IEEE Robotics and Automation Letters最新文献_第7页

Design of Wheel Grouser Geometry With Reduced Sinkage for LEV-1 Lunar Rover LEV-1月球车减小沉陷的轮槽几何设计

IF 4.6 2区计算机科学

IEEE Robotics and Automation Letters Pub Date : 2025-04-16 DOI: 10.1109/LRA.2025.3561571

Masatsugu Otsuki;Kent Yoshikawa;Takao Maeda;Naoto Usami;Tetsuo Yoshimitsu

引用次数: 0

Personalizing Human Gait Entrainment: A Reinforcement Learning Approach to Optimizing Magnitude of Periodic Mechanical Perturbations 个性化人类步态干扰：一种优化周期性机械扰动幅度的强化学习方法

IF 4.6 2区计算机科学

IEEE Robotics and Automation Letters Pub Date : 2025-04-16 DOI: 10.1109/LRA.2025.3561574

Omik Save;Junmin Zhong;Suhrud Joglekar;Jennie Si;Hyunglae Lee

{"title":"Personalizing Human Gait Entrainment: A Reinforcement Learning Approach to Optimizing Magnitude of Periodic Mechanical Perturbations","authors":"Omik Save;Junmin Zhong;Suhrud Joglekar;Jennie Si;Hyunglae Lee","doi":"10.1109/LRA.2025.3561574","DOIUrl":"https://doi.org/10.1109/LRA.2025.3561574","url":null,"abstract":"The feasibility of gait entrainment to periodic mechanical perturbations varies with perturbation magnitude in neurotypical individuals. Effective design of gait entrainment studies thus requires a systematic approach to personalize periodic perturbation parameters. However, current studies still rely on manually selecting the perturbation magnitude, a practice that is neither efficient nor optimal for individual users. This study proposes a new reinforcement learning (RL) method to personalize the minimum magnitude of periodic perturbation to hip flexion that ensures successful entrainment. The method entails offline learning and in situ adaptation (OLAP), where offline learning involves training a deep Q-network (DQN), which is subsequently used in situ to guide the adaptive selection of an optimal perturbation magnitude for individuals. This study recruited thirteen healthy participants, with entrainment characteristics data from seven participants used for offline DQN training. The remaining six participants performed in situ adaptation to identify their personalized optimal perturbation parameters. Results demonstrate that the OLAP agent effectively tailored a minimum perturbation magnitude for each of the six participants in the adaptation group, leveraging generalization from the DQN policy. All adaptation group participants achieved a 100% entrainment success rate at their personalized perturbation magnitude during a 3-trial post-evaluation session, highlighting the agent's effectiveness. The efficiency and robustness of our approach underscore its significance in designing future optimal gait entrainment studies for diverse population groups.","PeriodicalId":13241,"journal":{"name":"IEEE Robotics and Automation Letters","volume":"10 6","pages":"5673-5680"},"PeriodicalIF":4.6,"publicationDate":"2025-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143900546","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Path Planning for Robot Assisted Steerable Bevel-Tip Needle in 3D Dynamic Environment 三维动态环境下机器人辅助可操纵斜尖针路径规划

IF 4.6 2区计算机科学

IEEE Robotics and Automation Letters Pub Date : 2025-04-16 DOI: 10.1109/LRA.2025.3562010

Kaushik Halder;M. Felix Orlando

{"title":"Path Planning for Robot Assisted Steerable Bevel-Tip Needle in 3D Dynamic Environment","authors":"Kaushik Halder;M. Felix Orlando","doi":"10.1109/LRA.2025.3562010","DOIUrl":"https://doi.org/10.1109/LRA.2025.3562010","url":null,"abstract":"In Minimally Invasive Surgery (MIS), achieving target-reaching accuracy without colliding with anatomical obstacles is the most crucial aspect. However, due to the non-holonomic constraints within the tissue environment and the dynamic behavior during needle insertion, planning an appropriate path presents a significant and complex challenge. In order to address the above-mentioned challenges, this study introduces a novel path-planning approach for a robot-assisted flexible bevel-tip needle within the tissue region. The primary contribution of this path planner is its ability to incorporate a dynamic 3D environment, which includes multiple targets and obstacles with varying locations. In the literature, there are several methods for planning obstacle-free paths within the tissue region. Among them, the Rapidly-Exploring-Random-Trees (RRT) based path planner methodology is advantageous due to its reduced computational time and suitability for high-dimensional spaces. The proposed algorithm builds upon the RRT technique, enhancing it with a greediness concept to handle multiple dynamic targets. Additionally, extensive simulations and experimental studies have been conducted to demonstrate the efficacy of the proposed method, with a view toward future clinical tests. Statistical analysis of the proposed path planner methodology has also been performed, focusing on computational time for finding feasible paths and the length of the planned trajectory.","PeriodicalId":13241,"journal":{"name":"IEEE Robotics and Automation Letters","volume":"10 6","pages":"5887-5894"},"PeriodicalIF":4.6,"publicationDate":"2025-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143902732","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

HomeEmergency - Using Audio to Find and Respond to Emergencies in the Home 家庭紧急情况-使用音频查找和应对家庭紧急情况

IF 4.6 2区计算机科学

IEEE Robotics and Automation Letters Pub Date : 2025-04-16 DOI: 10.1109/LRA.2025.3561570

James F. Mullen;Dhruva Kumar;Xuewei Qi;Rajasimman Madhivanan;Arnie Sen;Dinesh Manocha;Richard Kim

{"title":"HomeEmergency - Using Audio to Find and Respond to Emergencies in the Home","authors":"James F. Mullen;Dhruva Kumar;Xuewei Qi;Rajasimman Madhivanan;Arnie Sen;Dinesh Manocha;Richard Kim","doi":"10.1109/LRA.2025.3561570","DOIUrl":"https://doi.org/10.1109/LRA.2025.3561570","url":null,"abstract":"In the United States alone accidental home deaths exceed 128,000 per year. Our work aims to enable home robots who respond to emergency scenarios in the home, preventing injuries and deaths. We introduce a new dataset of household emergencies based in the ThreeDWorld simulator. Each scenario in our dataset begins with an instantaneous or periodic sound which may or may not be an emergency. The agent must navigate the multi-room home scene using prior observations, alongside audio signals and images from the simulator, to determine if there is an emergency or not. In addition to our new dataset, we present a modular approach for localizing and identifying potential home emergencies. Underpinning our approach is a novel probabilistic dynamic scene graph (P-DSG), where our key insight is that graph nodes corresponding to agents can be represented with a probabilistic edge. This edge, when refined using Bayesian inference, enables efficient and effective localization of agents in the scene. We also utilize multi-modal vision-language models (VLMs) as a component in our approach, determining object traits (e.g. flammability) and identifying emergencies. We present a demonstration of our method completing a real-world version of our task on a consumer robot, showing the transferability of both our task and our method. Our dataset will be released to the public upon this letters publication.","PeriodicalId":13241,"journal":{"name":"IEEE Robotics and Automation Letters","volume":"10 6","pages":"5649-5656"},"PeriodicalIF":4.6,"publicationDate":"2025-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143900547","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

VTD: Visual and Tactile Dataset for Driver State and Behavior Detection 驾驶员状态和行为检测的视觉和触觉数据集

IF 4.6 2区计算机科学

IEEE Robotics and Automation Letters Pub Date : 2025-04-16 DOI: 10.1109/LRA.2025.3561563

Jie Wang;Mobing Cai;Zhongpan Zhu;Hongjun Ding;Jiwei Yi;Aimin Du

引用次数: 0

Globally-Guided Geometric Fabrics for Reactive Mobile Manipulation in Dynamic Environments 动态环境中响应式移动操作的全局引导几何结构

IF 4.6 2区计算机科学

IEEE Robotics and Automation Letters Pub Date : 2025-04-16 DOI: 10.1109/LRA.2025.3562005

Tomas Merva;Saray Bakker;Max Spahn;Danning Zhao;Ivan Virgala;Javier Alonso-Mora

{"title":"Globally-Guided Geometric Fabrics for Reactive Mobile Manipulation in Dynamic Environments","authors":"Tomas Merva;Saray Bakker;Max Spahn;Danning Zhao;Ivan Virgala;Javier Alonso-Mora","doi":"10.1109/LRA.2025.3562005","DOIUrl":"https://doi.org/10.1109/LRA.2025.3562005","url":null,"abstract":"Mobile manipulators operating in dynamic environments shared with humans and robots must adapt in real time to environmental changes to complete their tasks effectively. While global planning methods are effective at considering the full task scope, they lack the computational efficiency required for reactive adaptation. In contrast, local planning approaches can be executed online but are limited by their inability to account for the full task's duration. To tackle this, we propose Globally-Guided Geometric Fabrics (G3F), a framework for real-time motion generation along the full task horizon, by interleaving an optimization-based planner with a fast reactive geometric motion planner, called Geometric Fabrics (GF). The approach adapts the path and explores a multitude of acceptable target poses, while accounting for collision avoidance and the robot's physical constraints. This results in a real-time adaptive framework considering whole-body motions, where a robot operates in close proximity to other robots and humans. We validate our approach through various simulations and real-world experiments on mobile manipulators in multi-agent settings, achieving improved success rates compared to vanilla GF, Prioritized Rollout Fabrics and Model Predictive Control.","PeriodicalId":13241,"journal":{"name":"IEEE Robotics and Automation Letters","volume":"10 6","pages":"5553-5560"},"PeriodicalIF":4.6,"publicationDate":"2025-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10967245","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143888291","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

SDD-SLAM: Semantic-Driven Dynamic SLAM With Gaussian Splatting SDD-SLAM：语义驱动的高斯溅射动态SLAM

IF 4.6 2区计算机科学

IEEE Robotics and Automation Letters Pub Date : 2025-04-16 DOI: 10.1109/LRA.2025.3561565

Haosong Liu;Long Wang;Haiyong Luo;Fang Zhao;Runze Chen;Yushi Chen;Mingyu Xiao;Jiaquan Yan;Dan Luo

引用次数: 0

Ankle Exoskeleton Control via Data-Driven Gait Estimation for Walking, Running, and Inclines 基于数据驱动的步态估计的踝关节外骨骼控制，用于行走、跑步和倾斜

IF 4.6 2区计算机科学

IEEE Robotics and Automation Letters Pub Date : 2025-04-16 DOI: 10.1109/LRA.2025.3561566

Pavan R. Shetty;Jayston A. Menezes;Seungmoon Song;Aaron J. Young;Max K. Shepherd

{"title":"Ankle Exoskeleton Control via Data-Driven Gait Estimation for Walking, Running, and Inclines","authors":"Pavan R. Shetty;Jayston A. Menezes;Seungmoon Song;Aaron J. Young;Max K. Shepherd","doi":"10.1109/LRA.2025.3561566","DOIUrl":"https://doi.org/10.1109/LRA.2025.3561566","url":null,"abstract":"Ankle exoskeletons have the potential to augment mobility, but control strategies have largely failed to seamlessly adapt to changes in the locomotion task. Here, we introduce a multi-headed network that predicts gait speed, ground incline, stance/swing transitions, and percent stance. These predictions are mapped to exoskeleton torque using typical biological torques as a guide. The model was trained on 9 subjects walking/jogging for 12 minutes across a range of speeds and inclines. The controller was validated on 4 subjects, and achieved stance phase prediction error of 3.4% across a range of speeds and inclines, both inside and outside the training set distribution. A secondary analysis showed similar accuracy could have been obtained with only 10% of the collected data, suggesting researchers may need fewer total strides of training data, provided the data is sufficiently diverse across users and tasks. Metabolic cost was improved during running compared to wearing the exoskeleton powered off, but was beneficial for only one subject during level walking and ramp ascent when compared to no exoskeleton. Overall, our controller smoothly adapted to time-varying inclines and walking/jogging speeds, and achieved high accuracy with a reduced training dataset, though larger torque magnitudes may be required to see metabolic benefit.","PeriodicalId":13241,"journal":{"name":"IEEE Robotics and Automation Letters","volume":"10 6","pages":"5855-5862"},"PeriodicalIF":4.6,"publicationDate":"2025-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143901868","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Genetic Approach to Gradient-Free Kinodynamic Planning in Uneven Terrains 不平整地形无梯度动力学规划的遗传方法

IF 4.6 2区计算机科学

IEEE Robotics and Automation Letters Pub Date : 2025-04-15 DOI: 10.1109/LRA.2025.3560883

Otobong Jerome;Alexandr Klimchik;Alexander Maloletov;Geesara Kulathunga

引用次数: 0

Seeing Through Pixel Motion: Learning Obstacle Avoidance From Optical Flow With One Camera 透过像素运动：学习避障从光流与一个相机

IF 4.6 2区计算机科学

IEEE Robotics and Automation Letters Pub Date : 2025-04-15 DOI: 10.1109/LRA.2025.3560842

Yu Hu;Yuang Zhang;Yunlong Song;Yang Deng;Feng Yu;Linzuo Zhang;Weiyao Lin;Danping Zou;Wenxian Yu

{"title":"Seeing Through Pixel Motion: Learning Obstacle Avoidance From Optical Flow With One Camera","authors":"Yu Hu;Yuang Zhang;Yunlong Song;Yang Deng;Feng Yu;Linzuo Zhang;Weiyao Lin;Danping Zou;Wenxian Yu","doi":"10.1109/LRA.2025.3560842","DOIUrl":"https://doi.org/10.1109/LRA.2025.3560842","url":null,"abstract":"Optical flow captures the motion of pixels in an image sequence over time, providing information about movement, depth, and environmental structure. Flying insects utilize this information to navigate and avoid obstacles, allowing them to execute highly agile maneuvers even in complex environments. Despite its potential, autonomous flying robots have yet to fully leverage this motion information to achieve comparable levels of agility and robustness. The main challenges are two-fold: 1) extracting accurate optical flow from visual data during high-speed flight and 2) designing a robust controller that can handle noisy optical flow estimations while ensuring robust performance in complex environments. To address these challenges, we propose a novel end-to-end system for quadrotor obstacle avoidance using monocular optical flow. We develop an efficient differentiable simulator coupled with a simplified quadrotor model, allowing our policy to be trained directly through first-order gradient optimization. Additionally, we introduce a central flow attention mechanism and an action-guided active sensing strategy that enhances the policy's focus on task-relevant optical flow observations to enable more responsive decision-making during flight. Our system is validated both in simulation and the real world using an FPV racing drone. Despite being trained in a simple environment in simulation, our system demonstrates agile and robust flight in various unknown, cluttered environments in the real world at speeds of up to 6 m/s.","PeriodicalId":13241,"journal":{"name":"IEEE Robotics and Automation Letters","volume":"10 6","pages":"5871-5878"},"PeriodicalIF":4.6,"publicationDate":"2025-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143902625","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0