IEEE Robotics and Automation Letters最新文献_第10页

Rapidly Tunable Stiffness Soft Gripper for Multifunctional Grasping

IF 4.6 2区计算机科学

IEEE Robotics and Automation Letters Pub Date : 2024-11-22 DOI: 10.1109/LRA.2024.3505822

Jiawei Xu;Qingyue Li;Wenxiang Xie;Xu Dong;Yaoyao Jiang;Lvzhou Li;Jianning Ding

{"title":"Rapidly Tunable Stiffness Soft Gripper for Multifunctional Grasping","authors":"Jiawei Xu;Qingyue Li;Wenxiang Xie;Xu Dong;Yaoyao Jiang;Lvzhou Li;Jianning Ding","doi":"10.1109/LRA.2024.3505822","DOIUrl":"https://doi.org/10.1109/LRA.2024.3505822","url":null,"abstract":"The flexible gripper exhibits limited load capacity while possessing dexterity and adaptability to complex environments. Conversely, the thermally-driven variable stiffness gripper boasts high load capacity but suffers from slow response times. This study presents a multifunctional flexible gripper characterized by rapid response and high load capacity, achieved through a combination of thermally responsive variable stiffness fingers and a jet-cooling system. The thermally responsive variable stiffness fingers are composed of a layered material comprising liquid metal particles and shape memory polymer composites, with stiffness ranging from 3.56 MPa to 4356 MPa, spanning three orders of magnitude. The maximum load capacity reaches \u0000<inline-formula><tex-math>$sim$</tex-math></inline-formula>\u000013 N (single finger at 15 mm deflection) with a maximum bending angle of \u0000<inline-formula><tex-math>$sim 82^{circ }$</tex-math></inline-formula>\u0000 and a rapid stiffening speed of \u0000<inline-formula><tex-math>$sim$</tex-math></inline-formula>\u00002 s. The gripper, consisting of three fingers, can grasp objects up to \u0000<inline-formula><tex-math>$sim$</tex-math></inline-formula>\u000054 times finger weight, including oranges, empty plastic cups, and other deformable objects. We discuss the thermal-stiffness response characteristics and mechanical properties and demonstrate the variable stiffness gripper's ability to grasp targets of different sizes and masses in various initial orientations. This work shows the potential applications of flexible manipulators in the rapid, damage-free grasping domain.","PeriodicalId":13241,"journal":{"name":"IEEE Robotics and Automation Letters","volume":"10 1","pages":"708-715"},"PeriodicalIF":4.6,"publicationDate":"2024-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142821197","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

Adaptive Dynamic Programming-Based Fixed-Time Optimal Control for Wheeled Mobile Robot

IF 4.6 2区计算机科学

IEEE Robotics and Automation Letters Pub Date : 2024-11-21 DOI: 10.1109/LRA.2024.3504314

Chen Wang;Haoran Zhan;Qing Guo;Tieshan Li

引用次数: 0

Autonomous Navigation of Soft Rolling Microrobots Under a Helmholtz Coil System Across Fields of View Using Image Stitching 利用图像拼接技术实现软滚动微型机器人在亥姆霍兹线圈系统下的跨视场自主导航

IF 4.6 2区计算机科学

IEEE Robotics and Automation Letters Pub Date : 2024-11-21 DOI: 10.1109/LRA.2024.3504234

Lijun Fang;Hoyeon Kim;Zhaowen Su;U Kei Cheang

{"title":"Autonomous Navigation of Soft Rolling Microrobots Under a Helmholtz Coil System Across Fields of View Using Image Stitching","authors":"Lijun Fang;Hoyeon Kim;Zhaowen Su;U Kei Cheang","doi":"10.1109/LRA.2024.3504234","DOIUrl":"https://doi.org/10.1109/LRA.2024.3504234","url":null,"abstract":"Under the guidance of an integrated control and imaging system, magnetic microrobots have the capability to navigate within narrow spaces to perform tasks such as cargo delivery and manipulations. However, due to the difficulty of balancing image resolution and width of the field of view (FOV), achieving accurate autonomous navigation of microrobots in large workspaces remains a significant challenge. This letter introduces a control strategy aided by image stitching to address this challenge. First, an image stitching algorithm based on key point matching, a motorized mobile platform, and a camera were used to obtain a global map that spanned multiple FOVs. Then, an A* global path planning algorithm was used to calculate the collision-free optimal path. Next, a key point matching method was used to calculate the local path in the FOV where the microrobot was located. Finally, a closed-loop control algorithm and the mobile platform were used to guide the microrobots to the endpoint in the global space. This control strategy was demonstrated in experiments using soft alginate microrobots in microchannels that spanned multiple FOVs. Experiments showed that this method was able to obtain global maps of large workspaces with high accuracy through image stitching and guide microrobots through different environments with different channel geometries. The results of this work demonstrated the possibility of using microrobots for automated tasks in more than one FOV, which can significantly widen the range of microrobotic applications.","PeriodicalId":13241,"journal":{"name":"IEEE Robotics and Automation Letters","volume":"10 1","pages":"820-827"},"PeriodicalIF":4.6,"publicationDate":"2024-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142825934","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

San Francisco World: Leveraging Structural Regularities of Slope for 3-DoF Visual Compass

IF 4.6 2区计算机科学

IEEE Robotics and Automation Letters Pub Date : 2024-11-21 DOI: 10.1109/LRA.2024.3504315

Jungil Ham;Minji Kim;Suyoung Kang;Kyungdon Joo;Haoang Li;Pyojin Kim

{"title":"San Francisco World: Leveraging Structural Regularities of Slope for 3-DoF Visual Compass","authors":"Jungil Ham;Minji Kim;Suyoung Kang;Kyungdon Joo;Haoang Li;Pyojin Kim","doi":"10.1109/LRA.2024.3504315","DOIUrl":"https://doi.org/10.1109/LRA.2024.3504315","url":null,"abstract":"We propose the San Francisco world (SFW) model, a novel structural model inspired by San Francisco's hilly terrain, enabling 3D inter-floor navigation in urban areas rather than being limited to 2D intra-floor navigation of various robotics platforms. Our SFW consists of a single vertical dominant direction (VDD), two horizontal dominant directions (HDDs), and four sloping dominant directions (SDDs) sharing a common inclination angle. Although SFW is a more general model than the Manhattan world (MW), it is a more compact model than the mixture of Manhattan world (MMW). Leveraging the structural regularities of SFW, such as uniform inclination angle and geometric patterns of the four SDDs, we design an efficient and robust DD/vanishing point estimation method by aggregating sloping line normals on the Gaussian sphere. We further utilize the structural patterns of SFW for the 3-DoF visual compass, the rotational motion tracking from a single line and plane, which corresponds to the theoretical minimal sampling for 3-DoF rotation estimation. Our method demonstrates enhanced adaptability in more challenging inter-floor scenes in urban areas and the highest rotational tracking accuracy compared to state-of-the-art methods. We release the first dataset of sequential RGB-D images captured in San Francisco world (SFW) and open source codes at: \u0000<uri>https://SanFranciscoWorld.github.io/</uri>\u0000.","PeriodicalId":13241,"journal":{"name":"IEEE Robotics and Automation Letters","volume":"10 1","pages":"382-389"},"PeriodicalIF":4.6,"publicationDate":"2024-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142777710","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

Large-Scale Multi-Session Point-Cloud Map Merging 大规模多会期点云图合并

IF 4.6 2区计算机科学

IEEE Robotics and Automation Letters Pub Date : 2024-11-21 DOI: 10.1109/LRA.2024.3504317

Hairuo Wei;Rundong Li;Yixi Cai;Chongjian Yuan;Yunfan Ren;Zuhao Zou;Huajie Wu;Chunran Zheng;Shunbo Zhou;Kaiwen Xue;Fu Zhang

{"title":"Large-Scale Multi-Session Point-Cloud Map Merging","authors":"Hairuo Wei;Rundong Li;Yixi Cai;Chongjian Yuan;Yunfan Ren;Zuhao Zou;Huajie Wu;Chunran Zheng;Shunbo Zhou;Kaiwen Xue;Fu Zhang","doi":"10.1109/LRA.2024.3504317","DOIUrl":"https://doi.org/10.1109/LRA.2024.3504317","url":null,"abstract":"This paper introduces LAMM, an open-source framework for large-scale multi-session 3D LiDAR point cloud map merging. LAMM can automatically integrate sub-maps from multiple agents carrying LiDARs with different scanning patterns, facilitating place feature extraction, data association, and global optimization in various environments. Our framework incorporates two key novelties that enable robust, accurate, large-scale map merging. The first novelty is a temporal bidirectional filtering mechanism that removes dynamic objects from 3D LiDAR point cloud data. This eliminates the effect of dynamic objects on the 3D map model, providing higher-quality map merging results. The second novelty is a robust and efficient outlier removal algorithm for detected loop closures. This algorithm ensures a high recall rate and a low false alarm rate in position retrieval, significantly reducing outliers in repetitive environments during large-scale merging. We evaluate our framework using various datasets, including KITTI, HeLiPR, WildPlaces, and a self-collected colored point cloud dataset. The results demonstrate that our proposed framework can accurately merge maps captured by different types of LiDARs and data acquisition devices across diverse scenarios.","PeriodicalId":13241,"journal":{"name":"IEEE Robotics and Automation Letters","volume":"10 1","pages":"88-95"},"PeriodicalIF":4.6,"publicationDate":"2024-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142736261","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

Cloud-Native Fog Robotics: Model-Based Deployment and Evaluation of Real-Time Applications

IF 4.6 2区计算机科学

IEEE Robotics and Automation Letters Pub Date : 2024-11-21 DOI: 10.1109/LRA.2024.3504243

Long Wen;Yu Zhang;Markus Rickert;Jianjie Lin;Fengjunjie Pan;Alois Knoll

{"title":"Cloud-Native Fog Robotics: Model-Based Deployment and Evaluation of Real-Time Applications","authors":"Long Wen;Yu Zhang;Markus Rickert;Jianjie Lin;Fengjunjie Pan;Alois Knoll","doi":"10.1109/LRA.2024.3504243","DOIUrl":"https://doi.org/10.1109/LRA.2024.3504243","url":null,"abstract":"As the field of robotics evolves, robots become increasingly multi-functional and complex. Currently, there is a need for solutions that enhance flexibility and computational power without compromising real-time performance. The emergence of fog computing and cloud-native approaches addresses these challenges. In this paper, we integrate a microservice-based architecture with cloud-native fog robotics to investigate its performance in managing complex robotic systems and handling real-time tasks. Additionally, we apply model-based systems engineering (MBSE) to achieve automatic configuration of the architecture and to manage resource allocation efficiently. To demonstrate the feasibility and evaluate the performance of this architecture, we conduct comprehensive evaluations using both bare-metal and cloud setups, focusing particularly on real-time and machine-learning-based tasks. The experimental results indicate that a microservice-based cloud-native fog architecture offers a more stable computational environment compared to a bare-metal one, achieving over 20% reduction in the standard deviation for complex algorithms across both CPU and GPU. It delivers improved startup times, along with a 17% (wireless) and 23% (wired) faster average message transport time. Nonetheless, it exhibits a 37% slower execution time for simple CPU tasks and 3% for simple GPU tasks, though this impact is negligible in cloud-native environments where such tasks are typically deployed on bare-metal systems.","PeriodicalId":13241,"journal":{"name":"IEEE Robotics and Automation Letters","volume":"10 1","pages":"398-405"},"PeriodicalIF":4.6,"publicationDate":"2024-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10759800","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142790234","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

QT-TDM: Planning With Transformer Dynamics Model and Autoregressive Q-Learning QT-TDM：利用变压器动力学模型和自回归 Q 学习进行规划

IF 4.6 2区计算机科学

IEEE Robotics and Automation Letters Pub Date : 2024-11-21 DOI: 10.1109/LRA.2024.3504341

Mostafa Kotb;Cornelius Weber;Muhammad Burhan Hafez;Stefan Wermter

{"title":"QT-TDM: Planning With Transformer Dynamics Model and Autoregressive Q-Learning","authors":"Mostafa Kotb;Cornelius Weber;Muhammad Burhan Hafez;Stefan Wermter","doi":"10.1109/LRA.2024.3504341","DOIUrl":"https://doi.org/10.1109/LRA.2024.3504341","url":null,"abstract":"Inspired by the success of the Transformer architecture in natural language processing and computer vision, we investigate the use of Transformers in Reinforcement Learning (RL), specifically in modeling the environment's dynamics using Transformer Dynamics Models (TDMs). We evaluate the capabilities of TDMs for continuous control in real-time planning scenarios with Model Predictive Control (MPC). While Transformers excel in long-horizon prediction, their tokenization mechanism and autoregressive nature lead to costly planning over long horizons, especially as the environment's dimensionality increases. To alleviate this issue, we use a TDM for short-term planning, and learn an autoregressive discrete Q-function using a separate Q-Transformer (QT) model to estimate a long-term return beyond the short-horizon planning. Our proposed method, QT-TDM, integrates the robust predictive capabilities of Transformers as dynamics models with the efficacy of a model-free Q-Transformer to mitigate the computational burden associated with real-time planning. Experiments in diverse state-based continuous control tasks show that QT-TDM is superior in performance and sample efficiency compared to existing Transformer-based RL models while achieving fast and computationally efficient inference.","PeriodicalId":13241,"journal":{"name":"IEEE Robotics and Automation Letters","volume":"10 1","pages":"112-119"},"PeriodicalIF":4.6,"publicationDate":"2024-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142736260","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

Probabilistically Correct Language-Based Multi-Robot Planning Using Conformal Prediction

IF 4.6 2区计算机科学

IEEE Robotics and Automation Letters Pub Date : 2024-11-21 DOI: 10.1109/LRA.2024.3504233

Jun Wang;Guocheng He;Yiannis Kantaros

{"title":"Probabilistically Correct Language-Based Multi-Robot Planning Using Conformal Prediction","authors":"Jun Wang;Guocheng He;Yiannis Kantaros","doi":"10.1109/LRA.2024.3504233","DOIUrl":"https://doi.org/10.1109/LRA.2024.3504233","url":null,"abstract":"This paper addresses task planning problems for language-instructed robot teams. Tasks are expressed in natural language (NL), requiring the robots to apply their skills at various locations and semantic objects. Several recent works have addressed similar planning problems by leveraging pre-trained Large Language Models (LLMs) to design effective multi-robot plans. However, these approaches lack performance guarantees. To address this challenge, we introduce a new distributed LLM-based planner, called S-ATLAS for Safe plAnning for Teams of Language-instructed AgentS, that can achieve user-defined mission success rates. This is accomplished by leveraging conformal prediction (CP), a distribution-free uncertainty quantification tool. CP allows the proposed multi-robot planner to reason about its inherent uncertainty, due to imperfections of LLMs, in a distributed fashion, enabling robots to make local decisions when they are sufficiently confident and seek help otherwise. We show, both theoretically and empirically, that the proposed planner can achieve user-specified task success rates, assuming successful plan execution, while minimizing the average number of help requests. We provide comparative experiments against related works showing that our method is significantly more computational efficient and achieves lower help rates.","PeriodicalId":13241,"journal":{"name":"IEEE Robotics and Automation Letters","volume":"10 1","pages":"160-167"},"PeriodicalIF":4.6,"publicationDate":"2024-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142753868","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

On the Consistency of Multi-Robot Cooperative Localization: A Transformation-Based Approach

IF 4.6 2区计算机科学

IEEE Robotics and Automation Letters Pub Date : 2024-11-21 DOI: 10.1109/LRA.2024.3504320

Ning Hao;Fenghua He;Chungeng Tian;Yi Hou

引用次数: 0

Sensor-Free Strategy for Estimating Guidewire/Catheter Shape and Contact Force in Endovascular Interventions

IF 4.6 2区计算机科学

IEEE Robotics and Automation Letters Pub Date : 2024-11-21 DOI: 10.1109/LRA.2024.3504236

Naner Li;Yiwei Wang;Huan Zhao;Han Ding

{"title":"Sensor-Free Strategy for Estimating Guidewire/Catheter Shape and Contact Force in Endovascular Interventions","authors":"Naner Li;Yiwei Wang;Huan Zhao;Han Ding","doi":"10.1109/LRA.2024.3504236","DOIUrl":"https://doi.org/10.1109/LRA.2024.3504236","url":null,"abstract":"Accurate assessment of guidewire shape and contact forces is critical for autonomous robotic endovascular procedures. However, existing sensor-based approaches often require modifications to standard guidewires or the use of custom-made alternatives, which can hinder integration into conventional surgical workflows and increase costs. Moreover, the sensor-based method can only obtain partial force information. This letter aimed to develop a novel sensor-free two-step computational method for estimating overall guidewire shape and forces using only routinely obtainable information. The vascular space is discretized into multiple mesh points along the centerline to form a graph. Based on an energy equation, the lowest energy path between the start point (the insertion position) and the endpoint (the guidewire tip position) is searched as the initial shape of the guidewire. This initial shape, along with the known insertion length, is then input into a finite element model to compute the final guidewire configuration and contact forces. The method was validated through 3 rounds of testing in 3 phantom models at 4 different insertion lengths. In 11 successful experimental scenarios, the estimated guidewire shapes closely matched the actual shapes, with an average root mean square error of 0.50 \u0000<inline-formula><tex-math>$pm$</tex-math></inline-formula>\u0000 0.12 mm. The contact force estimation achieved an average accuracy of 91.9 \u0000<inline-formula><tex-math>$pm$</tex-math></inline-formula>\u0000 2.9%, with an average angular deviation of 1.94 \u0000<inline-formula><tex-math>$pm$</tex-math></inline-formula>\u0000 1.03\u0000<inline-formula><tex-math>$^circ$</tex-math></inline-formula>\u0000 from measured values.","PeriodicalId":13241,"journal":{"name":"IEEE Robotics and Automation Letters","volume":"10 1","pages":"264-271"},"PeriodicalIF":4.6,"publicationDate":"2024-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142761548","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