IEEE Transactions on Robotics最新文献_第10页

The Unreasonable Effectiveness of Discrete-Time Gaussian Process Mixtures for Robot Policy Learning 离散时间高斯混合过程在机器人策略学习中的不合理有效性

IF 11.1 1区计算机科学

IEEE Transactions on Robotics Pub Date : 2026-01-01 Epub Date: 2026-03-26 DOI: 10.1109/TRO.2026.3697167

Jan Ole von Hartz;Adrian Röfer;Joschka Boedecker;Abhinav Valada

{"title":"The Unreasonable Effectiveness of Discrete-Time Gaussian Process Mixtures for Robot Policy Learning","authors":"Jan Ole von Hartz;Adrian Röfer;Joschka Boedecker;Abhinav Valada","doi":"10.1109/TRO.2026.3697167","DOIUrl":"https://doi.org/10.1109/TRO.2026.3697167","url":null,"abstract":"In this article, we present mixture of discrete-time Gaussian processes (MiDiGaPs), a novel approach for flexible policy representation and imitation learning in robot manipulation. MiDiGaP enables learning from as few as five demonstrations using only camera observations and generalizes across a wide range of challenging tasks. It excels at long-horizon behaviors, such as making coffee, highly constrained motions, such as opening doors, dynamic actions, such as scooping with a spatula, and multimodal tasks, such as hanging a mug. MiDiGaP learns these tasks on a CPU in less than a minute and scales linearly to large datasets. We also develop a rich suite of tools for inference-time steering using evidence, such as collision signals and robot kinematic constraints. This steering enables novel generalization capabilities, including obstacle avoidance and cross-embodiment policy transfer. MiDiGaP achieves state-of-the-art performance on diverse few-shot manipulation benchmarks. On constrained RLBench tasks, it improves policy success by 76 percentage points and reduces trajectory cost by 67%. On multimodal tasks, it improves policy success by 48 percentage points while improving sample efficiency 7-fold. In cross-embodiment transfer, it more than doubles policy success. We make the code publicly available.","PeriodicalId":50388,"journal":{"name":"IEEE Transactions on Robotics","volume":"42 ","pages":"2419-2438"},"PeriodicalIF":11.1,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148442464","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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 General Safety Framework for Autonomous Manipulation in Human Environments 人类环境中自主操作的通用安全框架

IF 11.1 1区计算机科学

IEEE Transactions on Robotics Pub Date : 2026-01-01 Epub Date: 2026-06-23 DOI: 10.1109/TRO.2026.3706550

Jakob Thumm;Julian Balletshofer;Leonardo Maglanoc;Luis Muschal;Matthias Althoff

{"title":"A General Safety Framework for Autonomous Manipulation in Human Environments","authors":"Jakob Thumm;Julian Balletshofer;Leonardo Maglanoc;Luis Muschal;Matthias Althoff","doi":"10.1109/TRO.2026.3706550","DOIUrl":"10.1109/TRO.2026.3706550","url":null,"abstract":"Autonomous robots are projected to significantly augment the manual workforce, especially in repetitive and hazardous tasks. For a successful deployment of such robots in human environments, it is crucial to guarantee human safety. State-of-the-art approaches to ensure human safety are either too conservative to permit a natural human–robot collaboration or make strong assumptions that do not hold for autonomous robots, e.g., no clamping is possible. Therefore, we propose the <underline>shield for <underline>Safe <underline>Autonomous human–robot collaboration through <underline>Reachability <underline>Analysis (SARA shield). This novel power and force limiting framework provides formal safety guarantees for manipulation in human environments, while realizing fast robot speeds. As unconstrained contacts allow for significantly higher contact forces than constrained contacts (also known as clamping), we use reachability analysis to classify potential contacts by their type in an over-approximative way. For each contact type, we formally verify that the kinetic energy of the robot is below pain and injury thresholds for the respective human body part in contact. Our experiments show that SARA shield satisfies the contact safety constraints, while completing collaborative tasks 15.9% faster than the best-performing state-of-the-art approach.","PeriodicalId":50388,"journal":{"name":"IEEE Transactions on Robotics","volume":"42 ","pages":"2806-2823"},"PeriodicalIF":11.1,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11575118","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148314125","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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

Learning Robot Safety From Sparse Human Feedback Using Conformal Prediction 利用保形预测从稀疏人类反馈中学习机器人安全

IF 11.1 1区计算机科学

IEEE Transactions on Robotics Pub Date : 2026-01-01 Epub Date: 2026-06-23 DOI: 10.1109/TRO.2026.3706570

Aaron O. Feldman;Joseph A. Vincent;Maximilian Adang;JunEn Low;Mac Schwager

{"title":"Learning Robot Safety From Sparse Human Feedback Using Conformal Prediction","authors":"Aaron O. Feldman;Joseph A. Vincent;Maximilian Adang;JunEn Low;Mac Schwager","doi":"10.1109/TRO.2026.3706570","DOIUrl":"10.1109/TRO.2026.3706570","url":null,"abstract":"Ensuring robot safety can be challenging; user-defined constraints can miss edge cases, policies can become unsafe even when trained from safe data, and safety can be subjective. Thus, we learn about robot safety by showing policy trajectories to a human who flags unsafe behavior. From this binary feedback, we use the statistical method of conformal prediction to identify a region of states, potentially in learned latent space, guaranteed to contain a user-specified fraction of future policy errors. Our method is sample-efficient, as it builds on nearest neighbor classification and avoids withholding data as is common with conformal prediction. By alerting if the robot reaches the suspected unsafe region, we obtain a warning system that mimics the human's safety preferences with guaranteed miss rate. From video labeling, our system can detect when a quadcopter visuomotor policy will fail to steer through a designated gate. We present an approach for policy improvement by avoiding the suspected unsafe region. With it we improve a model predictive controller's safety, as shown in experimental testing with 30 quadcopter flights across 6 navigation tasks. Code and videos are provided.","PeriodicalId":50388,"journal":{"name":"IEEE Transactions on Robotics","volume":"42 ","pages":"2824-2842"},"PeriodicalIF":11.1,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148314128","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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

Visibility-Aware Cooperative Tracking With Decentralized LiDAR-Based Aerial Swarms 基于分散激光雷达的空中蜂群的可视性感知协同跟踪

IF 11.1 1区计算机科学

IEEE Transactions on Robotics Pub Date : 2026-01-01 Epub Date: 2026-08-12 DOI: 10.1109/TRO.2026.3723180

Longji Yin;Yunfan Ren;Fangcheng Zhu;Liuyu Shi;Fanze Kong;Benxu Tang;Wenyi Liu;Ximin Lyu;Fu Zhang

{"title":"Visibility-Aware Cooperative Tracking With Decentralized LiDAR-Based Aerial Swarms","authors":"Longji Yin;Yunfan Ren;Fangcheng Zhu;Liuyu Shi;Fanze Kong;Benxu Tang;Wenyi Liu;Ximin Lyu;Fu Zhang","doi":"10.1109/TRO.2026.3723180","DOIUrl":"10.1109/TRO.2026.3723180","url":null,"abstract":"Autonomous aerial tracking with drones offers vast potential for surveillance, cinematography, and industrial inspection. While single-drone tracking has been extensively studied, swarm-based target tracking remains underexplored despite its advantages in distributed perception, fault tolerance, and multidirectional coverage. In this article, we propose a decentralized a decentralized swarm tracking framework based on Light Detection and Ranging (LiDAR) sensors that enablesvisibility-aware cooperative tracking in complex environments. To address visibility, we introduce a novel spherical signed distance field (SSDF)-based metric for 3-D environmental occlusion representation, coupled with an algorithm that enables real-time onboard SSDF updating. A general field-of-view alignment cost supporting heterogeneous LiDAR configurations is proposed for consistent target observation. Swarm coordination is enhanced through costs that enforce inter-robot clearance, prevent mutual occlusions, and facilitate 3-D multidirectional target encirclement via a novel electrostatic-potential-inspired distribution metric. These are integrated into a hierarchical planner combining a kinodynamic front-end searcher with a spatiotemporal <inline-formula><tex-math>$text{SE}(3)$</tex-math></inline-formula> back-end optimizer. The proposed approach is thoroughly evaluated through comprehensive benchmark comparisons and ablation studies. Deployed on heterogeneous LiDAR swarms, the fully decentralized system supports collaborative perception, distributed planning, and dynamic reconfigurability. Validated through extensive real-world experiments in cluttered outdoor environments, the proposed system demonstrates robust cooperative tracking of dynamic targets (drones, humans) while achieving visibility maintenance.","PeriodicalId":50388,"journal":{"name":"IEEE Transactions on Robotics","volume":"42 ","pages":"3388-3407"},"PeriodicalIF":11.1,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148728093","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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

Fast and Robust Online Initialization of Monocular Visual-Inertial Odometry via One-Dimensional Cost Approximation 基于一维代价逼近的单目视觉惯性里程计快速鲁棒在线初始化

IF 10.5 1区计算机科学

IEEE Transactions on Robotics Pub Date : 2026-01-01 Epub Date: 2026-04-21 DOI: 10.1109/TRO.2026.3686255

Jiseock Kang;Jaeu Choe;Doyoon Kong;Byoungkwon Yoon;Jaehwi Cho;Dongjun Lee

{"title":"Fast and Robust Online Initialization of Monocular Visual-Inertial Odometry via One-Dimensional Cost Approximation","authors":"Jiseock Kang;Jaeu Choe;Doyoon Kong;Byoungkwon Yoon;Jaehwi Cho;Dongjun Lee","doi":"10.1109/TRO.2026.3686255","DOIUrl":"10.1109/TRO.2026.3686255","url":null,"abstract":"In this article, we present a fast and accurate initialization algorithm of monocular visual-inertial odometry (MVIO). Our algorithm enables MVIO initialization within under-second motion time (0.45 s for Q1 and 0.7 s for Q2) without divergence for 1500 random runs in the EuroC-MAV and TUM-VI dataset. Our algorithm is based on almost-exact one-dimensional (1-D) approximation of the loosely coupled MVIO (LC-MVIO) problem, which is obtained by approximately decoupling optimization of vision rotation error from the original LC-MVIO optimization. Thanks to the efficiency of 1-D domain exploration, this approximated LC-MVIO is feasible without the initial guess, therefore can be used as an initializer of the original MVIO. Based on this 1-D formulation, we design our initializer with exhaustive correctness guarantee, a novel estimator guarantee we propose in this work, that certifies the absence of multiple, ambiguous solution modes with similar likelihood cost. Our algorithm is validated through Monte-Carlo simulation, real-world dataset experiment, and real-vehicle experiment. An open-source MVIO pipeline with the suggested initialization algorithm is also provided as a supplement.","PeriodicalId":50388,"journal":{"name":"IEEE Transactions on Robotics","volume":"42 ","pages":"2289-2304"},"PeriodicalIF":10.5,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11488893","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147731760","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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

Safe and Agile Transportation of Cable-Suspended Payload via Multiple Aerial Robots 多空中机器人悬索载荷的安全敏捷运输

IF 10.5 1区计算机科学

IEEE Transactions on Robotics Pub Date : 2026-01-01 Epub Date: 2026-03-24 DOI: 10.1109/TRO.2026.3677010

Yongchao Wang;Junjie Wang;Xiaobin Zhou;Tiankai Yang;Xin Zhou;Chao Xu;Fei Gao

{"title":"Safe and Agile Transportation of Cable-Suspended Payload via Multiple Aerial Robots","authors":"Yongchao Wang;Junjie Wang;Xiaobin Zhou;Tiankai Yang;Xin Zhou;Chao Xu;Fei Gao","doi":"10.1109/TRO.2026.3677010","DOIUrl":"10.1109/TRO.2026.3677010","url":null,"abstract":"Transporting a heavy payload using multiple aerial robots (MARs) is an efficient manner to extend the load capacity of a single aerial robot. However, existing planning schemes for the MAR transportation system (MARTS) still lack the capability to generate a collision-free and dynamically feasible trajectory in real time. Therefore, they are limited to low-agility transportation in simple environments. To bridge the gap, we propose a complete planning scheme for the MARTS, achieving safe and agile aerial transportation (SAAT) of a cable-suspended payload in complex environments. Flatness map for the motor’s revolutions per minute of the aerial robot, considering the complete kinematic constraint and the dynamical coupling between each aerial robot and payload, is derived. To improve the responsiveness for the generation of the safe, dynamically feasible, and agile trajectory in complex environments, a real-time spatiotemporal trajectory planning scheme is proposed for the MARTS. Besides, we break away from the reliance on the state measurement for both the payload and cable, as well as the closed-loop control for the payload, and integrate a fully distributed control scheme to track the agile trajectory that is robust against imprecise payload mass, nonpoint mass payload, wind disturbances, and communication delays. The proposed schemes are extensively validated through benchmark comparisons, ablation studies, and simulations. Finally, extensive real-world experiments are conducted on practical MARTSs containing different numbers of aerial robots with onboard computers and sensors. The result validates the efficiency and robustness of our proposed schemes for the SAAT in complex environments.","PeriodicalId":50388,"journal":{"name":"IEEE Transactions on Robotics","volume":"42 ","pages":"1804-1823"},"PeriodicalIF":10.5,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147506849","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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

Compact One-Shot Modeling of High-Dimensional Demonstrations Using Laplacian Eigenmaps 利用拉普拉斯特征映射的高维证明的紧凑单点建模

IF 10.5 1区计算机科学

IEEE Transactions on Robotics Pub Date : 2026-01-01 Epub Date: 2026-02-18 DOI: 10.1109/TRO.2026.3666134

Sthithpragya Gupta;Aradhana Nayak;Aude Billard

{"title":"Compact One-Shot Modeling of High-Dimensional Demonstrations Using Laplacian Eigenmaps","authors":"Sthithpragya Gupta;Aradhana Nayak;Aude Billard","doi":"10.1109/TRO.2026.3666134","DOIUrl":"10.1109/TRO.2026.3666134","url":null,"abstract":"Learning control policies from high-dimensional robot demonstrations remains challenging due to the need for large datasets, limited generalization, and high model complexity. These limitations hinder data-efficient learning and reactive deployment from limited demonstrations. This article introduces Laplacian Eigenmap-based modeling of nonlinear dynamical systems (LEMON-DS), a compact and data-efficient framework for one-shot learning of stable control policies from high-dimensional demonstrations. LEMON-DS proceeds in the following three stages: first, a graph Laplacian-based spectral embedding that reveals a quasi-linear latent structure from a single trajectory, second, defining a globally asymptotically stable dynamical system (DS) in the latent space, and third, learning a diffeomorphic mapping that reconstructs the demonstrated behavior. Collectively, this pipeline yields a lightweight reactive control policy in the form of a DS that is parameter-efficient, globally asymptotically stable, and faithfully reproduces the demonstrated behavior generalizing across initial conditions. We show empirical performance across diverse robot tasks up to 23 dimensions, outperforming prior approaches in accuracy and model compactness.","PeriodicalId":50388,"journal":{"name":"IEEE Transactions on Robotics","volume":"42 ","pages":"1468-1484"},"PeriodicalIF":10.5,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146230832","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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

Continuum Jacobian-Based Computational Morphogenesis for Soft Robotic Workspace Optimization 基于连续统雅可比矩阵的软机器人工作空间优化计算形态发生

IF 11.1 1区计算机科学

IEEE Transactions on Robotics Pub Date : 2026-01-01 Epub Date: 2026-07-22 DOI: 10.1109/TRO.2026.3716051

Zenan Song;Feifei Chen;Guoying Gu;Xiangyang Zhu

{"title":"Continuum Jacobian-Based Computational Morphogenesis for Soft Robotic Workspace Optimization","authors":"Zenan Song;Feifei Chen;Guoying Gu;Xiangyang Zhu","doi":"10.1109/TRO.2026.3716051","DOIUrl":"10.1109/TRO.2026.3716051","url":null,"abstract":"The robot workspace, which defines the complete set of reachable end-effector positions and orientations, is critical for functional capability. However, quantitative workspace design remains an open challenge in soft robotics. This is due to the complicated implicit kinematics governed by nonlinear continuum mechanics and the prohibitive computational cost of evaluating deformations across the full actuation spectrum. This article presents a computational morphogenesis framework for the automatic optimization of position and orientation workspaces in multichamber soft pneumatic actuators. Our approach is built on three key innovations: 1) a continuum Jacobian, defined as the derivative of the end-effector’s degrees of freedom with respect to the actuation inputs, which transforms the workspace integral from the configuration space to the actuation space, making the volume computation analytically tractable; 2) a second-order adjoint method to derive the analytical shape derivatives of both the displacement field and this Jacobian, providing the explicit gradient of the workspace volume with respect to the robot's morphology; and 3) a differentiable singularity-free geometric model, complemented by an adaptive surface reconstruction algorithm, to represent and evolve the robot's free-form shape. The framework is validated by designing multichamber pneumatic soft actuators, achieving an eightfold increase in the 3-D positional workspace volume and a 1.6-fold increase in the 2-D orientational workspace volume compared to the baseline Pneu-Nets actuators.","PeriodicalId":50388,"journal":{"name":"IEEE Transactions on Robotics","volume":"42 ","pages":"3048-3068"},"PeriodicalIF":11.1,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148586794","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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

URGE: Efficient Decentralized Multirobot Exploration Guided by Unknown Regions Under Limited Communication URGE：有限通信条件下未知区域引导下的高效客户端分散多机器人探索

IF 11.1 1区计算机科学

IEEE Transactions on Robotics Pub Date : 2026-01-01 Epub Date: 2026-07-17 DOI: 10.1109/TRO.2026.3714659

Qingchen Bi;Xuebo Zhang;Shiyong Zhang;Qianli Dong;Jing Yuan

{"title":"URGE: Efficient Decentralized Multirobot Exploration Guided by Unknown Regions Under Limited Communication","authors":"Qingchen Bi;Xuebo Zhang;Shiyong Zhang;Qianli Dong;Jing Yuan","doi":"10.1109/TRO.2026.3714659","DOIUrl":"10.1109/TRO.2026.3714659","url":null,"abstract":"Multirobot autonomous exploration often suffers from low efficiency and high communication overhead. To address this, we propose an unknown-region-guided autonomous exploration framework (URGE), which introduces a lightweight, subregion-based environmental representation and information sharing scheme to enable a task allocation strategy that jointly optimizes cost and task load, ultimately achieving spatially dispersed exploration. To capture sufficient spatial information while significantly reducing inter-robot communication volume, the framework incorporates a novel regionalized exploration information map (REIM) that abstracts the environment into subregions with different states. Based on the REIM, a task allocation strategy formulated as a joint optimization problem is proposed. It minimizes the total path cost while balancing the task load across robots, encouraging spatially dispersed exploration and fully leveraging each robot's exploration capability. Furthermore, we extend prior route planning strategies by introducing global geometric cues. This enables more globally informed exploration routes and promotes the exploration of distant, unknown regions. The proposed framework is comprehensively evaluated using five metrics through extensive comparisons with existing methods, ablation studies, and real-world experiments. Compared with the state-of-the-art methods, URGE improves exploration efficiency by 13.3%–45.6% and reduces redundant exploration by 22.5%–51.5%. The evaluation results also demonstrate that URGE achieves superior cooperative performance and strong practical applicability, while maintaining low communication overhead.","PeriodicalId":50388,"journal":{"name":"IEEE Transactions on Robotics","volume":"42 ","pages":"3028-3047"},"PeriodicalIF":11.1,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148475830","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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

Allocation for Omnidirectional Aerial Robots: Incorporating Power Dynamics 全向空中机器人的分配：结合动力动力学

IF 10.5 1区计算机科学

IEEE Transactions on Robotics Pub Date : 2026-01-01 Epub Date: 2026-04-28 DOI: 10.1109/TRO.2026.3688101

Eugenio Cuniato;Mike Allenspach;Thomas Stastny;Helen Oleynikova;Roland Siegwart;Michael Pantic

{"title":"Allocation for Omnidirectional Aerial Robots: Incorporating Power Dynamics","authors":"Eugenio Cuniato;Mike Allenspach;Thomas Stastny;Helen Oleynikova;Roland Siegwart;Michael Pantic","doi":"10.1109/TRO.2026.3688101","DOIUrl":"https://doi.org/10.1109/TRO.2026.3688101","url":null,"abstract":"Tilt-rotor aerial robots are more dynamic and versatile than fixed-rotor platforms, since the thrust vector and body orientation are decoupled. However, the coordination of servos and propellers (the <italic>allocation problem) is not trivial, especially accounting for overactuation and actuator dynamics. We incrementally build and present three novel allocation methods for tilt-rotor aerial robots, comparing them to state-of-the-art methods on a real system performing dynamic maneuvers. We extend the state-of-the-art geometric allocation (GA) into a differential allocation, which uses the platform’s redundancy and does not suffer from singularities. We expand it by incorporating actuator dynamics and propeller <italic>power dynamics. These allow us to model dynamic propeller acceleration limits, bringing two main advantages: balancing propeller speed without the need of nullspace goals and allowing the platform to selectively turn off propellers during flight, opening the door to new manipulation possibilities. We also use actuator dynamics and limits to normalize the allocation problem, making it easier to tune and allowing it to track 70% faster trajectories than a GA.","PeriodicalId":50388,"journal":{"name":"IEEE Transactions on Robotics","volume":"42 ","pages":"2166-2177"},"PeriodicalIF":10.5,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148171703","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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