IEEE Robotics and Automation Letters最新文献_第9页

Robust Neuromorphic Method for Tactile Recognition of Material Surfaces

IF 4.6 2区计算机科学

IEEE Robotics and Automation Letters Pub Date : 2025-02-26 DOI: 10.1109/LRA.2025.3546086

Dongyan Nie;Yan Zhang;Rui Song;Hong Fei;Xiaoying Sun

{"title":"Robust Neuromorphic Method for Tactile Recognition of Material Surfaces","authors":"Dongyan Nie;Yan Zhang;Rui Song;Hong Fei;Xiaoying Sun","doi":"10.1109/LRA.2025.3546086","DOIUrl":"https://doi.org/10.1109/LRA.2025.3546086","url":null,"abstract":"Tactile recognition enables humanoid robots to interact naturally and intelligently. Neuromorphic models, known for their robustness, efficiency, and low energy consumption, offer significant potential. Existing approaches primarily focus on normal force, neglecting other signals. Moreover, the imprecise anti-noise characteristics of tactile-oriented neuromorphic models hinder their optimal performance. To address this, we propose a neuromorphic approach that fuses tactile signals for material recognition, based on mechanoreceptor physiological responses and finger-surface interaction patterns. The method incorporates four models, each handling normal force, tangential force, velocity, and acceleration. Robustness is systematically evaluated at three levels: (1) analyzing the mean difference in spike firing rates for each model; (2) comparing noise resistance through the changing rate of membership degree; and (3) assessing the impact of signal-to-noise ratio on recognition accuracy. The results show that the method's resilience to blue, white, and pink noise decreases in this order. Compared to feature extraction methods, the neuromorphic approach demonstrates superior robustness. This research provides valuable insights for guiding multimodal tactile fusion recognition.","PeriodicalId":13241,"journal":{"name":"IEEE Robotics and Automation Letters","volume":"10 4","pages":"3924-3931"},"PeriodicalIF":4.6,"publicationDate":"2025-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143621726","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

Improving the Energy Efficiency by Using Quasi-Passive-Dynamics-Based Elastic Actuator

IF 4.6 2区计算机科学

IEEE Robotics and Automation Letters Pub Date : 2025-02-26 DOI: 10.1109/LRA.2025.3546098

Ruigang Chen;Tongchen Lin;Yizhar Or;Mingyi Liu

引用次数: 0

Robots Have Been Seen and Not Heard: Effects of Consequential Sounds on Human-Perception of Robots

IF 4.6 2区计算机科学

IEEE Robotics and Automation Letters Pub Date : 2025-02-26 DOI: 10.1109/LRA.2025.3546097

Aimee Allen;Tom Drummond;Dana Kulić

引用次数: 0

Fast Autolearning for Multimodal Walking in Humanoid Robots With Variability of Experience

IF 4.6 2区计算机科学

IEEE Robotics and Automation Letters Pub Date : 2025-02-26 DOI: 10.1109/LRA.2025.3546168

Nícolas F. Figueroa;Julio C. Tafur;Abderrahmane Kheddar

{"title":"Fast Autolearning for Multimodal Walking in Humanoid Robots With Variability of Experience","authors":"Nícolas F. Figueroa;Julio C. Tafur;Abderrahmane Kheddar","doi":"10.1109/LRA.2025.3546168","DOIUrl":"https://doi.org/10.1109/LRA.2025.3546168","url":null,"abstract":"Recent advancements in reinforcement learning (RL) and humanoid robotics are rapidly addressing the challenge of adapting to complex, dynamic environments in real time. This letter introduces a novel approach that integrates two key concepts: experience variability (a criterion for detecting changes in loco-manipulation) and experience accumulation (an efficient method for storing acquired experiences based on a selection criterion). These elements are incorporated into the development of RL agents and humanoid robots, with an emphasis on stability. This focus enhances adaptability and efficiency in unpredictable environments. Our approach enables more sophisticated modeling of such environments, significantly improving the system's ability to adapt to real-world complexities. By combining this method with advanced RL techniques, such as Proximal Policy Optimization (PPO) and Model-Agnostic Meta-Learning (MAML), and incorporating self-learning driven by stability, we improve the system's generalization capabilities. This facilitates rapid learning from novel and previously unseen scenarios. We validate our algorithm through both simulations and real-world experiments on the HRP-4 humanoid robot, utilizing an intrinsically stable model predictive controller.","PeriodicalId":13241,"journal":{"name":"IEEE Robotics and Automation Letters","volume":"10 4","pages":"3747-3754"},"PeriodicalIF":4.6,"publicationDate":"2025-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143601955","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

Optimal Scheduling of Timed Petri Nets With Resource Marking and Ready Times: Application to Robotic Flow Shops

IF 4.6 2区计算机科学

IEEE Robotics and Automation Letters Pub Date : 2025-02-26 DOI: 10.1109/LRA.2025.3546072

Jun-Ho Lee;Hyun-Jung Kim

{"title":"Optimal Scheduling of Timed Petri Nets With Resource Marking and Ready Times: Application to Robotic Flow Shops","authors":"Jun-Ho Lee;Hyun-Jung Kim","doi":"10.1109/LRA.2025.3546072","DOIUrl":"https://doi.org/10.1109/LRA.2025.3546072","url":null,"abstract":"Many scheduling problems, especially for automated manufacturing systems, have been addressed with a timed Petri net (TPN) by developing optimal or heuristic algorithms based on it. However, most of them have focused on cyclic scheduling, in which a firing sequence of transitions in a TPN is repeated, to minimize the cycle time. A few studies have considered a noncyclic scheduling problem but focused on developing a heuristic search method. In this study, a noncyclic scheduling problem for automated manufacturing systems is considered with a TPN to obtain an optimal solution with the makespan measure. Specifically, a scheduling problem of a dual-gripper robotic flow shop with a given job sequence is considered to determine an optimal robot task sequence. We first define resource marking and resource ready times for the dual-gripper robotic flow shop based on a TPN and develop dominance properties based on them. Then, an optimal algorithm that eliminates dominated nodes in a reachability tree by using those properties is proposed. The experimental results show that the proposed algorithm significantly outperforms the existing studies.","PeriodicalId":13241,"journal":{"name":"IEEE Robotics and Automation Letters","volume":"10 4","pages":"3684-3691"},"PeriodicalIF":4.6,"publicationDate":"2025-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143601963","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 Hybrid Motion Optimization Framework for the Humanoid Upper-Body Robot: Safe and Dexterous Object Carrying

IF 4.6 2区计算机科学

IEEE Robotics and Automation Letters Pub Date : 2025-02-26 DOI: 10.1109/LRA.2025.3546091

Zhaoyang Chen;Kang Min;Xinyang Fan;Fenglei Ni;Hong Liu

{"title":"A Hybrid Motion Optimization Framework for the Humanoid Upper-Body Robot: Safe and Dexterous Object Carrying","authors":"Zhaoyang Chen;Kang Min;Xinyang Fan;Fenglei Ni;Hong Liu","doi":"10.1109/LRA.2025.3546091","DOIUrl":"https://doi.org/10.1109/LRA.2025.3546091","url":null,"abstract":"In this letter, a novel hybrid motion optimization framework is proposed for a humanoid upper-body robot with two 7-DOF arms and a 2-DOF waist, to flexibly and safely carry objects in constrained and dynamic environments. The framework consists of <bold>trilayer interconnected optimization, which is dedicated to planning the optimal carrying configuration, waist-arm motion trajectory, and dual-arm nullspace trajectory, respectively. The top layer finds the most dexterous waist-arm carrying configuration that satisfies environmental constraints, which is achieved by the effective integration of the multi-objective evolutionary algorithm (EA), the proposed optimal manipulation index, and the parameterization method. The middle layer applies a non-linear optimization method to plan collision-free trajectory that connects the initial and optimal carrying configuration. The bottom layer is achieved by equipping the top layer with elite reproduction operator strategy and adaptive evolution space strategy, generating dual-arm nullspace trajectory in real-time for dynamic obstacle avoidance. The various carrying experiments demonstrate the effectiveness of the proposed framework.","PeriodicalId":13241,"journal":{"name":"IEEE Robotics and Automation Letters","volume":"10 4","pages":"3892-3899"},"PeriodicalIF":4.6,"publicationDate":"2025-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143621912","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

Functional Eigen-Grasping Using Approach Heatmaps

IF 4.6 2区计算机科学

IEEE Robotics and Automation Letters Pub Date : 2025-02-26 DOI: 10.1109/LRA.2025.3546089

Malek Aburub;Kazuki Higashi;Weiwei Wan;Kensuke Harada

{"title":"Functional Eigen-Grasping Using Approach Heatmaps","authors":"Malek Aburub;Kazuki Higashi;Weiwei Wan;Kensuke Harada","doi":"10.1109/LRA.2025.3546089","DOIUrl":"https://doi.org/10.1109/LRA.2025.3546089","url":null,"abstract":"This work presents a framework for a robot with a multi-fingered hand to freely utilize daily tools, including functional parts like buttons and triggers. An approach heatmap is generated by selecting a functional finger, indicating optimal palm positions on the object's surface that enable the functional finger to contact the tool's functional part. Once the palm position is identified through the heatmap, achieving the functional grasp becomes a straightforward process where the fingers stably grasp the object with low-dimensional inputs using the eigengrasp. As our approach does not need human demonstrations, it can easily adapt to various sizes and designs, extending its applicability to different objects. In our approach, we use directional manipulability to obtain the approach heatmap. In addition, we add two kinds of energy functions, i.e., palm energy and functional energy functions, to realize the eigengrasp. Using this method, each robotic gripper can autonomously identify its optimal workspace for functional grasping, extending its applicability to non-anthropomorphic robotic hands. We show that several daily tools like spray, drill, and remotes can be efficiently used by not only an anthropomorphic Shadow hand but also a non-anthropomorphic Barrett hand.","PeriodicalId":13241,"journal":{"name":"IEEE Robotics and Automation Letters","volume":"10 4","pages":"3771-3778"},"PeriodicalIF":4.6,"publicationDate":"2025-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143601954","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

CurviTrack: Curvilinear Trajectory Tracking for High-Speed Chase of a USV

IF 4.6 2区计算机科学

IEEE Robotics and Automation Letters Pub Date : 2025-02-26 DOI: 10.1109/LRA.2025.3546079

Parakh M. Gupta;Ondřej Procházka;Tiago Nascimento;Martin Saska

引用次数: 0

Rampa: Robotic Augmented Reality for Machine Programming by DemonstrAtion

IF 4.6 2区计算机科学

IEEE Robotics and Automation Letters Pub Date : 2025-02-26 DOI: 10.1109/LRA.2025.3546109

Fatih Dogangun;Serdar Bahar;Yigit Yildirim;Bora Toprak Temir;Emre Ugur;Mustafa Doga Dogan

{"title":"Rampa: Robotic Augmented Reality for Machine Programming by DemonstrAtion","authors":"Fatih Dogangun;Serdar Bahar;Yigit Yildirim;Bora Toprak Temir;Emre Ugur;Mustafa Doga Dogan","doi":"10.1109/LRA.2025.3546109","DOIUrl":"https://doi.org/10.1109/LRA.2025.3546109","url":null,"abstract":"This letter introduces Robotic Augmented Reality for Machine Programming by Demonstration (<sc>Rampa), the first ML-integrated, XR-driven end-to-end robotic system, allowing training and deployment of ML models such as ProMPs on the fly, and utilizing the capabilities of state-of-the-art and commercially available AR headsets, e.g., <italic>Meta Quest 3, to facilitate the application of Programming by Demonstration (PbD) approaches on industrial robotic arms, e.g., <italic>Universal Robots UR10. Our approach enables <italic>in-situ data recording, visualization, and fine-tuning of skill demonstrations directly within the user's physical environment. <sc>Rampa addresses critical challenges of PbD, such as safety concerns, programming barriers, and the inefficiency of collecting demonstrations on the actual hardware. The performance of our system is evaluated against the traditional method of kinesthetic control in teaching three different robotic manipulation tasks and analyzed with quantitative metrics, measuring task performance and completion time, trajectory smoothness, system usability, user experience, and task load using standardized surveys. Our findings indicate a substantial advancement in how robotic tasks are taught and refined, promising improvements in operational safety, efficiency, and user engagement in robotic programming.","PeriodicalId":13241,"journal":{"name":"IEEE Robotics and Automation Letters","volume":"10 4","pages":"3795-3802"},"PeriodicalIF":4.6,"publicationDate":"2025-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143601941","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

SoftTex: Soft Robotic Arm With Learning-Based Textile Proprioception

IF 4.6 2区计算机科学

IEEE Robotics and Automation Letters Pub Date : 2025-02-26 DOI: 10.1109/LRA.2025.3546070

Niccolò Pagliarani;Carlo Alessi;Luca Arleo;Giulia Campinoti;Martina Maselli;Egidio Falotico;Matteo Cianchetti

{"title":"SoftTex: Soft Robotic Arm With Learning-Based Textile Proprioception","authors":"Niccolò Pagliarani;Carlo Alessi;Luca Arleo;Giulia Campinoti;Martina Maselli;Egidio Falotico;Matteo Cianchetti","doi":"10.1109/LRA.2025.3546070","DOIUrl":"https://doi.org/10.1109/LRA.2025.3546070","url":null,"abstract":"Soft robots are promising in biomedical applications thanks to their inherent structural compliance and distributed large deformations. However, integrating a sensory system that maintains the robot's dexterity while offering accurate state estimation remains an open challenge for their widespread adoption. This letter presents SoftTex, a small-scale soft robotic arm built with textile fabrics. SoftTex redesigns the STIFF-FLOP soft manipulator to favor affordable, rapid, and repeatable fabrication methods, facilitating the integration of a proprioceptive system based on piezoresistive textile strips preserving the soft arm compliance. First, we characterized the bending and stretching capabilities of the soft robotic arm and its workspace. The force tests demonstrated effectiveness for potential biomedical applications, revealing pulling forces ranging from 3.4–7.4 N and pushing forces from 2–7.5 N. Finally, we leveraged actuation, motion, and proprioceptive data collected with an open-loop controller to develop a position state estimator using a parallel recurrent neural network trained with supervised curriculum learning. The proprioceptive network achieves an average prediction error of <inline-formula><tex-math>${text{2.0}} pm {text{1.8}}$</tex-math></inline-formula> mm (<inline-formula><tex-math>$3.4 pm 2.9%L$</tex-math></inline-formula>, where <inline-formula><tex-math>$L$</tex-math></inline-formula> is module length). The findings are promising for closed-loop control, addressing the demand for low-cost, sensor-equipped soft robotic arms in the medical field and enhancing their potential for confined space exploration.","PeriodicalId":13241,"journal":{"name":"IEEE Robotics and Automation Letters","volume":"10 4","pages":"3779-3786"},"PeriodicalIF":4.6,"publicationDate":"2025-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143601912","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