IEEE Transactions on Robotics最新文献_第4页

Splat-Nav: Safe Real-Time Robot Navigation in Gaussian Splatting Maps

IF 9.4 1区计算机科学

IEEE Transactions on Robotics Pub Date : 2025-03-17 DOI: 10.1109/TRO.2025.3552348

Timothy Chen;Ola Shorinwa;Joseph Bruno;Aiden Swann;Javier Yu;Weijia Zeng;Keiko Nagami;Philip Dames;Mac Schwager

{"title":"Splat-Nav: Safe Real-Time Robot Navigation in Gaussian Splatting Maps","authors":"Timothy Chen;Ola Shorinwa;Joseph Bruno;Aiden Swann;Javier Yu;Weijia Zeng;Keiko Nagami;Philip Dames;Mac Schwager","doi":"10.1109/TRO.2025.3552348","DOIUrl":"10.1109/TRO.2025.3552348","url":null,"abstract":"We present Splat-Nav, a real-time robot navigation pipeline for Gaussian splatting (GSplat) scenes, a powerful new 3-D scene representation. Splat-Nav consists of two components: first, Splat-Plan, a safe planning module, and second, Splat-Loc, a robust vision-based pose estimation module. Splat-Plan builds a safe-by-construction polytope corridor through the map based on mathematically rigorous collision constraints and then constructs a Bézier curve trajectory through this corridor. Splat-Loc provides real-time recursive state estimates given only an RGB feed from an on-board camera, leveraging the point-cloud representation inherent in GSplat scenes. Working together, these modules give robots the ability to recursively replan smooth and safe trajectories to goal locations. Goals can be specified with position coordinates, or with language commands by using a semantic GSplat. We demonstrate improved safety compared to point cloud-based methods in extensive simulation experiments. In a total of 126 hardware flights, we demonstrate equivalent safety and speed compared to motion capture and visual odometry, but without a manual frame alignment required by those methods. We show online replanning at more than 2 Hz and pose estimation at about 25 Hz, an order of magnitude faster than neural radiance field-based navigation methods, thereby enabling real-time navigation.","PeriodicalId":50388,"journal":{"name":"IEEE Transactions on Robotics","volume":"41 ","pages":"2765-2784"},"PeriodicalIF":9.4,"publicationDate":"2025-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143640775","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

Strategic Decision-Making in Multiagent Domains: A Weighted Constrained Potential Dynamic Game Approach

IF 9.4 1区计算机科学

IEEE Transactions on Robotics Pub Date : 2025-03-17 DOI: 10.1109/TRO.2025.3552325

Maulik Bhatt;Yixuan Jia;Negar Mehr

{"title":"Strategic Decision-Making in Multiagent Domains: A Weighted Constrained Potential Dynamic Game Approach","authors":"Maulik Bhatt;Yixuan Jia;Negar Mehr","doi":"10.1109/TRO.2025.3552325","DOIUrl":"10.1109/TRO.2025.3552325","url":null,"abstract":"In interactive multiagent settings, decision-making and planning are challenging mainly due to the agents' interconnected objectives. Dynamic game theory offers a formal framework for analyzing such intricacies. Yet, solving constrained dynamic games and determining the interaction outcome in the form of generalized Nash equilibria (GNE) pose computational challenges due to the need for solving constrained coupled optimal control problems. In this article, we address this challenge by proposing to leverage the special structure of many real-world multiagent interactions. More specifically, our key idea is to leverage constrained dynamic potential games, which are games for which GNE can be found by solving a single constrained optimal control problem associated with minimizing the potential function. We argue that constrained dynamic potential games can effectively facilitate interactive decision-making in many multiagent interactions. We will identify structures in realistic multiagent interactive scenarios that can be transformed into weighted constrained potential dynamic games (WCPDGs). We will show that the GNE of the resulting WCPDG can be obtained by solving a single constrained optimal control problem. We will demonstrate the effectiveness of the proposed method through various simulation studies and show that we achieve significant improvements in solve time compared to state-of-the-art game solvers. We further provide experimental validation of our proposed method in a navigation setup involving two quadrotors carrying a rigid object while avoiding collisions with two humans.","PeriodicalId":50388,"journal":{"name":"IEEE Transactions on Robotics","volume":"41 ","pages":"2749-2764"},"PeriodicalIF":9.4,"publicationDate":"2025-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143640489","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

CoverLib: Classifiers-Equipped Experience Library by Iterative Problem Distribution Coverage Maximization for Domain-Tuned Motion Planning

IF 7.8 1区计算机科学

IEEE Transactions on Robotics Pub Date : 2025-03-17 DOI: 10.1109/tro.2025.3552346

Hirokazu Ishida, Naoki Hiraoka, Kei Okada, Masayuki Inaba

引用次数: 0

Modeling, Embedded Control, and Design of Soft Robots Using a Learned Condensed FEM Model

IF 9.4 1区计算机科学

IEEE Transactions on Robotics Pub Date : 2025-03-17 DOI: 10.1109/TRO.2025.3552353

Tanguy Navez;Etienne Ménager;Paul Chaillou;Olivier Goury;Alexandre Kruszewski;Christian Duriez

{"title":"Modeling, Embedded Control, and Design of Soft Robots Using a Learned Condensed FEM Model","authors":"Tanguy Navez;Etienne Ménager;Paul Chaillou;Olivier Goury;Alexandre Kruszewski;Christian Duriez","doi":"10.1109/TRO.2025.3552353","DOIUrl":"10.1109/TRO.2025.3552353","url":null,"abstract":"The finite element method (FEM) is a powerful modeling tool for predicting soft robots' behavior, but its computation time can limit practical applications. In this article, a learning-based approach based on condensation of the FEM model is detailed. The proposed method handles several kinds of actuators and contacts with the environment. We demonstrate that this compact model can be learned as a unified model across several designs and remains very efficient in terms of modeling since we can deduce the direct and inverse kinematics of the robot. Building upon the intuition introduced in (Ménager et al., 2023), the learned model is presented as a general framework for modeling, controlling, and designing soft manipulators. First, the method's adaptability and versatility are illustrated through optimization-based control problems involving positioning and manipulation tasks with mechanical contact-based coupling. Second, the low-memory consumption and the high prediction speed of the learned condensed model are leveraged for real-time embedding control without relying on costly online FEM simulation. Finally, the ability of the learned condensed FEM model to capture soft robot design variations and its differentiability are leveraged in calibration and design optimization applications.","PeriodicalId":50388,"journal":{"name":"IEEE Transactions on Robotics","volume":"41 ","pages":"2441-2459"},"PeriodicalIF":9.4,"publicationDate":"2025-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143640491","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

Safe Start Regions for Medical Steerable Needle Automation

IF 9.4 1区计算机科学

IEEE Transactions on Robotics Pub Date : 2025-03-17 DOI: 10.1109/TRO.2025.3552323

Janine Hoelscher;Inbar Fried;Spiros Tsalikis;Jason Akulian;Robert J. Webster;Ron Alterovitz

{"title":"Safe Start Regions for Medical Steerable Needle Automation","authors":"Janine Hoelscher;Inbar Fried;Spiros Tsalikis;Jason Akulian;Robert J. Webster;Ron Alterovitz","doi":"10.1109/TRO.2025.3552323","DOIUrl":"10.1109/TRO.2025.3552323","url":null,"abstract":"Steerable needles are minimally invasive devices that can enable novel medical procedures by following curved paths to avoid critical anatomical obstacles. We introduce a new start pose robustness metric for steerable needle motion plans. A steerable needle deployment typically consists of a physician manually placing a steerable needle at a precomputed start pose on the surface of tissue and handing off control to a robot, which then autonomously steers the needle through the tissue to the target. The handoff between humans and robots is critical for procedure success, as even small deviations from a planned start pose change the steerable needle's reachable workspace. Our metric is based on a novel geometric method to efficiently compute how far the physician can deviate from the planned start pose in both position and orientation such that the steerable needle can still reach the target. We evaluate our metric through simulation in liver and lung scenarios. Our evaluation shows that our metric can be applied to plans computed by different steerable needle motion planners and that it can be used to efficiently select plans with large safe start regions.","PeriodicalId":50388,"journal":{"name":"IEEE Transactions on Robotics","volume":"41 ","pages":"2424-2440"},"PeriodicalIF":9.4,"publicationDate":"2025-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143640776","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

AVOCADO: Adaptive Optimal Collision Avoidance Driven by Opinion

IF 9.4 1区计算机科学

IEEE Transactions on Robotics Pub Date : 2025-03-17 DOI: 10.1109/TRO.2025.3552350

Diego Martinez-Baselga;Eduardo Sebastián;Eduardo Montijano;Luis Riazuelo;Carlos Sagüés;Luis Montano

{"title":"AVOCADO: Adaptive Optimal Collision Avoidance Driven by Opinion","authors":"Diego Martinez-Baselga;Eduardo Sebastián;Eduardo Montijano;Luis Riazuelo;Carlos Sagüés;Luis Montano","doi":"10.1109/TRO.2025.3552350","DOIUrl":"10.1109/TRO.2025.3552350","url":null,"abstract":"We present AdaptiVe Optimal Collision Avoidance Driven by Opinion (AVOCADO), a novel navigation approach to address holonomic robot collision avoidance when the robot does not know how cooperative the other agents in the environment are. AVOCADO departs from a velocity obstacle's (VO) formulation akin to the optimal reciprocal collision avoidance method. However, instead of assuming reciprocity, it poses an adaptive control problem to adapt to the cooperation level of other robots and agents in real time. This is achieved through a novel nonlinear opinion dynamics design that relies solely on sensor observations. As a by-product, we leverage tools from the opinion dynamics formulation to naturally avoid the deadlocks in geometrically symmetric scenarios that typically suffer VO-based planners. Extensive numerical simulations show that AVOCADO surpasses existing motion planners in mixed cooperative/noncooperative navigation environments in terms of success rate, time to goal and computational time. In addition, we conduct multiple real experiments that verify that AVOCADO is able to avoid collisions in environments crowded with other robots and humans.","PeriodicalId":50388,"journal":{"name":"IEEE Transactions on Robotics","volume":"41 ","pages":"2495-2511"},"PeriodicalIF":9.4,"publicationDate":"2025-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10930712","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143640490","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

A Compact 6D Suction Cup Model for Robotic Manipulation via Symmetry Reduction

IF 9.4 1区计算机科学

IEEE Transactions on Robotics Pub Date : 2025-03-14 DOI: 10.1109/TRO.2025.3551197

Alexander A. Oliva;Maarten J. Jongeneel;Alessandro Saccon

{"title":"A Compact 6D Suction Cup Model for Robotic Manipulation via Symmetry Reduction","authors":"Alexander A. Oliva;Maarten J. Jongeneel;Alessandro Saccon","doi":"10.1109/TRO.2025.3551197","DOIUrl":"10.1109/TRO.2025.3551197","url":null,"abstract":"Active suction cups are widely adopted in industrial and logistics automation. Despite that, validated dynamic models describing their 6D force/torque interaction with objects are rare. This work aims at filling this gap by showing that it is possible to employ a compact model for suction cups, providing good accuracy also for large deformations. Its potential use is for advanced manipulation, planning, and control. We model the interconnected object-suction cup system as a lumped 6D mass-spring-damper systems, employing a potential energy function on <inline-formula><tex-math>$text {SE}(3)$</tex-math></inline-formula>, parametrized by a <inline-formula><tex-math>$6times 6$</tex-math></inline-formula> stiffness matrix. By exploiting geometric symmetries of the suction cup, we reduce the parameter identification problem, from <inline-formula><tex-math>$6(6+1) / 2 = 21$</tex-math></inline-formula> to only <inline-formula><tex-math>$boldsymbol {5}$</tex-math></inline-formula> independent parameters, greatly simplifying the parameter identification procedure, that is otherwise ill-conditioned. Experimental validation is provided and data is shared openly to further stimulate research. As an indication of the achievable pose prediction in steady state, for an object of about <inline-formula><tex-math>$boldsymbol {1.75}$</tex-math></inline-formula> kg, we obtain a pose error in the order of <inline-formula><tex-math>$boldsymbol {5}$</tex-math></inline-formula> mm and <inline-formula><tex-math>$boldsymbol {3}$</tex-math></inline-formula> deg, with a gripper inclination of <inline-formula><tex-math>$boldsymbol {60}$</tex-math></inline-formula> deg.","PeriodicalId":50388,"journal":{"name":"IEEE Transactions on Robotics","volume":"41 ","pages":"2285-2300"},"PeriodicalIF":9.4,"publicationDate":"2025-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143631372","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

RADIUM: Predicting and Repairing End-to-End Robot Failures Using Gradient-Accelerated Sampling

IF 9.4 1区计算机科学

IEEE Transactions on Robotics Pub Date : 2025-03-14 DOI: 10.1109/TRO.2025.3551198

Charles Dawson;Anjali Parashar;Chuchu Fan

{"title":"RADIUM: Predicting and Repairing End-to-End Robot Failures Using Gradient-Accelerated Sampling","authors":"Charles Dawson;Anjali Parashar;Chuchu Fan","doi":"10.1109/TRO.2025.3551198","DOIUrl":"10.1109/TRO.2025.3551198","url":null,"abstract":"Before deploying autonomous systems in safety-critical applications, we must be able to understand and verify the safety of these systems. For cases where the risk or cost of real-world testing is prohibitive, we propose a simulation-based framework for 1) predicting ways in which an autonomous system is likely to fail and 2) automatically adjusting the system's design and control policy to preemptively mitigate those failures. Existing tools for failure prediction struggle to search over high-dimensional environmental parameters, cannot efficiently handle end-to-end testing for systems with vision in the loop, and provide little guidance on how to mitigate failures once they are discovered. We approach this problem through the lens of approximate Bayesian inference, using differentiable simulation and rendering for efficient failure case prediction and repair (and providing a gradient-free version of our algorithm for cases where a differentiable simulator is not available). We include a theoretical and empirical evaluation of the tradeoffs between gradient-based and gradient-free methods, applying our approach to a range of robotics and control problems, including optimizing search patterns for robot swarms, UAV formation control, and robust network control. Compared to optimization-based falsification methods, our method predicts a more diverse, representative set of failure modes, and we find that our use of differentiable simulation yields solutions that have up to 10x lower cost and requires up to 2x fewer iterations to converge relative to gradient-free techniques. In hardware experiments, we find that repairing control policies using our method leads to a 5x robustness improvement.","PeriodicalId":50388,"journal":{"name":"IEEE Transactions on Robotics","volume":"41 ","pages":"2268-2284"},"PeriodicalIF":9.4,"publicationDate":"2025-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143631489","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

Dynamic Control of Multimodal Motion for Bistable Soft Millirobots in Complex Environments

IF 9.4 1区计算机科学

IEEE Transactions on Robotics Pub Date : 2025-03-14 DOI: 10.1109/TRO.2025.3551541

Zhengyuan Xin;Shihao Zhong;Anping Wu;Zhiqiang Zheng;Qing Shi;Qiang Huang;Toshio Fukuda;Huaping Wang

{"title":"Dynamic Control of Multimodal Motion for Bistable Soft Millirobots in Complex Environments","authors":"Zhengyuan Xin;Shihao Zhong;Anping Wu;Zhiqiang Zheng;Qing Shi;Qiang Huang;Toshio Fukuda;Huaping Wang","doi":"10.1109/TRO.2025.3551541","DOIUrl":"10.1109/TRO.2025.3551541","url":null,"abstract":"Soft millirobots are highly promising for biomedical applications due to their reconfigurability and multifunctionality within physiological environments. However, the diverse and narrow biological cavity environments pose significant adaptability challenges for these millirobots. Here, we present a dual-morphology, thin-film millirobot equipped with a magnetic drive head and a functional tail to facilitate multimodal motion and targeted cell delivery. The millirobot can reversibly switch between two distinct morphologies in response to environmental stimuli through the deformation of its hydrogel body. Utilizing these dual morphologies, the millirobot can perform robust multimodal fundamental motions controlled by magnetic fields. We encapsulate fundamental motions with specific programmable magnetic field parameters into motion primitives, allowing easy invocation and adjustment of motion modes on demand. A knowledge graph is established to map terrain features to motion units, enabling the identification of optimal motion modes based on typical terrain characteristics. Experimental results indicate that the millirobot can effectively switch its morphology and movement modes to navigate various terrains, including narrow and curved channels as small as 1 mm, 0.8 mm high stairs with a 15° incline, and even the complex environment of a swine intestinal lumen. Its functional tail can carry immune cells to target and kill cancer cells. This robot can transport drugs and cells while navigating complex terrains through multimodal motion, paving the way for targeted medical tasks in intricate human environments in the future.","PeriodicalId":50388,"journal":{"name":"IEEE Transactions on Robotics","volume":"41 ","pages":"2662-2676"},"PeriodicalIF":9.4,"publicationDate":"2025-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143631490","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

Informative Path Planning for Active Regression With Gaussian Processes via Sparse Optimization

IF 9.4 1区计算机科学

IEEE Transactions on Robotics Pub Date : 2025-03-07 DOI: 10.1109/TRO.2025.3548865

Shamak Dutta;Nils Wilde;Stephen L. Smith

引用次数: 0