检索结果-内蒙古大学图书馆

Wake Homing Torpedo Guidance Using a Hierarchical Deep Reinforcement Learning Framework

IEEE Access 2025年 13卷 72938-72952页

作者： Hwang, Kunchul Kim, Jinwhan KAIST Robotics Program Daejeon34141 Korea Republic of Agency for Defense Development Gyeongsangnam-do Changwon51667 Korea Republic of KAIST Department of Mechanical Engineering Daejeon34141 Korea Republic of

This paper proposes a novel Hierarchical Deep Reinforcement Learning (HRL) framework for wake homing torpedo guidance, applying the Discrete Event System Specification (DEVS) formalism to design high-level policies and reward shaping functions. Wake homing torpedo guidance generates course commands to enable the torpedo to follow the wake trajectory of a target ship. When the target ship evades the incoming torpedo, the wake trajectory becomes curved, often causing the torpedo to lose track due to the narrow detection range of the wake detection sensor. This necessitates a sophisticated algorithm to consistently track the target ship, particularly in scenarios where the torpedo exits and re-enters the wake trajectory in noisy environments. While heuristic algorithms can handle typical wake trajectories, developing a robust solution for unknown trajectories remains a significant challenge. To address this, we apply a novel reinforcement learning approach to develop the guidance logic and compare its performance with a conventional algorithm-based method. The performance and effectiveness of the proposed approach are demonstrated through numerical simulations. © 2013 IEEE.

关键词： Deep reinforcement learning

来源：评论

学校读者我要写书评

暂无评论

A Novel Hybrid Ureteroscope Tracking for Robotic-Assisted Retrograde Intrarenal Surgery via Recognition of Pathway With Lumen Identification

引用

IEEE robotics and Automation Letters 2025年第6期10卷 6368-6375页

作者： Han, Jung-Min Kwon, Dong-Soo Kyung, Ki-Uk Korea Advanced Institute of Science and Technology Department of the Robotics Program Daejeon34141 Korea Republic of Roen Surgical Inc. Daejeon34051 Korea Republic of Korea Advanced Institute of Science and Technology Department of Mechanical Engineering Daejeon34141 Korea Republic of

Resolving disorientation of the surgeon caused by wrong recognition of scope's position, which often increases procedural time and workload, remains a significant challenge in robotic-assisted retrograde intrarenal surgery (RIRS). This letter introduces a novel hybrid ureteroscope tracking algorithm that integrates low-latency lumen identification with robotic motion data to enhance intrarenal navigation. The system estimates the ureteroscope's position on the centerline of the kidney by recognizing its pathway. In validation tests using a 3D-printed phantom, the proposed method achieved an average localization success rate of 89.2% for major calyx entry and 84.1% for minor calyx entry, with an average computation time of 0.26 seconds, ensuring low-latency operation. Usability testing with ten novice participants demonstrated a 44.5% reduction in cognitive workload (NASA-TLX), improved task success rates, and reduced manipulation effort. These results indicate that the proposed tracking algorithm significantly enhances ureteroscope navigation, improving efficiency and reducing the surgeon's cognitive load in robotic-assisted RIRS. © 2016 IEEE.

关键词： Medical robotics

来源：评论

学校读者我要写书评

暂无评论

Adaptive Robot-Mediated Assessment using LLM for Enhanced Survey Quality in Older Adults Care programs 20

Adaptive Robot-Mediated Assessment using LLM for Enhanced Su...

引用

20th Annual ACM/IEEE International Conference on Human-Robot Interaction, HRI 2025

作者： Park, Cheonshu Cho, Miyoung Shin, Minjung Ryu, Jeh-Kwang Jang, Minsu Social Robotics Research Lab Daejeon Korea Republic of Seoul National University Interdisciplinary Program in Cognitive Science Seoul Korea Republic of Dongguk University Department of Physical Education Seoul Korea Republic of

ISBN: (纸本)9798350378931

This study presents an adaptive human-robot interaction (HRI) system that evaluates older adult participants' satisfaction with personalized health care programs. By integrating the CLOi robot with a large language model (LLM), the system conducts satisfaction surveys that adapt in real-time to participant responses. The system was applied to evaluate healthcare programs that include physical health measurements, exercise assessments, and virtual reality (VR) experiences. The system utilizes the CLOi robot and Claude API to analyze response clarity in real-time, automatically generating contextually appropriate follow-up questions when responses are deemed ambiguous. This adaptive questioning strategy ensures comprehensive response quality before proceeding to subsequent survey items. We conducted a preliminary feasibility study with five older adult participants to evaluate our approach. The system leverages LLM prompts to analyze gaps between question intent and participant responses, generating targeted follow-up questions as needed. Results demonstrate that our LLM-enhanced robotic interview system effectively reduced response ambiguity through dynamic follow-up questioning, achieving an 85% response resolution rate. This adaptive approach improved the clarity and specificity of healthcare satisfaction assessments for older adults. © 2025 IEEE.

关键词： Industrial robots

来源：评论

学校读者我要写书评

暂无评论

Convergent effects of peptides on the initiation of feeding motor programs in the mollusk Aplysia

引用

Journal of Neurophysiology 2025年第5期133卷 1368-1379页

作者： Evans, Colin G. Barry, Michael A. Reaver, Carrie N. Patel, Paras R. Chestek, Cynthia A. Perkins, Matthew H. Jing, Jian Cropper, Elizabeth C. Department of Neuroscience Friedman Brain Institute Icahn School of Medicine at Mount Sinai New York NY United States Department of Biomedical Engineering Biointerfaces Institute University of Michigan Ann Arbor MI United States Department of Electrical Engineering and Computer Science Neurosciences Program Robotics Program University of Michigan Ann Arbor MI United States State Key Laboratory of Pharmaceutical Biotechnology Institute for Brain Sciences Chemistry and Biomedicine Innovation Center Jiangsu Engineering Research Center for MicroRNA Biology and Biotechnology Advanced Institute for Life Sciences School of Life Sciences Nanjing University Nanjing China

Neuropeptides configure the feeding network of Aplysia. For example, egestive activity is promoted by small cardioactive peptide (SCP), and ingestive activity is promoted by a combination of feeding circuit activating peptide (FCAP) and cerebral peptide 2 (CP-2). In addition, SCP and FCAP/CP-2 have a common network effect that does not contribute to motor program specification. They increase the excitability of an interneuron, B63. In this report, we further characterized the effects of peptides on B63. We performed voltage-clamp experiments and used a step protocol to look at steady-state currents. We found that SCP and FCAP/CP-2 both induced an inward current that was virtually absent in low-sodium saline. Previous work has established that B63 is unusual in the feeding circuit in that subthreshold depolarizations are autonomously generated that can trigger motor programs. Here, we show that this autonomous activity is more frequent in the presence of peptides. Previous studies have also shown that activity of the feeding central pattern generator (CPG) can be initiated by neurons that excite B63, e.g., by cerebral buccal interneuron 2 (CBI-2), a projection neuron that triggers biting-like motor programs. Here, we show that the latency of CBI-2-induced activity is decreased by stimulation of the esophageal nerve (EN) (which releases endogenous SCP). These results, taken together with previous results, indicate that peptides that act divergently to configure network activity additionally act convergently to promote motor program induction. We present data that suggest that this arrangement facilitates brief switches between ingestive and egestive motor activity. © 2025 The Authors.

关键词： central pattern generator invertebrate modulation motor program neuropeptide

来源：评论

学校读者我要写书评

暂无评论

Material informatics-driven insights into brain cancer nanocarriers: A bibliometric comparison of PLGA vs. liposomes

引用

OpenNano 2025年 21卷

作者： Makalew, Brilly Andro Abrori, Syauqi Abdurrahman Computer Science Department School of Computer Science Bina Nusantara University Jakarta 11480 Indonesia Automotive & Robotics Program Computer Engineering Department BINUS ASO School of Engineering Bina Nusantara University Jakarta 11480 Indonesia

This study explores a comparative analysis of PLGA nanoparticles and liposomes as potential carriers for brain cancer drug delivery, with a special focus on how material informatics enhances their design, biocompatibility, and drug release profiles to improve treatment efficacy and contribute to sustainable health outcomes. The investigation employed a bibliometric analysis using Scopus and VOSviewer to uncover the role of material informatics in optimizing these nanocarriers. The analysis revealed that material informatics, particularly through the application of machine learning and molecular dynamics simulations, significantly optimizes the performance of both PLGA nanoparticles and liposomes. The results highlighted distinct strengths of each nanocarrier: PLGA nanoparticles excel in biodegradability, while liposomes offer superior drug encapsulation capabilities. However, material informatics techniques bridged these enhancing drug release kinetics, stability, and biocompatibility. These improvements are crucial for effective delivery across the blood-brain barrier, a major challenge in brain cancer treatment. The integration of computational modelling, machine learning, and high-throughput screening enabled by material informatics is shown to be a key factor in advancing the design and optimization of these nanocarriers. By leveraging these tools, researchers can develop more personalized and efficient drug delivery systems tailored to address the specific challenges of glioblastoma therapy, ultimately contributing to sustainable health outcomes © 2024 The Author(s)

关键词： Bibliometric analysis Brain cancer Drug delivery Liposomes Material informatics Nanocarriers PLGA nanoparticles VOSviewer

来源：评论

学校读者我要写书评

暂无评论

Adaptive Robot-Mediated Assessment using LLM for Enhanced Survey Quality in Older Adults Care programs 25

Adaptive Robot-Mediated Assessment using LLM for Enhanced Su...

引用

ACM/IEEE International Conference on Human-Robot Interaction (HRI)

作者： Cheonshu Park Miyoung Cho Minjung Shin Jeh-Kwang Ryu Minsu Jang Social Robotics Research Lab Electronics and Telecommunications Research Institute (ETRI) Daejeon Republic of Korea Interdisciplinary Program in Cognitive Science Seoul National University Seoul Republic of Korea Department of Physical Education Dongguk University Seoul Republic of Korea

ISBN: (数字)9798350378931

ISBN: (纸本)9798350378948

关键词： Surveys Large language models Human-robot interaction Medical services Virtual reality Particle measurements Real-time systems Question generation Older adults Robots

来源：评论

学校读者我要写书评

暂无评论

Goal-Conditioned Reinforcement Learning Approach for Autonomous Parking in Complex Environments

Goal-Conditioned Reinforcement Learning Approach for Autonom...

引用

International Conference on Artificial Intelligence in Information and Communication (ICAIIC)

作者： Taeyoung Kim Taemin Kang Seungah Son Kuk Won Ko Dongsoo Har CCS Graduate School of Mobility Korea Advanced Institute of Science and Technology(KAIST) Daejeon Rep. of Korea The Robotics Program Korea Advanced Institute of Science and Technology(KAIST) Daejeon Rep. of Korea Department of Future Mobility Engineering Halla University Wonju Rep. of Korea

ISBN: (数字)9798331507022

ISBN: (纸本)9798331507039

In complex urban environments, autonomous vehicle parking is challenged by irregularly parked cars, static obstacles, and narrow spaces. Traditional parking methods are often limited to well-structured parking lots and fail to adapt to unstructured scenarios like alleyways with obstacles and randomly positioned vehicles. This paper addresses this limitation by applying goal-conditioned reinforcement learning to enable autonomous vehicles to park in congested environments based on specified target positions and orientations. A custom simulation environment is developed using Pygame to simulate parking scenarios across four progressive levels of difficulty, with obstacles to test adaptability. Three RL algorithms, SAC, HER, and an improved HER variant, are implemented to compare the performance in the simulation environment. Experimental results demonstrate that the proposed approach significantly improves parking success rates and trajectory efficiency in complex scenarios, contributing to robust, adaptable parking solutions for autonomous vehicles in real-world applications.

关键词： Training Space vehicles Three-dimensional displays Urban areas Reinforcement learning Trajectory Reliability Vehicle dynamics Autonomous vehicles Testing

来源：评论

学校读者我要写书评

暂无评论

Dual-UNet: An End-to-End Deep Learning Framework for the Automatic Chronic Diabetic Wound Segmentation

Dual-UNet: An End-to-End Deep Learning Framework for the Aut...

引用

Computing and Information Technology (ICCIT-1441), 2020 International Conference on

作者： Mustafa Alhababi Gregory Auner Hafiz Malik Lubna Alazzawi Muteb Aljasem Electrical and Computer Engineering Wayne State University Detroit MI USA Department of Smart Sensors and Integrated Microsystems Program Wayne State University Detroit MI USA Electrical and Computer Engineering University of Michigan-Dearborn Dearborn MI USA Electronics and Computer Engineering & Robotics Engineering Bowling Green State University Bowling Green OH USA

ISBN: (数字)9798350353839

ISBN: (纸本)9798350353846

Foot ulcers are one of the chronic wounds commonly occurring in diabetic patients and are associated with a high risk of major or minor amputations. Evaluation and measurement of such wounds are done manually by experts to assess the wound healing and suggest further treatment. Manual assessment methods can cause infections at times and are less feasible in the existence of pandemic situations. The development of artificial intelligence has brought a revolution in many domains of medical imaging. Deep learning-based computer-aided approaches can be applied to assist clinicians in assessing and monitoring chronic wounds. Wound segmentation helps to measure wound area which is useful for assessing its healing progress. In this research work, a deep learning-based segmentation method, namely Dual-UNet is presented for precisely segmenting the diabetic foot ulcers images. The foot ulcer images are passed to Dual-UNet to generate the mask image having the segmented wound area. We proposed two modified UNets each having a customized encoder and decoder with skip connections, atrous spatial pyramid pooling (ASPP) block, and output block to improve the segmentation results. We assessed our framework by performing experimentation on two benchmark datasets, named the foot ulcer segmentation (FUSeg) challenge and the AZH segmentation dataset. Additionally, we have also assessed our Dual-UNet for cross-corpora validation to demonstrate the generalization capability of the proposed approach. The qualitative and quantitative results highlight the accuracy and effectiveness of the Dual-UN et framework for segmenting chronic diabetic wounds. Future research should focus on the development of large and diverse wound datasets and improving the results for cross-corpora evaluation.

关键词： Deep learning Image segmentation Pandemics Computational modeling Manuals Wounds Diabetes Decoding Information technology Monitoring

来源：评论

学校读者我要写书评

暂无评论

OriSnake: Design, Fabrication, and Experimental Analysis of a 3-D Origami Snake Robot

引用

IEEE robotics and Automation Letters 2018年第3期3卷 1993-1999页

作者： Luo, Ming Yan, Ruibo Wan, Zhenyu Qin, Yun Santoso, Junius Skorina, Erik H. Onal, Cagdas D. Mechanical Engineering Department and Robotics Engineering Program Worcester Polytechnic Institute WorcesterMA01609 United States

Snake robots offer a useful and unique mobility platform for search-and-rescue applications. However, existing prototypes made of rigid links and joints are hampered by a lack of flexibility that limits their utility in highly cluttered, maze-like environments, and their heavy weight limits their energy-efficiency and performance in three-dimensional (3-D) tasks. To address these challenges, this letter presents a new approach using cylindrical, origami continuum modules driven by internal cables and electric motors, as well as a local feedback control system on each module. Thus, we can distribute actuation, sensing, and control for highly scalable soft robotic continuum origami systems. Using this approach, we develop a 3-D origami robotic snake that is able to locomote using lateral undulation and sidewinding gaits similar to those used by biological snakes. The proposed snake robot is a continuously deformable, lightweight, modular, and low cost robotic system made of a folded thin plastic body. We detail the design, fabrication, and control of this first 3-D origami robotic snake prototype, focusing on the analysis of locomotion parameters for each gait. We experimentally search for the optimal parameters for both types of locomotion, with maximum speeds characterized as 40.5 mm/s (0.1 body-lengths per second) for lateral undulation and 35 mm/s (0.09 body-lengths per second) for sidewinding locomotion. © 2016 IEEE.

关键词： Fabrication

来源：评论

学校读者我要写书评

暂无评论

Supply Chain Sustainability in Disruption: SC Intelligence, Customer Knowledge Transfer, and the Mediating Role of IS/IT

引用

IEEE Engineering Management Review 2025年

作者： Ratna, Silvia Saide, Saide Rater, Salya Svyazhanovna, Baizakova Saule Herzavina, Herzavina Faculty of Information Technology Department of Informatics Engineering and Department of Information Systems Banjarmasin Indonesia State Islamic University of Sultan Syarif Kasim Riau Universitas Islam Negeri Sultan Syarif Kasim Riau-UIN SUSKA Riau Department of Information Systems Faculty of Science and Technology Indonesia PRO Knowledge Indonesia Pekanbaru Indonesia Universitas Pahlawan Tuanku Tambusai Indonesia Lembaga Enreach UIN Suska Riau Indonesia Politeknik Aceh Selatan Department of Informatics Engineering Aceh Indonesia Information Communication Technologies Robotics in Arkalyk Pedagogical Institute Master of Natural Sciences Educational Program for the Informatics Computer Science Kazakhstan Universitas Pahlawan Tuanku Tambusai Department of Informatics Engineering Indonesia National Taiwan University of Science and Technology Taiwan

Knowledge resource and information system/technology (IS/IT) capability have been considered to improve firm performance, however there is still a gap regarding the sustainability of supply chain to face and recover from disruption (e.g., COVID-19). Questionnaire-based surveys was adopted and received feedback from sixty (160) Indonesian companies or about 28.07% of response rate. © 1973-2011 IEEE.

关键词： customer knowledge transfer disruption information system/technology (IS/IT) responding knowledge management resource-based view (RBV) Supply chain (SC) sustainability supply chain knowledge transfer

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：