IEEE Robotics and Automation Letters最新文献_第4页

A Human-in-The-Loop Approach to Robot Action Replanning Through LLM Common-Sense Reasoning 基于LLM常识推理的机器人动作重规划的人在环方法

IF 5.3 2区计算机科学

IEEE Robotics and Automation Letters Pub Date : 2025-09-01 DOI: 10.1109/LRA.2025.3604702

Elena Merlo;Marta Lagomarsino;Arash Ajoudani

引用次数: 0

BOW: Bayesian Optimization Over Windows for Motion Planning in Complex Environments BOW：基于窗口的贝叶斯优化在复杂环境中的运动规划

IF 5.3 2区计算机科学

IEEE Robotics and Automation Letters Pub Date : 2025-09-01 DOI: 10.1109/LRA.2025.3604738

Sourav Raxit;Abdullah Al Redwan Newaz;Paulo Padrao;Jose Fuentes;Leonardo Bobadilla

{"title":"BOW: Bayesian Optimization Over Windows for Motion Planning in Complex Environments","authors":"Sourav Raxit;Abdullah Al Redwan Newaz;Paulo Padrao;Jose Fuentes;Leonardo Bobadilla","doi":"10.1109/LRA.2025.3604738","DOIUrl":"https://doi.org/10.1109/LRA.2025.3604738","url":null,"abstract":"This letter introduces the BOW Planner, a scalable motion planning algorithm designed to navigate robots through complex environments using constrained Bayesian optimization (CBO). Unlike traditional methods, which often struggle with kinodynamic constraints such as velocity and acceleration limits, the BOW Planner excels by concentrating on a planning window of reachable velocities and employing CBO to sample control inputs efficiently. This approach enables the planner to manage high-dimensional objective functions and stringent safety constraints with minimal sampling, ensuring rapid and secure trajectory generation. Theoretical analysis confirms the algorithm's asymptotic convergence to near-optimal solutions, while extensive evaluations in cluttered and constrained settings reveal substantial improvements in computation times, trajectory lengths, and solution times compared to existing techniques. Successfully deployed across various real-world robotic systems, the BOW Planner demonstrates its practical significance through exceptional sample efficiency, safety-aware optimization, and rapid planning capabilities, making it a valuable tool for advancing robotic applications.","PeriodicalId":13241,"journal":{"name":"IEEE Robotics and Automation Letters","volume":"10 10","pages":"10714-10721"},"PeriodicalIF":5.3,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145051017","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 Coordinated and Resilient Formation Strategy Based on Hierarchical Reorganization 基于层次重组的协调弹性编队策略

IF 5.3 2区计算机科学

IEEE Robotics and Automation Letters Pub Date : 2025-09-01 DOI: 10.1109/LRA.2025.3604698

Yuzhu Li;Wei Dong

{"title":"A Coordinated and Resilient Formation Strategy Based on Hierarchical Reorganization","authors":"Yuzhu Li;Wei Dong","doi":"10.1109/LRA.2025.3604698","DOIUrl":"https://doi.org/10.1109/LRA.2025.3604698","url":null,"abstract":"Multi-leader formations offer superior flexibility and adaptability compared to single-leader configurations. However, the failure of even a single leader can pose significant risks to the overall success of hierarchical formations. Although existing strategies to address leader failures often rely on dynamic re-election mechanisms, these approaches are primarily tailored to single-leader configurations. To overcome these limitations, this paper presents a resilient formation strategy based on hierarchical reorganization. The central concept is to endow the formation with fail-tolerance through seamless leadership transitions while preserving overall agility. Specifically, we propose a comprehensive fail-tolerant leadership evaluation algorithm capable of selecting the most agile leadership configuration while maintaining formation safety. Recognizing that distributed evaluations may yield inconsistent leader selections, we integrate a Raft-based configuration consensus mechanism to achieve distributed agreement during hierarchical reorganization. Additionally, to guarantee the smooth execution of the reorganization process, a synchronous state updating strategy is adopted to mitigate communication delays, thereby facilitating seamless reconfiguration. We conducted extensive simulations and real-world experiments. Experiments results across multiple scenarios demonstrate that the proposed strategy swiftly identifies malfunctioning leaders, mitigates their adverse effects through hierarchical reorganization, and improves the mission success rate of a 7-UAV formation from 28.6% to 85.7%. Overall, our findings show that the proposed approach not only addresses individual agent failures but also significantly enhances the formation's stability and robustness.","PeriodicalId":13241,"journal":{"name":"IEEE Robotics and Automation Letters","volume":"10 10","pages":"10650-10657"},"PeriodicalIF":5.3,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145050815","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

Efficient Guidance Control of Large-Scale Drone Swarms Using Implicitly Informed Agents 基于隐式智能体的大规模无人机群制导控制

IF 5.3 2区计算机科学

IEEE Robotics and Automation Letters Pub Date : 2025-09-01 DOI: 10.1109/LRA.2025.3604701

Guangpeng Hu;Zhiwei Zhang;Zhaohui Song;Lifu Zhang;Sirun Xu;Hongjun Chu

{"title":"Efficient Guidance Control of Large-Scale Drone Swarms Using Implicitly Informed Agents","authors":"Guangpeng Hu;Zhiwei Zhang;Zhaohui Song;Lifu Zhang;Sirun Xu;Hongjun Chu","doi":"10.1109/LRA.2025.3604701","DOIUrl":"https://doi.org/10.1109/LRA.2025.3604701","url":null,"abstract":"Guidance control is crucial for the effective operation of distributed aerial swarm systems. Despite significant advancements, developing effective guidance control techniques for large-scale drone swarms remains a considerable challenge, especially when dealing with scenarios involving implicitly informed agents. Traditional methods often lead to swarm fragmentation in non-uniform guidance scenarios. Inspired by the intelligent swarming behavior of starlings, we propose a novel resilient guidance control model for drone swarms. This model employs a stochastic transition strategy for interaction modes based on a Markov decision process, establishing a swarm resilience mechanism that dynamically couples swarm cohesion with individual integration behaviors. This mechanism enables informed agents to guide individuals beyond their immediate topological interaction range effectively. Furthermore, the guidance control problem is formulated as a multi-objective optimization problem, which balances system flexibility and motion consistency through an adaptive optimization algorithm. Extensive simulations demonstrate that the model can guide a 1000-drone swarm to execute complex trajectories with a 99.95% success rate, even with only 5% informed agents. Real-world experiments using Crazyflie micro quadrotors further validate the model's practicality. This letter introduces a novel approach to large-scale drone swarm guidance and offers valuable insights for designing next-generation intelligent swarm systems.","PeriodicalId":13241,"journal":{"name":"IEEE Robotics and Automation Letters","volume":"10 10","pages":"10618-10625"},"PeriodicalIF":5.3,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145050851","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

Distributed NMPC for Cooperative Aerial Manipulation of Cable-Suspended Loads 悬索载荷协同空中操纵的分布式NMPC

IF 5.3 2区计算机科学

IEEE Robotics and Automation Letters Pub Date : 2025-09-01 DOI: 10.1109/LRA.2025.3604703

Nicola De Carli;Riccardo Belletti;Emanuele Buzzurro;Andrea Testa;Giuseppe Notarstefano;Marco Tognon

引用次数: 0

Maximizing Seaweed Growth on Autonomous Farms: A Dynamic Programming Approach for Underpowered Systems Operating in Uncertain Ocean Currents 自主农场海藻生长最大化：在不确定洋流中运行的动力不足系统的动态规划方法

IF 5.3 2区计算机科学

IEEE Robotics and Automation Letters Pub Date : 2025-09-01 DOI: 10.1109/LRA.2025.3604727

Matthias Killer;Marius Wiggert;Hanna Krasowski;Manan Doshi;Pierre F.J. Lermusiaux;Claire J. Tomlin

{"title":"Maximizing Seaweed Growth on Autonomous Farms: A Dynamic Programming Approach for Underpowered Systems Operating in Uncertain Ocean Currents","authors":"Matthias Killer;Marius Wiggert;Hanna Krasowski;Manan Doshi;Pierre F.J. Lermusiaux;Claire J. Tomlin","doi":"10.1109/LRA.2025.3604727","DOIUrl":"https://doi.org/10.1109/LRA.2025.3604727","url":null,"abstract":"Seaweed biomass presents a substantial opportunity for climate mitigation, yet to realize its potential, farming must be expanded to the vast open oceans. However, in the open ocean neither anchored farming nor floating farms with powerful engines are economically viable. Thus, a potential solution are farms that operate by <italic>going with the flow</i>, utilizing minimal propulsion to strategically leverage beneficial ocean currents. In this work, we focus on low-power autonomous seaweed farms and design controllers that maximize seaweed growth by taking advantage of ocean currents. We first introduce a Dynamic Programming (DP) formulation to solve for the growth-optimal value function when the true currents are known. However, in reality only short-term imperfect forecasts with increasing uncertainty are available. Hence, we present three additional extensions. Firstly, we use frequent replanning to mitigate forecast errors. Second, to optimize for long-term growth, we extend the value function beyond the forecast horizon by estimating the expected future growth based on seasonal average currents. Lastly, we introduce a discounted finite-time DP formulation to account for the increasing uncertainty in future ocean current estimates. We empirically evaluate our approach with 30-day simulations of farms in realistic ocean conditions. Our method achieves 95.8% of the best possible growth using only 5-day forecasts. This demonstrates that low-power propulsion is a promising method to operate autonomous seaweed farms in real-world conditions.","PeriodicalId":13241,"journal":{"name":"IEEE Robotics and Automation Letters","volume":"10 10","pages":"10745-10752"},"PeriodicalIF":5.3,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145050802","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

Sensorless Force Imbalance Prediction Based on Visual Information for Robotic Ultrasound Scanning 基于视觉信息的机器人超声扫描无传感器力不平衡预测

IF 5.3 2区计算机科学

IEEE Robotics and Automation Letters Pub Date : 2025-09-01 DOI: 10.1109/LRA.2025.3604730

Qian Liu;Eunbin Choi;Anika Tabassum Sejuty;Suhyun Park

{"title":"Sensorless Force Imbalance Prediction Based on Visual Information for Robotic Ultrasound Scanning","authors":"Qian Liu;Eunbin Choi;Anika Tabassum Sejuty;Suhyun Park","doi":"10.1109/LRA.2025.3604730","DOIUrl":"https://doi.org/10.1109/LRA.2025.3604730","url":null,"abstract":"During robotic ultrasound examinations, maintaining pressure and angle control over the ultrasound probe is crucial for obtaining consistent images for an accurate diagnosis. Although force and torque sensors are commonly used for contact force monitoring, their accuracy can be influenced by sensor placement and system complexity. To address these issues, we propose a sensorless approach to estimate the contact force difference between the two sides of an ultrasound probe. Our proposed method utilizes a deep learning-based approach, specifically, a convolutional neural network–long short-term memory (CNN–LSTM) approach, that leverages sequential ultrasound images to estimate force differentials. Experiments were conducted using three tissue-mimicking phantoms and an in vivo human arm to train and evaluate the proposed approach. By varying the applied force difference on the phantoms and human arm, we achieved root mean squared error values of 0.501 and 0.553 N, respectively, in the contact force difference prediction. For performance assessment, we compared our proposed approach with a confidence map and various CNN–LSTM-based methods and demonstrated that our approach outperforms other approaches in terms of accuracy. The results indicate that our proposed method is effective for probe imbalance prediction without relying on physical sensors at inference time and can be deployed to control probes during robotic ultrasound examinations. Therefore, our sensorless approach offers a promising solution for more consistent and reliable robotic ultrasound scanning.","PeriodicalId":13241,"journal":{"name":"IEEE Robotics and Automation Letters","volume":"10 10","pages":"10594-10601"},"PeriodicalIF":5.3,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145050992","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

Miniature Multihole Airflow Sensor for Lightweight Aircraft Over Wide Speed and Angular Range 轻型飞机大速度和大角度范围微型多孔气流传感器

IF 5.3 2区计算机科学

IEEE Robotics and Automation Letters Pub Date : 2025-09-01 DOI: 10.1109/LRA.2025.3604704

Lukas Stuber;Simon Luis Jeger;Raphael Zufferey;Dario Floreano

{"title":"Miniature Multihole Airflow Sensor for Lightweight Aircraft Over Wide Speed and Angular Range","authors":"Lukas Stuber;Simon Luis Jeger;Raphael Zufferey;Dario Floreano","doi":"10.1109/LRA.2025.3604704","DOIUrl":"https://doi.org/10.1109/LRA.2025.3604704","url":null,"abstract":"An aircraft's airspeed, angle of attack, and angle of side slip are crucial to its safety, especially when flying close to the stall regime. Various solutions exist, including pitot tubes, angular vanes, and multihole pressure probes. However, current sensors are either too heavy (<inline-formula><tex-math>$>$</tex-math></inline-formula> 30g) or require large airspeeds (<inline-formula><tex-math>$>$</tex-math></inline-formula>20 m/s), making them unsuitable for small uncrewed aerial vehicles. We propose a novel multihole pressure probe, integrating sensing electronics in a single-component structure, resulting in a mechanically robust and lightweight sensor (9 g), which we released to the public domain. Since there is no consensus on two critical design parameters, tip shape (conical vs spherical) and hole spacing (distance between holes), we provide a study on measurement accuracy and noise generation using wind tunnel experiments. The sensor is calibrated using a multivariate polynomial regression model over an airspeed range of 3-27 m/s and an angle of attack/sideslip range of <inline-formula><tex-math>$pm 35^circ$</tex-math></inline-formula>, achieving a mean absolute error of 0.44 m/s and 0.16<inline-formula><tex-math>$^circ$</tex-math></inline-formula>. Finally, we validated the sensor in outdoor flights near the stall regime. Our probe enabled accurate estimations of airspeed, angle of attack and sideslip during different acrobatic manoeuvres. Due to its size and weight, this sensor will enable safe flight for lightweight, uncrewed aerial vehicles flying at low speeds close to the stall regime.","PeriodicalId":13241,"journal":{"name":"IEEE Robotics and Automation Letters","volume":"10 10","pages":"10722-10728"},"PeriodicalIF":5.3,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145050843","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

Enhancing Actuation in Magnetic Soft Actuators: An Inverse Design Framework Incorporating Internal Magnetic Coupling 增强磁性软执行器的致动性：一种结合内部磁耦合的逆设计框架

IF 5.3 2区计算机科学

IEEE Robotics and Automation Letters Pub Date : 2025-09-01 DOI: 10.1109/LRA.2025.3604707

Zhaoda Du;Arjun Sharma;Sahibzada Shahroze Umar;Xiaolong Liu

{"title":"Enhancing Actuation in Magnetic Soft Actuators: An Inverse Design Framework Incorporating Internal Magnetic Coupling","authors":"Zhaoda Du;Arjun Sharma;Sahibzada Shahroze Umar;Xiaolong Liu","doi":"10.1109/LRA.2025.3604707","DOIUrl":"https://doi.org/10.1109/LRA.2025.3604707","url":null,"abstract":"This letter investigates the role of internal magnetic interactions in magnetic soft actuators and introduces a novel framework for their design and optimization. Magnetic soft actuators, composed of soft composites embedded with magnetic particles, enable untethered deformation and actuation under external magnetic fields and hold great potential for robotic applications such as minimally invasive surgery and intervention. Existing design approaches primarily address external field effects and mechanical resistance, often neglecting the contributions of internal magnetic interactions, which are critical to actuator performance. To address this gap, we develop an inverse design methodology that integrates material properties, actuator geometry, and internal magnetic dynamics. By analyzing the interplay between particle volumetric fractions, magnetic moment strengths, and intrinsic properties such as saturation magnetization and coercivity, we propose that internal magnetic coupling can significantly enhance deformation. Rotating-square magnetic metastructures are employed to evaluate actuation behaviors, comparing performance with and without internal coupling. Our findings demonstrate that incorporating internal magnetic interactions into the design process can lead to up to a 36–49% increase in deformation. In addition, the inverse design framework accurately predicted actuator performance, with experimental measurements of relaxed and actuated state deformations matching simulation results within 10%. This study contributes to the field by 1) quantifying the role of internal magnetic interactions in enhancing actuator performance, 2) developing a fabrication process that reliably produces a magnetic soft composite with targeted remanence and Young's modulus, and 3) introducing an optimization framework for predictive actuator design.","PeriodicalId":13241,"journal":{"name":"IEEE Robotics and Automation Letters","volume":"10 10","pages":"10846-10853"},"PeriodicalIF":5.3,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145036788","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

RUSH: Rapid UAV Spatial Hierarchical Exploration via Regional Viewpoint Generation for Large-Scale Environments RUSH：大尺度环境下基于区域视点生成的快速无人机空间分层探索

IF 5.3 2区计算机科学

IEEE Robotics and Automation Letters Pub Date : 2025-09-01 DOI: 10.1109/LRA.2025.3604699

Ningbo Bu;Gen Xu;Hao Zheng;Xuehang Wei;Wenshi Chen;Li Lv;Xiaolu Zhang;Jiangjian Xiao;Zhiqiang Li

{"title":"RUSH: Rapid UAV Spatial Hierarchical Exploration via Regional Viewpoint Generation for Large-Scale Environments","authors":"Ningbo Bu;Gen Xu;Hao Zheng;Xuehang Wei;Wenshi Chen;Li Lv;Xiaolu Zhang;Jiangjian Xiao;Zhiqiang Li","doi":"10.1109/LRA.2025.3604699","DOIUrl":"https://doi.org/10.1109/LRA.2025.3604699","url":null,"abstract":"Exploring large-scale environments quickly and autonomously using uncrewed aerial vehicles (UAVs) remains a challenge. Two major issues, long-distance back-tracking and the UAV's low-velocity flight, significantly hinder exploration efficiency. To tackle this problem, we propose a spatial hierarchical exploration method combining rapid regional viewpoint generation. This involves dividing the exploration space into subregions using an online hgrid spatial decomposition, and determining the order of exploration for these subregions by solving a non-closed traveling salesman problem. Optimal viewpoints are chosen from these subregions based on a global loss function related to frontiers. By dividing the space into subregions and optimizing the path globally, we can reduce the UAV's back-tracking distance. Additionally, the selected optimal viewpoints allow UAVs to make smaller turns, avoid obstacles, and achieve better coverage, which helps decrease the occurrence of low-velocity movements and back-tracking. We also incorporate a velocity loss constrain to improve local trajectories, ensuring high-velocity flight. Our proposed method has been analyzed and validated through simulations and real-world tests, showing improved exploration efficiency compared to several leading methods, particularly in large-scale environments.","PeriodicalId":13241,"journal":{"name":"IEEE Robotics and Automation Letters","volume":"10 10","pages":"10698-10705"},"PeriodicalIF":5.3,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145051039","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