The International Journal of Robotics Research最新文献_第2页

Reduced order modeling of hybrid soft-rigid robots using global, local, and state-dependent strain parameterization 利用全局、局部和随状态变化的应变参数化，建立软硬混合机器人的低阶模型

The International Journal of Robotics Research Pub Date : 2024-07-26 DOI: 10.1177/02783649241262333

Anup Teejo Mathew, Daniel Feliu-Talegon, Abdulaziz Y Alkayas, Frederic Boyer, Federico Renda

{"title":"Reduced order modeling of hybrid soft-rigid robots using global, local, and state-dependent strain parameterization","authors":"Anup Teejo Mathew, Daniel Feliu-Talegon, Abdulaziz Y Alkayas, Frederic Boyer, Federico Renda","doi":"10.1177/02783649241262333","DOIUrl":"https://doi.org/10.1177/02783649241262333","url":null,"abstract":"The need for fast and accurate analysis of soft robots calls for reduced order models (ROM). Among these, the relative reduction of strain-based ROMs follows the discretization of the strain to capture the configurations of the robot. Based on the geometrically exact variable strain parametrization of the Cosserat rod, we developed a ROM that necessitates a minimal number of degrees of freedom to represent the state of the robot: the Geometric Variable Strain (GVS) model. This model allows the static and dynamic analysis of open-, branched-, or closed-chain soft-rigid hybrid robots, all under the same mathematical framework. This paper presents for the first time the complete GVS modeling framework for a generic hybrid soft-rigid robot. Based on the Magnus expansion of the variable strain field, we developed an efficient recursive algorithm for computing the Lagrangian dynamics of the system. To discretize the soft link, we introduce state- and time-dependent basis, which is the most general form of strain basis. We classify the independent bases into global and local bases. We propose “FEM-like” local strain bases with nodal values as their generalized coordinates. Finally, using four real-world applications, we illustrate the potential of the model developed. We think that the soft robotics community will use the comprehensive framework presented in this work to analyze a wide range of specific robotic systems.","PeriodicalId":501362,"journal":{"name":"The International Journal of Robotics Research","volume":"14 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141778237","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A geometric characterization of observability in inertial parameter identification 惯性参数识别中可观测性的几何特征

The International Journal of Robotics Research Pub Date : 2024-07-25 DOI: 10.1177/02783649241258215

Patrick M. Wensing, Günter Niemeyer, Jean-Jacques E. Slotine

引用次数: 0

Fast and robust learned single-view depth-aided monocular visual-inertial initialization 快速稳健的学习型单视角深度辅助单目视觉惯性初始化

The International Journal of Robotics Research Pub Date : 2024-07-25 DOI: 10.1177/02783649241262452

Nathaniel Merrill, Patrick Geneva, Saimouli Katragadda, Chuchu Chen, Guoquan Huang

{"title":"Fast and robust learned single-view depth-aided monocular visual-inertial initialization","authors":"Nathaniel Merrill, Patrick Geneva, Saimouli Katragadda, Chuchu Chen, Guoquan Huang","doi":"10.1177/02783649241262452","DOIUrl":"https://doi.org/10.1177/02783649241262452","url":null,"abstract":"In monocular visual-inertial navigation, it is desirable to initialize the system as quickly and robustly as possible. A state-of-the-art initialization method typically constructs a linear system to find a closed-form solution using the image features and inertial measurements and then refines the states with a nonlinear optimization. These methods generally require a few seconds of data, which however can be expedited (less than a second) by adding constraints from a robust but only up-to-scale monocular depth network in the nonlinear optimization. To further accelerate this process, in this work, we leverage the scale-less depth measurements instead in the linear initialization step that is performed prior to the nonlinear one, which only requires a single depth image for the first frame. Importantly, we show that the typical estimation of all feature states independently in the closed-form solution can be modeled as estimating only the scale and bias parameters of the learned depth map. As such, our formulation enables building a smaller minimal problem than the state of the art, which can be seamlessly integrated into RANSAC for robust estimation. Experiments show that our method has state-of-the-art initialization performance in simulation as well as on popular real-world datasets (TUM-VI, and EuRoC MAV). For the TUM-VI dataset in simulation as well as real-world, we demonstrate the superior initialization performance with only a 0.3 s window of data, which is the smallest ever reported, and validate that our method can initialize more often, robustly, and accurately in different challenging scenarios.","PeriodicalId":501362,"journal":{"name":"The International Journal of Robotics Research","volume":"25 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141778226","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Hybrid trajectory planning of two permanent magnets for medical robotic applications 医疗机器人应用中两个永磁体的混合轨迹规划

The International Journal of Robotics Research Pub Date : 2024-07-24 DOI: 10.1177/02783649241264844

Michael Brockdorff, Tomas da Veiga, Joshua Davy, Peter Lloyd, James H Chandler, Giovanni Pittiglio, Ryan K Mathew, Pietro Valdastri

{"title":"Hybrid trajectory planning of two permanent magnets for medical robotic applications","authors":"Michael Brockdorff, Tomas da Veiga, Joshua Davy, Peter Lloyd, James H Chandler, Giovanni Pittiglio, Ryan K Mathew, Pietro Valdastri","doi":"10.1177/02783649241264844","DOIUrl":"https://doi.org/10.1177/02783649241264844","url":null,"abstract":"Independent robotic manipulation of two large permanent magnets, in the form of the dual External Permanent Magnet (dEPM) system has demonstrated the possibility for enhanced magnetic control by allowing for actuation up to eight magnetic degrees of freedom (DOFs) at clinically relevant scales. This precise off-board control has facilitated the use of magnetic agents as medical devices, including catheter-like soft continuum robots (SCRs). The use of multiple robotically actuated permanent magnets poses the risk of collision between the robotic arms, the environment, and the patient. Furthermore, unconstrained transitions between actuation inputs can lead to undesired spikes in magnetic fields potentially resulting in unsafe manipulator deformation. This paper presents a hybrid approach to trajectory planning for the dEPM platform. This is performed by splitting the planning problem in two: first finding a collision-free physical path for the two robotically actuated permanent magnets before combining this with a path in magnetic space, which permits for a smooth change in magnetic fields and gradients. This algorithm was characterized by actuating each of the eight magnetic DOFs sequentially, eliminating any potential collisions and reducing the maximum undesired actuation value by 203.7 mT for fields and by 418.7 mT/m for gradients. The effect of this planned magnetic field actuation on a SCR was then examined through two case studies. First, a tip-driven SCR was moved to set points within a confined area. Actuation using the proposed planner reduced movement outside the restricted area by an average of 41.3%. Lastly, the use of the proposed magnetic planner was shown to be essential in navigating a multi-segment magnetic SCR to the site of an aneurysm within a silicone brain phantom.","PeriodicalId":501362,"journal":{"name":"The International Journal of Robotics Research","volume":"35 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141778239","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Unified force-impedance control 力阻抗统一控制

The International Journal of Robotics Research Pub Date : 2024-07-24 DOI: 10.1177/02783649241249194

Sami Haddadin, Erfan Shahriari

{"title":"Unified force-impedance control","authors":"Sami Haddadin, Erfan Shahriari","doi":"10.1177/02783649241249194","DOIUrl":"https://doi.org/10.1177/02783649241249194","url":null,"abstract":"Unified force-impedance control (UFIC) aims at integrating the advantages of impedance control and force control. Compliance and exact force regulation are equally important abilities in modern robot manipulation. The developed passivity-based framework builds on the energy tank concept and is suitable for serial rigid and flexible-joint robots. Furthermore, it is able to deal either with direct force measurements or model-based contact force estimation. Thus, in this theoretical framework, the most relevant practical systems are covered and shown to be stable for arbitrary passive environments. Particular focus is also laid on a robust impedance-based contact/non-contact stabilization methodology that prevents abrupt, unwanted, and potentially dangerous movements of the manipulator in case of contact loss, a well-known problem of both impedance and force control. The validity of the approach is shown in simulation and through various experiments. Our work roots in Haddadin (2015); Schindlbeck and Haddadin (2015), where the basic UFIC regulation controller was proposed. In the present paper, we significantly advance this idea into a complete theoretical UFIC tracking framework, including rigorous stability analysis and extensive experimental evidence.","PeriodicalId":501362,"journal":{"name":"The International Journal of Robotics Research","volume":"20 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141778240","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Modeling multi-legged robot locomotion with slipping and its experimental validation 多足机器人打滑运动建模及其实验验证

The International Journal of Robotics Research Pub Date : 2024-07-23 DOI: 10.1177/02783649241263114

Ziyou Wu, Dan Zhao, Shai Revzen

引用次数: 0

MOB-Net: Limb-modularized uncertainty torque learning of humanoids for sensorless external torque estimation MOB-Net：用于无传感器外部扭矩估算的人形机器人肢体模块化不确定性扭矩学习

The International Journal of Robotics Research Pub Date : 2024-07-22 DOI: 10.1177/02783649241260428

Daegyu Lim, Myeong-Ju Kim, Junhyeok Cha, Jaeheung Park

{"title":"MOB-Net: Limb-modularized uncertainty torque learning of humanoids for sensorless external torque estimation","authors":"Daegyu Lim, Myeong-Ju Kim, Junhyeok Cha, Jaeheung Park","doi":"10.1177/02783649241260428","DOIUrl":"https://doi.org/10.1177/02783649241260428","url":null,"abstract":"Momentum observer (MOB) can estimate external joint torque without requiring additional sensors, such as force/torque or joint torque sensors. However, the estimation performance of MOB deteriorates due to the model uncertainty which encompasses the modeling errors and the joint friction. Moreover, the estimation error is significant when MOB is applied to high-dimensional floating-base humanoids, which prevents the estimated external joint torque from being used for force control or collision detection in the real humanoid robot. In this paper, the pure external joint torque estimation method named MOB-Net, is proposed for humanoids. MOB-Net learns the model uncertainty torque and calibrates the estimated signal of MOB, substantially reducing the estimation errors of MOB. The external joint torque can be estimated in the generalized coordinate including whole-body and virtual joints of the floating-base robot with only internal sensors (an IMU on the pelvis and encoders in the joints). Furthermore, MOB-Net shows more robust performance for the unseen data compared to the end-to-end learning method, and the robustness of MOB-Net is validated through extensive simulations, real robot experiments, and ablation studies. Finally, various collision handling scenarios are presented to show the versatility of MOB-Net: contact wrench feedback control for locomotion, collision detection, and collision reaction for safety.","PeriodicalId":501362,"journal":{"name":"The International Journal of Robotics Research","volume":"24 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141742145","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Machine learning for shipwreck segmentation from side scan sonar imagery: Dataset and benchmark 利用机器学习从侧扫声纳图像中分割沉船：数据集和基准

The International Journal of Robotics Research Pub Date : 2024-07-21 DOI: 10.1177/02783649241266853

Advaith V. Sethuraman, Anja Sheppard, Onur Bagoren, Christopher Pinnow, Jamey Anderson, Timothy C. Havens, Katherine A. Skinner

{"title":"Machine learning for shipwreck segmentation from side scan sonar imagery: Dataset and benchmark","authors":"Advaith V. Sethuraman, Anja Sheppard, Onur Bagoren, Christopher Pinnow, Jamey Anderson, Timothy C. Havens, Katherine A. Skinner","doi":"10.1177/02783649241266853","DOIUrl":"https://doi.org/10.1177/02783649241266853","url":null,"abstract":"Open-source benchmark datasets have been a critical component for advancing machine learning for robot perception in terrestrial applications. Benchmark datasets enable the widespread development of state-of-the-art machine learning methods, which require large datasets for training, validation, and thorough comparison to competing approaches. Underwater environments impose several operational challenges that hinder efforts to collect large benchmark datasets for marine robot perception. Furthermore, a low abundance of targets of interest relative to the size of the search space leads to increased time and cost required to collect useful datasets for a specific task. As a result, there is limited availability of labeled benchmark datasets for underwater applications. We present the AI4Shipwrecks dataset, which consists of 28 distinct shipwrecks totaling 286 high-resolution labeled side scan sonar images to advance the state-of-the-art in autonomous sonar image understanding. We leverage the unique abundance of targets in Thunder Bay National Marine Sanctuary in Lake Huron, MI, to collect and compile a sonar imagery benchmark dataset through surveys with an autonomous underwater vehicle (AUV). We consulted with expert marine archaeologists for the labeling of robotically gathered data. We then leverage this dataset to perform benchmark experiments for comparison of state-of-the-art supervised segmentation methods, and we present insights on opportunities and open challenges for the field. The dataset and benchmarking tools will be released as an open-source benchmark dataset to spur innovation in machine learning for Great Lakes and ocean exploration. The dataset and accompanying software are available at https://umfieldrobotics.github.io/ai4shipwrecks/ .","PeriodicalId":501362,"journal":{"name":"The International Journal of Robotics Research","volume":"12 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141742150","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

YUTO MMS: A comprehensive SLAM dataset for urban mobile mapping with tilted LiDAR and panoramic camera integration YUTO MMS：集成倾斜激光雷达和全景相机的城市移动制图综合 SLAM 数据集

The International Journal of Robotics Research Pub Date : 2024-07-19 DOI: 10.1177/02783649241261079

Yiujia Zhang, SeyedMostafa Ahmadi, Jungwon Kang, Zahra Arjmandi, Gunho Sohn

{"title":"YUTO MMS: A comprehensive SLAM dataset for urban mobile mapping with tilted LiDAR and panoramic camera integration","authors":"Yiujia Zhang, SeyedMostafa Ahmadi, Jungwon Kang, Zahra Arjmandi, Gunho Sohn","doi":"10.1177/02783649241261079","DOIUrl":"https://doi.org/10.1177/02783649241261079","url":null,"abstract":"The York University Teledyne Optech (YUTO) Mobile Mapping System (MMS) Dataset, encompassing four sequences totaling 20.1 km, was thoroughly assembled through two data collection expeditions on August 12, 2020, and June 21, 2019. Acquisitions were performed using a uniquely equipped vehicle, fortified with a panoramic camera, a tilted LiDAR, a Global Positioning System (GPS), and an Inertial Measurement Unit (IMU), journeying through two strategic locations: the York University Keele Campus in Toronto and the Teledyne Optech headquarters in City of Vaughan, Canada. This paper not only delineates the comprehensive overview of the YUTO MMS dataset, delving into aspects such as the collection procedure, sensor configuration, synchronization, data structure and format but also presents a robust benchmark of prevailing Simultaneous Localization and Mapping (SLAM) systems. By subjecting them to analysis utilizing the introduced dataset, this research lays a foundational baseline for ensuing studies, thereby contributing to advancements and enhancements in the SLAM-integrated mobile mapping system. The dataset can be downloaded from: https://ausmlab.github.io/yutomms/ .","PeriodicalId":501362,"journal":{"name":"The International Journal of Robotics Research","volume":"38 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141742146","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Group-k consistent measurement set maximization via maximum clique over k-uniform hypergraphs for robust multi-robot map merging 通过 k 个均匀超图上的最大聚类实现 k 组一致的测量集最大化，从而实现稳健的多机器人地图合并

The International Journal of Robotics Research Pub Date : 2024-07-02 DOI: 10.1177/02783649241256970

Brendon Forsgren, Michael Kaess, Ram Vasudevan, Timothy W. McLain, Joshua G. Mangelson

{"title":"Group-k consistent measurement set maximization via maximum clique over k-uniform hypergraphs for robust multi-robot map merging","authors":"Brendon Forsgren, Michael Kaess, Ram Vasudevan, Timothy W. McLain, Joshua G. Mangelson","doi":"10.1177/02783649241256970","DOIUrl":"https://doi.org/10.1177/02783649241256970","url":null,"abstract":"This paper unifies the theory of consistent-set maximization for robust outlier detection in a simultaneous localization and mapping framework. We first describe the notion of pairwise consistency before discussing how a consistency graph can be formed by evaluating pairs of measurements for consistency. Finding the largest set of consistent measurements is transformed into an instance of the maximum clique problem and can be solved relatively quickly using existing maximum-clique solvers. We then generalize our algorithm to check consistency on a group- k basis by using a generalized notion of consistency and using generalized graphs. We also present modified maximum clique algorithms that function over generalized graphs to find the set of measurements that is internally group- k consistent. We address the exponential nature of group- k consistency and present methods that can substantially decrease the number of necessary checks performed when evaluating consistency. We extend our prior work to perform data association, and to multi-agent systems in both simulation and hardware, and provide a comparison with other state-of-the-art methods.","PeriodicalId":501362,"journal":{"name":"The International Journal of Robotics Research","volume":"147 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141510968","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0