, including changes that occur when there is a sign change in the zeta potential near the pI.

关键词： Diffusiophoresis Electrokinetic flows Microfluidics Colloids

来源：评论

学校读者我要写书评

暂无评论

Resilient Navigation Based on Multimodal Measurements and Degradation Identification for High-Speed Autonomous Race Cars

Resilient Navigation Based on Multimodal Measurements and De...

引用

IEEE Symposium on Intelligent Vehicle

作者： Daegyu Lee Hyunwoo Nam Chanhoe Ryu Sungwon Nah D. Hyunchul Shim Department of Electrical Engineering Korea Advanced Institute of Science and Technologies (KAIST) Daejeon Republic of Korea Robotics Program KAIST Daejeon Republic of Korea

This paper presents a localization system robust against unreliable measurements and a resilient navigation system recovering from localization failures for Indy autonomous challenge (IAC). The IAC is a competition with full-scale autonomous race cars that drive at speeds up to 300 kph. Owing to high-speed and heavy vibration in the car, a GPS/INS system is prone to degrade causing critical localization errors, which leads to catastrophic *** order to address this issue, we propose a robust localization system that probabilistically evaluates the credibility of multi-modal measurements. At a correction step of the Kalman filter, a degradation identification method with a novel hyper-parameter derived from Bayesian decision theory is introduced to choose the most credible measurement values in real-time. Since the racing condition is so harsh that even our robust localization method can fail for a short period of time, we present a resilient navigation system that enables the race car to continue to follow the race track in the event of a localization failure. Our system uses direct perception information in planning and execution until the completion of localization *** proposed localization system is first validated in a simulation with real measurement data contaminated by large artificial noises. The experimental validation during an actual race is also presented. The last part of our paper shows the results from the real-world tests where our system recovers from failures and prevents accidents in real-time, which proves the resilience of the proposed navigation system.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Informative Path Planning of Autonomous Vehicle for Parking Occupancy Estimation

arXiv

引用

arXiv 2023年

作者： Hu, Yunze Chen, Jiaao Zhou, Kangjie Gao, Han Li, Yutong Liu, Chang The Department of Advanced Manufacturing and Robotics College of Engineering Peking University Beijing100871 China The Department of Aerospace Engineering University of Michigan Ann ArborMI48109 United States

Parking occupancy estimation holds significant potential in facilitating parking resource management and mitigating traffic congestion. Existing approaches employ robotic systems to detect the occupancy status of individual parking spaces and primarily focus on enhancing detection accuracy through perception pipelines. However, these methods often overlook the crucial aspect of robot path planning, which can hinder the accurate estimation of the entire parking area. In light of these limitations, we introduce the problem of informative path planning for parking occupancy estimation using autonomous vehicles and formulate it as a Partially Observable Markov Decision Process (POMDP) task. Then, we develop an occupancy state transition model and introduce a Bayes filter to estimate occupancy based on noisy sensor measurements. Subsequently, we propose the Monte Carlo Bayes Filter Tree, a computationally efficient algorithm that leverages progressive widening to generate informative paths. We demonstrate that the proposed approach outperforms the benchmark methods in diverse simulation environments, effectively striking a balance between optimality and computational efficiency. © 2023, CC BY.

关键词： Motion planning

来源：评论

学校读者我要写书评

暂无评论

Guided Learning from Demonstration for Robust Transferability

arXiv

引用

arXiv 2023年

作者： Sukkar, Fouad Moreno, Victor Hernandez Vidal-Calleja, Teresa Deuse, Jochen UTS Robotics Institute the Centre for Advanced Manufacturing School for Mechanical and Mechatronic Engineering University of Technology Sydney UltimoNSW2007 Australia Australia

Learning from demonstration (LfD) has the potential to greatly increase the applicability of robotic manipulators in modern industrial applications. Recent progress in LfD methods have put more emphasis in learning robustness than in guiding the demonstration itself in order to improve robustness. The latter is particularly important to consider when the target system reproducing the motion is structurally different to the demonstration system, as some demonstrated motions may not be reproducible. In light of this, this paper introduces a new guided learning from demonstration paradigm where an interactive graphical user interface (GUI) guides the user during demonstration, preventing them from demonstrating non-reproducible motions. The key aspect of our approach is determining the space of reproducible motions based on a motion planning framework which finds regions in the task space where trajectories are guaranteed to be of bounded length. We evaluate our method on two different setups with a six-degree-of-freedom (DOF) UR5 as the target system. First our method is validated using a seven-DOF Sawyer as the demonstration system. Then an extensive user study is carried out where several participants are asked to demonstrate, with and without guidance, a mock weld task using a hand held tool tracked by a VICON system. With guidance users were able to always carry out the task successfully in comparison to only 44% of the time without guidance. Copyright © 2023, The Authors. All rights reserved.

关键词： Demonstrations

来源：评论

学校读者我要写书评

暂无评论

Gumiho: A Hybrid Architecture to Prioritize Early Tokens in Speculative Decoding

arXiv

引用

arXiv 2025年

作者： Li, Jinze Xu, Yixing Huang, Haiduo Yin, Xuanwu Li, Dong Ngai, Edith C.H. Barsoum, Emad Department of Electrical and Electronic Engineering The University of Hong Kong Hong Kong Advanced Micro Devices Inc. Beijing China Institute of Artificial Intelligence and Robotics Xi’an Jiaotong University China

Speculative decoding (SPD) aims to accelerate the auto-regressive token generation process of a target Large Language Model (LLM). Some approaches employ a draft model with multiple heads to predict a sequence of future tokens, where each head handles a token in the sequence. The target LLM verifies the predicted sequence and accepts aligned tokens, enabling efficient multi-token generation. However, existing methods assume that all tokens within a sequence are equally important, employing identical head structures and relying on a single-generation paradigm, either serial or parallel. To this end, we theoretically demonstrate that initial tokens in the draft sequence are more important than later ones. Building on this insight, we propose Gumiho, a hybrid model combining serial and parallel heads. Specifically, given the critical importance of early tokens, we employ a sophisticated Transformer architecture for the early draft heads in a serial configuration to improve accuracy. For later tokens, we utilize multiple lightweight MLP heads operating in parallel to enhance efficiency. By allocating more advanced model structures and longer running times to the early heads, Gumiho achieves improved overall performance. The experimental results demonstrate that our method outperforms existing approaches, fully validating its effectiveness. © 2025, CC BY.

关键词： Decoding

来源：评论

学校读者我要写书评

暂无评论

BRNES: Enabling Security and Privacy-Aware Experience Sharing in Multiagent Robotic and Autonomous Systems

BRNES: Enabling Security and Privacy-Aware Experience Sharin...

引用

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

作者： Md Tamjid Hossain Hung Manh La Shahriar Badsha Anton Netchaev The Advanced Robotics and Automation Lab Computer Science and Engineering University of Nevada Reno Nevada USA Bosch Engineering North America The U.S. Army Corps.

Although experience sharing (ES) accelerates multiagent reinforcement learning (MARL) in an advisor-advisee framework, attempts to apply ES to decentralized multiagent systems have so far relied on trusted environments and over-looked the possibility of adversarial manipulation and inference. Nevertheless, in a real-world setting, some Byzantine attackers, disguised as advisors, may provide false advice to the advisee and catastrophically degrade the overall learning performance. Also, an inference attacker, disguised as an advisee, may conduct several queries to infer the advisors' private information and make the entire ES process questionable in terms of privacy leakage. To address and tackle these issues, we propose a novel MARL framework (BRNES) that heuristically selects a dynamic neighbor zone for each advisee at each learning step and adopts a weighted experience aggregation technique to reduce Byzantine attack impact. Furthermore, to keep the agent's private information safe from adversarial inference attacks, we leverage the local differential privacy (LDP)-induced noise during the ES process. Our experiments show that our framework outperforms the state-of-the-art in terms of the steps to goal, obtained reward, and time to goal metrics. Particularly, our evaluation shows that the proposed framework is 8.32x faster than the current non-private frameworks and 1.41x faster than the private frameworks in an adversarial setting.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Data-driven sleep structure deciphering based on cardiorespiratory signals

引用

Computer Methods and Programs in Biomedicine 2025年 267卷 108769-108769页

作者： Huang, Ming Iwata, Osuke Yokoyama, Kiyoko Tamura, Toshiyo Institute of Advanced Computing and Digital Engineering Shenzhen Institute of Advanced Technology Shenzhen China of Science and Technology Nara Institute of Science and Technology Ikoma Japan of Medical Sciences Nagoya City University Japan School of Data Science Nagoya City University Japan Institute for Healthcare Robotics Waseda University Japan

Background and Objective: : Cardiorespiratory signals provide a novel perspective for understanding sleep structure through the physiological mechanism of cardiopulmonary coupling. This mechanism divides the coupling spectrum into high-frequency (HF) and low-frequency (LF) bands, indicating that signal segments of 4–8 min are optimal for analysis. However, the lack of labels tailored to these signals has led to reliance on the American Academy of Sleep Medicine (AASM) definitions, which are primarily designed for electroencephalogram (EEG) and electrooculogram (EOG) data. This study aims to address the challenge of transitioning from AASM-defined labels to cardiorespiratory-oriented ones and to evaluate the feasibility of using these signals for accurate sleep structure recognition. Methods: To align with the physiological characteristics of cardiorespiratory signals, AASM labels were modified by excluding the N2 stage due to its overlap of stable and unstable non-rapid eye movement (NREM) phases, which introduces ambiguity. The modified dataset focused on the wake, N1, deep sleep (N3), and rapid eye movement (REM) stages. A physiologically-inspired deep-learning model (PIDM) was developed to extract features from cardiorespiratory time series and classify sleep stages. Post-analysis assessed the physiological validity of the model's N2 predictions by evaluating the HF-to-LF ratio and respiratory variability. Results: The pipeline, combining the modified labeling scheme with the PIDM model, achieved balanced accuracy scores of 0.83, 0.86, and 0.78 for wake, deep sleep, and REM stages, respectively in the normal group;and 0.92, 0.95, and 0.90 in the mild and moderate sleep apnea groups. Post-analysis revealed that most N2 samples were attributed to stable NREM sleep, characterized by higher HF-to-LF ratios and lower respiratory variability, aligning with physiological understanding. Conclusions: This study highlights the physiological relevance of cardiorespiratory s

关键词： Electroencephalography

来源：评论

学校读者我要写书评

暂无评论

Full State Quaternion-Based Observer Control for Multirotor Aerial Grasping

Full State Quaternion-Based Observer Control for Multirotor ...

引用

International Conference on Unmanned Aircraft Systems (ICUAS)

作者： I. García-Mosqueda A. Tevera-Ruiz H. Abaunza P. Castillo A. Sanchez-Orta J.D. Chazot Universite de technologie de Compiegne CNRS Heudiasyc/Roberval Compiegne France Tecnologico de Monterrey School of Engineering and Sciences Jalisco Mexico CINVESTAV-Saltillo Robotics and Advanced Manufacturing Mexico

ISBN: (数字)9798331513283

ISBN: (纸本)9798331513290

This paper presents an enhanced observer control strategy for multirotor aerial grasping. Unlike previous approaches, which focused solely on translational dynamics, this method incorporates dual observers-one for the translational subsystem and another for the rotational dynamics. By lever-aging quaternions, the proposed control framework provides a singularity-free representation of orientation while naturally decoupling rotational and translational dynamics. This allows the system to be treated as fully actuated in both position and orientation, improving disturbance rejection and compensating for torques induced by offcenter or asymmetrically shaped objects during grasping. A passive, non-actuated gripper further enhances the drone's ability to interact with objects in real-world scenarios. Experimental validations confirm the robustness and adaptability of the proposed approach, demonstrating its effectiveness in handling dynamic variations in mass and torque while maintaining stable flight.

关键词： Torque Quaternions Grasping Observers Robustness Grippers Aircraft Aerospace control

来源：评论

学校读者我要写书评

暂无评论

Outram: One-shot Global Localization via Triangulated Scene Graph and Global Outlier Pruning

Outram: One-shot Global Localization via Triangulated Scene ...

引用

IEEE International Conference on robotics and Automation (ICRA)

作者： Pengyu Yin Haozhi Cao Thien-Minh Nguyen Shenghai Yuan Shuyang Zhang Kangcheng Liu Lihua Xie Centre for Advanced Robotics Technology Innovation (CARTIN) School of Electrical and Electronic Engineering Nanyang Technological University Singapore Department of Electronic and Computer Engineering the Hong Kong University of Science and Technology Hong Kong SAR China

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

One-shot LiDAR localization refers to the ability to estimate the robot pose from one single point cloud, which yields significant advantages in initialization and relocalization processes. In the point cloud domain, the topic has been extensively studied as a global descriptor retrieval (i.e., loop closure detection) and pose refinement (i.e., point cloud registration) problem both in isolation or combined. However, few have explicitly considered the relationship between candidate retrieval and correspondence generation in pose estimation, leaving them brittle to substructure ambiguities. To this end, we propose a hierarchical one-shot localization algorithm called Outram that leverages substructures of 3D scene graphs for locally consistent correspondence searching and global substructure-wise outlier pruning. Such a hierarchical process couples the feature retrieval and the correspondence extraction to resolve the substructure ambiguities by conducting a local-to-global consistency refinement. We demonstrate the capability of Outram in a variety of scenarios in multiple large-scale outdoor datasets. Our implementation is open-sourced: https://***/Pamphlett/Outram.

关键词： Location awareness Point cloud compression Three-dimensional displays Laser radar Costs Pose estimation Feature extraction

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：