IROS 2025 Papers — Page 8
IEEE/RSJ International Conference on Intelligent Robots and Systems · 1984 papers
Event-Triggered Maps of Dynamics: A Framework for Modeling Spatial Motion Patterns in Non-Stationary Environments
Junyi Shi, Tomasz Kucner
Diffusion modelStochastic Differential Equation
🎯 What it does: Proposes the Event-Triggered Dynamic Mapping (ETMoD) framework for modeling spatial movement patterns in non-stationary environments.
EventSync: Joint Recovery of Temporal Offsets and Relative Orientations for Wide-Baseline Event Cameras
Wanli Xing, Jia Pan
Pose EstimationOptical Flow
🎯 What it does: Developed a software algorithm called EventSync for synchronizing multi-camera event streams and estimating the relative pose between cameras.
Evidential Uncertainty Estimation for Multi-Modal Trajectory Prediction
Sajad Marvi, A. Valada
Autonomous DrivingMultimodality
🎯 What it does: Propose a multi-modal trajectory prediction method based on evidence deep learning, which estimates position and mode probability uncertainties in real-time.
EvidMTL: Evidential Multi-Task Learning for Uncertainty-Aware Semantic Surface Mapping from Monocular RGB Images
Rohit Menon, Maren Bennewitz
SegmentationDepth EstimationSimultaneous Localization and MappingImage
🎯 What it does: Proposed the EvidMTL multi-task learning framework, combining evidence-based depth estimation with semantic segmentation to achieve uncertainty-aware reasoning from monocular RGB images.
ExAMPC: the Data-Driven Explainable and Approximate NMPC with Physical Insights
Jean Pierre Allamaa, Tong Duy Son
OptimizationExplainability and InterpretabilityPhysics Related
🎯 What it does: Propose the ExAMPC method, combining data-driven explainable AI with traditional nonlinear model predictive control (NMPC), to achieve interpretable approximate NMPC and enhance system trustworthiness.
ExFace: Expressive Facial Control for Humanoid Robots with Diffusion Transformers and Bootstrap Training
Dong Zhang, Jiahao Chen
Robotic IntelligenceTransformerDiffusion modelImage
🎯 What it does: Proposes the Expressive Facial Control (ExFace) method based on Diffusion Transformers, achieving precise mapping from facial blendshapes to biomimetic robot motor control.
Exo-ViHa: A Cross-Platform Exoskeleton System with Visual and Haptic Feedback for Efficient Dexterous Skill Learning
Xintao Chao, Wenbo Ding
Robotic IntelligenceSimultaneous Localization and MappingMultimodality
🎯 What it does: Proposed a cross-platform exoskeleton system Exo-ViHa based on 3D printing, which provides visual and tactile feedback and collects robotic hand operation data in real-time from a first-person perspective.
Exoskeleton Gait Adaptation Framework via Hm-DMP and PI2 Optimization for Dynamic Patient Mobility Matching
Qiaohuan Cao, Wei Yang
OptimizationRobotic IntelligenceReinforcement Learning
🎯 What it does: Proposed a closed-loop mobile matching framework that integrates hybrid multi-attractor dynamic movement primitives (Hm-DMP) with path integral strategy improvement (PI2) optimization, achieving real-time adaptive control of lower-limb exoskeleton gait trajectories;
Experimental Comparison of Whole-Body Control Formulations for Humanoid Robots in Task Acceleration and Task Force Spaces
Sait Sovukluk, Christian Ott
Robotic Intelligence
🎯 What it does: An experimental comparison of Inverse Dynamics Whole-Body Control (ID-WBC) and Passivity-Based Whole-Body Control (PB-WBC) on bipedal robots, covering swing leg position and attitude control, squatting with an additional mass modeled without a model, and jumping tasks.
Experimental Evaluation of Radio-aware Semantic Map with 5G-Enabled Mobile Robots
A. Ibanez, Xavier Pérez Costa
Robotic IntelligenceSimultaneous Localization and Mapping
🎯 What it does: Proposed a framework for constructing and utilizing wireless perception semantic maps based on 5G networks, supporting mobile robots in performing task offloading and real-time navigation decisions in unknown environments;
Experimental Evaluation of Safe Trajectory Planning for an Omnidirectional UAV
Mahmoud Hamandi, F. Khorrami
Safty and PrivacyRobotic Intelligence
🎯 What it does: Propose a safe trajectory planning framework for omnidirectional drones that dynamically adjusts tracking speed based on obstacle proximity, and verify its navigation capability in confined spaces on the OmniOcta UAV.
Experimental Open-Source Framework for Underwater Pick-and-Place Studies with Lightweight UVMS – An Extensive Quantitative Analysis
Nathalie Bauschmann, Daniel A. Duecker
OptimizationRobotic IntelligenceBenchmark
🎯 What it does: This paper proposes a complete open-source software framework for fully automated grasping and releasing experiments with a lightweight underwater manipulator (UVMS), extending the previous task-priority control framework by incorporating high-level decision-making and grasping detection methods, and verifying them on BlueROV2 and Alpha5 Manipulator.
eXplainable Intention Estimation in Teleoperated Manipulation Using Deep Dynamic Graph Neural Networks
Prakash Baskaran, Soshi Iba
Explainability and InterpretabilityRobotic IntelligenceGraph Neural Network
🎯 What it does: Developed and demonstrated a dynamic intent estimation framework based on graph neural networks, which can predict low-level actions and high-level tasks in dual-armed robot teleoperation, and validated the correctness and consistency of predictions using interpretability metrics.
ExpliDrive: Bridging Model Predictive Control and Transformers for Interactive Autonomous Driving
Zhexi Lian, Jia Hu
Autonomous DrivingOptimizationExplainability and InterpretabilityTransformer
🎯 What it does: Propose ExpliDrive, which utilizes Transformer to encode vehicle interactions and embeds them into MPC motion planning, achieving active interaction perception and response.
Exploiting Policy Idling for Dexterous Manipulation
Annie S. Chen, Dushyant Rao
Robotic IntelligenceReinforcement Learning
🎯 What it does: Propose a method to alleviate the 'stagnation' problem in robots during high-precision tasks such as grasping and insertion by applying perturbations (Pause-Induced Perturbations, PIP) in detected paused states, and evaluate it on simulated dual-arm tasks and real-world insertion tasks.
Exploratory Movement Strategies for Texture Discrimination with a Neuromorphic Tactile Sensor
Xingchen Xu, B. Ward-Cherrier
RecognitionComputational EfficiencyRobotic Intelligence
🎯 What it does: Developed a robot texture classification framework based on neuromorphic tactile sensors, investigating the impact of different exploration actions on classification performance.
Exploring Spontaneous Social Interaction Swarm Robotics Powered by Large Language Models
Yitao Jiang, Devin J. Balkcom
Robotic IntelligenceTransformerLarge Language Model
🎯 What it does: Built a decentralized multi-robot system that utilizes large language models (LLMs) for reasoning, enabling robots to discover each other, share information, and dynamically coordinate through natural language.
Exploring Stiffness Gradient Effects in Magnetically Induced Metamorphic Materials via Continuum Simulation and Validation
Wentao Shi, Hongliang Ren
Physics Related
🎯 What it does: Constructed graded stiffness magnetically induced deformable materials (GMCs) and developed a numerical model for their bending performance, while training an efficient and accurate bending prediction extension model.
Exploring the Virtual Pivot Point in Unilateral Transfemoral Amputee Locomotion: Implications for Prosthetic Development
Omid Mohseni, A. Seyfarth
Biomedical Data
🎯 What it does: First study on the virtual pivot point (VPP) in unilateral above-knee amputees, analyzing changes in quality and position of VPP in longitudinal and planar dynamics
Explosive Jumping with Rigid and Articulated Soft Quadrupeds via Example Guided Reinforcement Learning
Georgios Apostolides, Jiatao Ding
Robotic IntelligenceReinforcement Learning
🎯 What it does: This paper proposes a deep reinforcement learning framework based on example guidance, which learns controlled, variable-distance jumps for quadruped robots equipped with passive elastic structures, and enhances robustness to uneven terrain through advanced training.
Exponentially Weighted Instance-Aware Repeat Factor Sampling for Long-Tailed Object Detection Model Training in Unmanned Aerial Vehicles Surveillance Scenarios
Taufiq Ahmed, Sasu Tarkoma
Object DetectionData-Centric LearningConvolutional Neural NetworkImage
🎯 What it does: Developed an exponentially weighted instance-aware resampling method (E-IRFS) to address long-tailed class imbalance in UAV monitoring scenarios.
Extraction of Robotic Surface Processing Strategies from Human Demonstrations
Thomas Eiband, Alin Albu-Schäffer
Robotic IntelligenceReinforcement Learning from Human FeedbackMultimodalitySequential
🎯 What it does: This paper proposes a system that records human actions and contact forces during surface processing using electric sanding tools, provides a public dataset, and extracts robot execution strategies based on multi-user demonstrations through Learning from Demonstration (LfD).
Extreme-Hydrostatic-Pressure Resilient Dielectric Elastomer Actuator for Propeller Propulsion
Boyuan Du, Huichan Zhao
Robotic IntelligencePhysics Related
🎯 What it does: Designed and tested a rotational dielectric elastomer actuator capable of sustained operation under extremely high hydrostatic pressure for deep-sea propulsion.
Eye-In-Finger: Smart Fingers for Delicate Assembly and Disassembly of LEGO
Zhenran Tang, Changliu Liu
Robotic IntelligenceImage
🎯 What it does: Proposed the 'Eye-In-Finger' tool design concept, embedding low-cost high-resolution visual perception directly into the tool tip, and achieving real-time fine calibration for LEGO assembly and disassembly tasks, enhancing the robot's precise manipulation capabilities in cluttered environments.
FABG : End-to-end Imitation Learning for Embodied Affective Human-Robot Interaction
Yang Zhang, Jianwei Zhang
Robotic IntelligenceVideo
🎯 What it does: Proposed FABG (Facial Affective Behavior Generation) — an end-to-end imitative learning system for generating natural and fluent human-robot interaction facial emotional behaviors. High-quality demonstrations were collected using an immersive VR demonstration system, a predictive-driven delay compensation strategy was proposed, and the system was deployed and validated on a 25-degree-of-freedom humanoid robot, demonstrating effectiveness in four interaction tasks: emotional interaction, dynamic tracking, gaze focusing, and gesture recognition.
FABRIC: FAbricating Bodily-Expressive Robots for Inclusive and Low-Cost Design
A. Arabi, Jeeeun Kim
Robotic IntelligenceVideo
🎯 What it does: Developed an end-to-end toolkit called FABRIC for low-cost 3D printed robot fabrication and body language programming. The robot captures and translates users' body expressions through learning from demonstrations, and is equipped with a visual programming interface to integrate multi-source demonstrations.
Failure Forecasting Boosts Robustness of Sim2Real Rhythmic Insertion Policies
Yuhan Liu, Abdeslam Boularias
Pose EstimationDomain AdaptationReinforcement Learning
🎯 What it does: Proposed a sim-to-real framework for rhythmic insertion tasks, combining reinforcement learning insertion strategies with a failure prediction module, utilizing 6D joint pose tracking to achieve high-precision insertion and rotation, and performing simple recovery operations when failures occur.
FalconGym: A Photorealistic Simulation Framework for Zero-Shot Sim-to-Real Vision-Based Quadrotor Navigation
Yan Miao, Sayan Mitra
Domain AdaptationRobotic IntelligenceTransformerReinforcement LearningNeural Radiance FieldImageMultimodality
🎯 What it does: Built a realistic simulation framework FalconGym for training visual control policies in NeRF environments, achieving zero-shot transfer from simulation to real-world flight;
Fast Policy: Accelerating Visuomotor Policies without Re-training
Tong Wu, Zheng Wang
Computational EfficiencyRobotic IntelligenceConvolutional Neural NetworkReinforcement LearningDiffusion model
🎯 What it does: Propose Fast Policy (FP), which accelerates visual motion policies by reusing UNet encoder features in non-critical denoising steps and dynamically selecting key steps.
Fast Real-Time Neural Network-Based Kinematics Solving of the Cosserat Rod Model for a Parallel Continuum Surgical Manipulator
Xipeng Wu, Changsheng Li
Computational EfficiencyRobotic IntelligenceBiomedical DataPhysics Related
🎯 What it does: Propose a real-time inverse kinematics solver based on neural networks for miniaturized parallel continuum surgical manipulators, using the Cosserat rod model for kinematic modeling.
Fast-Revisit Coverage Path Planning for Autonomous Mobile Patrol Robots Using Long-Range Sensor Information
Srinivas Kachavarapu, Reinhard Gerndt
OptimizationRobotic Intelligence
🎯 What it does: Proposes the Fast-Revisit Coverage Path Planning (FaRe-CPP) algorithm for autonomous mobile patrolling robots to achieve rapid revisit coverage path planning under limited sensing ranges.
Fast(er) Robust Point Cloud Alignment Using Lie Algebra
Jean-Thomas Sexton, Jonathan Gaudreault
Pose EstimationComputational EfficiencyPoint CloudBenchmark
🎯 What it does: Propose an iterative reweighted least squares (IRLS) algorithm based on Lie algebra for robust 3D point cloud registration.
FASTEX: Fast UAV Exploration in Large-Scale Environments Using Dynamically Expanding Grids and Coverage Paths
Xiaoxun Zhang, Hui Cheng
Computational EfficiencyRobotic Intelligence
🎯 What it does: Proposes the FASTEX framework, which utilizes dynamic grid expansion and coverage paths to achieve rapid exploration of unmanned aerial vehicles (UAVs) in large environments.
FastTrack: GPU-Accelerated Tracking for Visual SLAM
Kimia Khabiri, Steven Y. Ko
Simultaneous Localization and MappingVideo
🎯 What it does: Accelerating the tracking module of visual-inertial SLAM systems using GPU, particularly stereo feature matching and local map tracking, to enhance tracking performance.
Fault-Tolerant Model Predictive Control for Safety of Unmanned Surface Vessels Berthing under Multimodal disturbances and Various Constraints
Jiangteng Shi, Yujing Chen
Autonomous DrivingOptimizationSafty and Privacy
🎯 What it does: A fault-tolerant model predictive control (FTMPC) framework is proposed to achieve safe berthing operations of unmanned surface vessels under multi-mode disturbances (external ocean disturbances EODs and internal thruster faults ITFs) and various constraints (underactuated nonlinear dynamics, actuator saturation, obstacle avoidance constraints).
FBG-based Actuation and Data Driven Contact Detection for Smart Steerable Instruments
Syed Zain Mehdi, E. V. Poorten
Robotic IntelligenceRecurrent Neural NetworkTime Series
🎯 What it does: A compact driving system based on fiber Bragg grating (FBG) was developed to control the bending of a steerable tip, and strain was measured on the FBG to estimate thrust. Subsequently, a long short-term memory network (LSTM) was used to predict contact with the surrounding environment based on thrust.
FCRF: Flexible Constructivism Reflection for Long-Horizon Robotic Task Planning with Large Language Models
Yufan Song, Shiqiang Zhu
Robotic IntelligenceTransformerLarge Language Model
🎯 What it does: Proposed the FCRF (Flexible Constructivism Reflection Framework), a Mentor-Actor architecture that utilizes large language models (LLMs) to achieve flexible self-reflection in long-term robot task planning.
Fear-Based Behavior Adaptation for Robust Walking Robots using Unsupervised Health Estimation
Tristan Schnell, R. Dillmann
Anomaly DetectionRobotic IntelligenceMultimodality
🎯 What it does: Implementing fear-based robot behavior adaptation using unsupervised anomaly detection, enabling robots to quickly and automatically respond to any unexpected issues in unknown environments.
Feasibility Analysis of real-time Robustness Certification
Emmanouil Seferis, Stefanos D. Kollias
Safty and PrivacyComputational EfficiencyAdversarial AttackImage
🎯 What it does: Investigated the feasibility of achieving real-time robustness proofs in Randomized Smoothing (RS) by significantly reducing the number of sampling times, and proposed a self-improvement method to alleviate the certified radius degradation caused by sample reduction.
Feature Matching-Based Gait Phase Prediction for Obstacle Crossing Control of Powered Transfemoral Prosthesis
Jiaxuan Zhang, Chenglong Fu
OptimizationHyperparameter SearchRobotic IntelligenceTime SeriesBiomedical Data
🎯 What it does: For lower-limb amputees using powered knee prostheses, the study installs inertial sensors on the healthy ankle, uses a genetic algorithm-optimized neural network to predict thigh and knee angles, and employs a gait phase prediction algorithm to determine the drive angle index of the prosthetic knee motor, thereby achieving obstacle crossing control.
Feature-aligned Fisheye Object Detection Network for Autonomous Driving
Hu Cao, Alois C. Knoll
Object DetectionAutonomous DrivingConvolutional Neural NetworkImage
🎯 What it does: Proposed a feature-aligned fisheye object detection network for autonomous driving, combining the FaPM and LaDH modules to achieve feature and spatial alignment
FedEMA: Federated Exponential Moving Averaging with Negative Entropy Regularizer in Autonomous Driving
Wei-Bin Kou, Yik-Chung Wu
Autonomous DrivingFederated LearningImage
🎯 What it does: Propose the FedEMA framework, integrating server-side EMA with vehicle-side negative entropy regularization to address the time catastrophic forgetting problem in FL AD models.
Feedback Control of a Single-Tail Bioinspired 59-mg Swimmer
Conor K. Trygstad, N. O. Pérez-Arancibia
Robotic IntelligencePhysics Related
🎯 What it does: Developed a single-tail FRISSHBot based on shape memory alloy (SMA) dual-fold actuator, achieving controllable motion in 2D space, and first realized feedback-controlled trajectory tracking at the sub-millimeter level in robotic systems.
Feedback Control of a Two-Degree-of-Freedom Electromagnetic Reluctance Precision Motion System
Michael Pumphrey, M. Janaideh
OptimizationPhysics Related
🎯 What it does: Designed and verified an Xθ two-degree-of-freedom electromagnetic impedance precision motion system based on magnetic reluctance drive, combining reluctance actuator with two moving magnet drivers to achieve precise translational and rotational control.
FEG-VON: Frontier Embedding Graph for Efficient Visual Object Navigation
Yingru Dai, Guijin Wang
Autonomous DrivingComputational EfficiencyGraph Neural NetworkVision Language ModelMultimodality
🎯 What it does: Proposes a training-free framework that constructs and maintains a frontier embedding graph to achieve efficient visual goal navigation.
FGS-SLAM: Fourier-based Gaussian Splatting for Real-time SLAM with Sparse and Dense Map Fusion
Yansong Xu, Weijia Zhou
Pose EstimationAutonomous DrivingGaussian SplattingSimultaneous Localization and MappingImage
🎯 What it does: Proposes an adaptive densification method based on Fourier frequency domain analysis to achieve fast convergence of Gaussian representations, and constructs independent and unified sparse and dense maps. The sparse map is used for efficient tracking, while the dense map is used for high-fidelity visual representation.
FIELD: Fast Information-driven Autonomous Exploration using Larger Perception Distance
Yuefeng Zhang, Wenbing Tao
OptimizationRobotic Intelligence
🎯 What it does: Proposes a planner called FIELD that enables fast, information-driven autonomous exploration for UAVs by leveraging a larger perception range.
Find Everything: A General Vision Language Model Approach to Multi-Object Search
Daniel Choi, Aaron Hao Tan
Object DetectionObject TrackingVision Language Model
🎯 What it does: Proposes a novel multi-object search method called Finder, which utilizes a visual language model to locate multiple objects and achieves simultaneous tracking and reasoning through multi-channel score maps and scene-level and object-level semantic relevance score maps; validated through extensive experiments in both simulated and real environments.
Finite-time Guiding Vector Fields for Accelerated Path Following of Nonholonomic Robots
Jian Yang, Weijia Yao
Autonomous DrivingOptimizationRobotic Intelligence
🎯 What it does: Proposed a finite-time guided vector field (finite-time GVF) based on the sign function, and designed a controller for a single-vehicle model to enable nonholonomic robots to follow any smooth n-dimensional path within finite time. The method was extended to multi-robot distributed motion coordination, and its effectiveness was validated through two unmanned ground vehicle experiments.
FLAME: A Federated Learning Benchmark for Robotic Manipulation
Santiago Bou Betran, Danica Kragic
Federated LearningRobotic IntelligenceBenchmark
🎯 What it does: Proposes the FLAME benchmark for federated learning in distributed robotic manipulation tasks.
Flexible Electronic Device with Multifunctional Tactile Perception for Enhanced Robotic Interaction
Chenhao Mao, Yancheng Wang
Robotic Intelligence
🎯 What it does: Developed a flexible electronic device for multifunctional tactile sensing to enable robot-human interaction; integrated the device into a robot interaction system to simultaneously measure force, angle, and sliding distance;
Flipping Manipulation with a Two-Fingered Parallel-Jaw Gripper
Wenxi Liao, Xin Jiang
OptimizationRobotic Intelligence
🎯 What it does: Proposed a systematic flipping strategy for parallel grippers in structured environments.
FlipWalker: Jacob’s Ladder toy-inspired robot for locomotion across diverse, complex terrain
Diancheng Li, Matthew A. Robertson
Robotic Intelligence
🎯 What it does: Designed an underactuated robot named FlipWalker inspired by Jacob’s Ladder, capable of moving forward by rolling over complex terrains.
FLOAT Drone: A Fully-actuated Coaxial Aerial Robot for Close-Proximity Operations
Junxiao Lin, Fei Gao
Robotic Intelligence
🎯 What it does: Designed and implemented a fully actuated coaxial twin-rotor UAV—FLOAT Drone—for close-range operations.
Floorplan-SLAM: A Real-Time, High-Accuracy, and Long-Term Multi-Session Point-Plane SLAM for Efficient Floorplan Reconstruction
Haolin Wang, Yihong Wu
OptimizationComputational EfficiencySimultaneous Localization and MappingImagePoint Cloud
🎯 What it does: Proposes Floorplan-SLAM, a real-time, high-precision long-term plane reconstruction framework that tightly integrates floor plane reconstruction into a multi-session SLAM system, achieved using only a stereo camera;
FloPE: Flower Pose Estimation for Precision Pollination
Rashik Shrestha, Yu Gu
Data SynthesisPose EstimationKnowledge DistillationRobotic IntelligenceGaussian SplattingImageAgriculture Related
🎯 What it does: Proposes FloPE, a real-time flower pose estimation framework for computationally constrained robotic pollination systems.
Flow-Aware Navigation of Magnetic Micro-Robots in Complex Fluids via PINN-Based Prediction
Yongyi Jia, Xiang Li
Robotic IntelligenceConvolutional Neural NetworkPhysics Related
🎯 What it does: Proposed a flow-aware navigation and control strategy for magnetic microrobots, utilizing PI-UNet to improve fluid velocity prediction and integrating it into A* path planning and control schemes
FlowMP: Learning Motion Fields for Robot Planning with Conditional Flow Matching
K. Nguyen, Minh Nhat Vu
Robotic IntelligenceFlow-based Model
🎯 What it does: By extending the flow matching method to capture second-order trajectory dynamics, learning a motion field incorporating acceleration information, directly mapping a simple prior distribution to smooth, executable robot trajectories.
FlowNav: Combining Flow Matching and Depth Priors for Efficient Navigation
Samiran Gode, Wolfram Burgard
Depth EstimationRobotic IntelligenceFlow-based Model
🎯 What it does: Proposes FlowNav, a robot navigation method that combines Conditional Flow Matching with depth prior.
FlowPlan: Zero-Shot Task Planning with LLM Flow Engineering for Robotic Instruction Following
Zijun Lin, Hong Zhang
Robotic IntelligenceLarge Language ModelText
🎯 What it does: Propose FlowPlan, a multi-stage LLM workflow for zero-shot robot instruction following task planning.
Flying on Point Clouds with Reinforcement Learning
Guangtong Xu, Fei Gao
Representation LearningRobotic IntelligenceReinforcement LearningPoint Cloud
🎯 What it does: Combining onboard 3D LiDAR and simulation-to-real reinforcement learning to achieve autonomous drone flight in complex environments.
FOCI: Trajectory Optimization on Gaussian Splats
Mario Gomez Andreu, Marco Hutter
OptimizationRobotic IntelligenceGaussian SplattingPoint Cloud
🎯 What it does: Proposed a FOCI algorithm that directly optimizes the robot's trajectory on 3D Gaussian Splatting
Focus Bug: Learning Environmental Awareness for Efficient Mapless Navigation
Charles Dansereau, Gabriela Nicolescu
Autonomous DrivingComputational EfficiencyReinforcement LearningPoint Cloud
🎯 What it does: Propose the Focus Bug algorithm, which selects necessary sensor data through reinforcement learning and combines it with classical mapless navigation methods to achieve mapless navigation with extremely low computational load.
Focusing on Projection-Stable Patch: Cross-View Localization with Geometric-Semantic Alignment
Riyu Qin, Xia Yuan
Pose EstimationAutonomous DrivingImagePoint Cloud
🎯 What it does: Propose a new feature alignment strategy that combines the Perspective-Driven Attention Fusion (PDAF) module with the Projection-Stable Patch-Guided Pose Optimizer (PSPG) for cross-perspective (ground-to-satellite) geolocation, addressing occlusion and distortion caused by perspective changes.
FoldPath: End-to-End Object-Centric Motion Generation via Modulated Implicit Paths
Paolo Rabino, Tatiana Tommasi
GenerationRobotic Intelligence
🎯 What it does: Proposed FoldPath, an end-to-end neural field method for object-centric motion generation (OCMG).
Force Aware Branch Manipulation To Assist Agricultural Tasks
M. Rijal, Yu Gu
Robotic IntelligenceAgriculture Related
🎯 What it does: Developed a method for safely manipulating branches to assist in agricultural tasks.
Force-Sensor-free Contact Estimation for Lower Limb Exoskeleton Robots Based on Probabilistic Modeling and Fusion
Weigen Ye, Hong Cheng
Robotic IntelligenceTime Series
🎯 What it does: Propose a foot contact estimation method without force sensors
FPGA Hardware Neural Control of CartPole and F1TENTH Race Car
Marcin Paluch, Tobi Delbruck
Autonomous DrivingRobotic IntelligenceSupervised Fine-Tuning
🎯 What it does: Developed an FPGA-based neural controller for high-speed control in robotic systems such as cartpole and F1TENTH racing cars, demonstrating its ability to achieve kilohertz-level control rates.
FRANC: Feeding Robot for Adaptive Needs and Personalized Care
J.-Anne Yow, Wei Tech Ang
Robotic IntelligenceTransformerLarge Language ModelPrompt Engineering
🎯 What it does: Developed the FRANC framework, leveraging large language models and decomposed prompting strategies to dynamically adjust bite sequences, acquisition, and transfer parameters during the robot's feeding process, achieving cross-phase iterative correction;
Free-form language-based robotic reasoning and grasping
Runyu Jiao, Fabio Poiesi
Object DetectionData SynthesisRobotic IntelligenceVision Language ModelMultimodality
🎯 What it does: The study investigates using pre-trained vision-language models for robot grasping based on free-form language instructions under zero-shot conditions, and proposes the FreeGrasp method.
From 2D Underwater Imaging Sonar Data to 3D Plane Extraction
António J. Oliveira, N. Cruz
Image
🎯 What it does: 3D plane extraction using 2D imaging sonar scanning
From Learning to Mastery: Achieving Safe and Efficient Real-World Autonomous Driving with Human-in-the-Loop Reinforcement Learning
Zeqiao Li, Z. Zuo
Autonomous DrivingReinforcement Learning from Human FeedbackReinforcement Learning
🎯 What it does: Proposed a reward-agnostic active human-in-the-loop learning method called H-DSAC to achieve safe and efficient real-world autonomous driving;
From Monocular Vision to Autonomous Action: Guiding Tumor Resection via 3D Reconstruction
Ayberk Acar, J. Wu
SegmentationRobotic IntelligenceImagePoint CloudBiomedical Data
🎯 What it does: This study proposes a 3D reconstruction pipeline that uses only RGB images to generate segmented point clouds of the target anatomy, thereby guiding automated navigation for tumor resection surgery.
From Satellite to Street: Semantic and Depth Information for Enhanced Geo-Localization
Yilong Zhu, Shaojie Shen
Pose EstimationDepth EstimationTransformerImage
🎯 What it does: Propose a localization method that combines perspective images and satellite images, using depth and semantic information extracted from monocular images for cross-view projection to achieve three degrees of freedom (3-DoF) precise pose estimation.
Frontier Shepherding: A Bio-inspired Multi-robot Framework for Large-Scale Exploration
John Lewis, Pedro U. Lima
Robotic Intelligence
🎯 What it does: Proposed and verified a multi-robot frontier exploration framework called Frontier Shepherding (FroShe) based on shepherd behavior for large-scale environment exploration.
Frozen Triumph: Lessons from GARMI’s Bimanual Trophy Handover at the Kandahar Ski World Cup – Shaping Current Research Directions
Mario Tröbinger (Garmi), Sami Haddadin (Garmi)
Robotic Intelligence
🎯 What it does: Completed the two-handed trophy handover demonstration of GARMI in extreme cold environments, and extended the previous framework to achieve real-time trophy quality estimation, while investigating the impact of base tilt and temperature variations on quality estimation and control performance.
FruitNeRF++: A Generalized Multi-Fruit Counting Method Utilizing Contrastive Learning and Neural Radiance Fields
Lukas Meyer, Marc Stamminger
Object DetectionNeural Radiance FieldContrastive LearningImagePoint CloudAgriculture Related
🎯 What it does: Proposed FruitNeRF++, a multi-fruit counting method combining contrastive learning and neural radiance fields (NeRF), capable of counting fruits in unstructured orchard images.
FSDP: Fast and Safe Data-Driven Overtaking Trajectory Planning for Head-to-Head Autonomous Racing Competitions
Cheng Hu (Zhejiang University), Lei Xie (Zhejiang University)
Autonomous DrivingOptimization
🎯 What it does: Propose Fast and Safe Data-Driven Planner for overtaking trajectory planning in autonomous racing.
FSGlove: An Inertial-Based Hand Tracking System with Shape-Aware Calibration
Yutong Li, Cewu Lu
Pose EstimationOptimizationTime Series
🎯 What it does: Proposed the FSGlove system, which utilizes inertial measurement units (IMUs) to achieve 48 degrees of freedom (DOF) hand motion capture, and employs the DiffHCal method for personalized hand shape reconstruction.
Full Pose Tracking via Robust Control for Over-Actuated Multirotors
Mohamad Hachem, Murat Bronz
OptimizationRobotic Intelligence
🎯 What it does: Designed a robust cascade control architecture to achieve full attitude tracking for overloaded multirotors.
Fully Autonomous Dual Arm Aerial Delivery Robot for Intralogistics: the euROBIN Nancy Competition Flight Dataset
A. Suárez, Aníbal Ollero
Robotic IntelligenceSimultaneous Localization and MappingBenchmark
🎯 What it does: Designed, developed, and verified a dual-arm drone system capable of autonomously performing mapping, localization, planning, and grasping packages. The system supports task execution in logistics environments with supply points, delivery points, labeled packages, and obstacles, and can generate task plans through voice commands.
FunGraph: Functionality Aware 3D Scene Graphs for Language-Prompted Scene Interaction
Dennis Rotondi, K. Arras
Object DetectionSegmentationRobotic IntelligenceVision-Language-Action ModelImageGraph
🎯 What it does: Develop a function-aware 3D scene graph to identify the location and usage of functional interaction elements, and perform fine-grained detection and storage of function-related components beneficial for robot interaction.
FUSE: Label-Free Image-Event Joint Monocular Depth Estimation via Frequency-Decoupled Alignment and Degradation-Robust Fusion
Pihai Sun, Xianming Liu
Depth EstimationTransformerMultimodality
🎯 What it does: Proposed a frequency-decoupled unsupervised image-event joint monocular depth estimation method called FUSE.
Fusion Scene Context: Robust and Efficient LiDAR Place Recognition Across Season
Fengkui Cao, Xieyuanli Chen
RecognitionAutonomous DrivingPoint Cloud
🎯 What it does: Proposed a compact fusion view image representation based on LiDAR point clouds to extract multi-view structural information, generate a global descriptor using texture features, and design regional features to adapt to seasonal changes.
G3 CN: Gaussian Topology Refinement Gated Graph Convolutional Network for Skeleton-Based Action Recognition
Haiqing Ren, Libo Zhang
RecognitionGraph Neural NetworkGraph
🎯 What it does: Proposes the Gaussian Topology Refinement Gated Graph Convolution (G3CN) method to enhance the discriminative ability for ambiguous actions in skeleton-based action recognition.
GABRIL: Gaze-Based Regularization for Mitigating Causal Confusion in Imitation Learning
Amin Banayeeanzade, Erdem Biyik
Autonomous DrivingSequential
🎯 What it does: Regularization learning using human gaze data to guide behavior cloning models to focus on causal-related features, thereby alleviating causal confusion.
GACL: Grounded Adaptive Curriculum Learning with Active Task and Performance Monitoring
Linji Wang, Xuesu Xiao
Robotic Intelligence
🎯 What it does: Proposed an adaptive curriculum learning framework GACL specifically designed for robot tasks, aiming to automatically generate task sequences that match the robot's current capabilities.
Gait in Eight: Efficient On-Robot Learning for Omnidirectional Quadruped Locomotion
Nico Bohlinger, Jan Peters
Robotic IntelligenceReinforcement Learning
🎯 What it does: Developed an efficient reinforcement learning framework for robots, enabling quadrupedal robots to learn full-directional locomotion within just 8 minutes of original real-time training.
GAT-Grasp: Gesture-Driven Affordance Transfer for Task-Aware Robotic Grasping
Ruixiang Wang, Kui Jia
Robotic IntelligenceVideoRetrieval-Augmented Generation
🎯 What it does: Proposed the GAT-Grasp framework, which utilizes human gestures to directly drive the generation of task-specific grasping poses, enabling robots to achieve precise grasping of diverse objects.
Gaussian Splatting with Reflectance Regularization for Endoscopic Scene Reconstruction
Chengkun Li, Q. Dou
Gaussian SplattingBiomedical Data
🎯 What it does: Propose a Gaussian Splatting-based endoscopic scene reconstruction framework with reflectance regularization to enhance geometric quality.
GaussianGraph: 3D Gaussian-Based Scene Graph Generation for Open-World Scene Understanding
Xihan Wang, Mengyin Fu
GenerationVision Language ModelGaussian Splatting
🎯 What it does: Propose the GaussianGraph framework, which combines 3D Gaussian Splatting with adaptive semantic clustering and scene graph generation to enhance 3D scene understanding and object localization capabilities.
GaussianPU: Color Point Cloud Upsampling via 3D Gaussian Splatting
Zixuan Guo, Fei Yu
Super ResolutionGaussian SplattingPoint Cloud
🎯 What it does: Proposed the GaussianPU framework, combining 3D Gaussian Splatting with a dual-scale rendering image recovery network to achieve high-quality upsampling of sparse colored point clouds.
Gaze-Guided 3D Hand Motion Prediction for Detecting Intent in Egocentric Grasping Tasks
Yufei He, Arno H. A. Stienen
Pose EstimationRobotic IntelligenceTransformerAuto EncoderVideoSequential
🎯 What it does: This paper proposes a 3D hand motion prediction method that integrates gaze information, historical hand motion sequences, and environmental object data to detect human intent in grasping tasks from the perspective of a head-mounted camera.
Gaze-Guided Task Decomposition for Imitation Learning in Robotic Manipulation
Ryo Takizawa, Y. Kuniyoshi
Robotic Intelligence
🎯 What it does: Decompose object manipulation tasks demonstrated by humans into subtasks using gaze transitions, enabling skill reuse and combination in imitation learning.
GazeTarget360: Towards Gaze Target Estimation in 360-Degree for Robot Perception
Zhu Dai, Chen Li
Robotic IntelligenceImage
🎯 What it does: Proposed a system called GazeTarget360 for estimating human gaze targets from panoramic scenes in images, integrating an eye contact detector, a pre-trained visual encoder, and a multi-scale fusion decoder.
GDM-Net++: Multi-robot 2D and 3D Gas Distribution Mapping Via Deep Q-Learning and Gaussian Process Regression
Iliya Kulbaka, Swapnoneel Roy
Robotic IntelligenceReinforcement LearningPoint Cloud
🎯 What it does: Proposed a multi-robot gas distribution mapping framework named GDM-Net++, combining Voronoi partitioning, deep Q-learning, and Gaussian process regression to achieve gas concentration mapping in 2D/3D areas.
GDTS: Goal-Guided Diffusion Model with Tree Sampling for Multi-Modal Pedestrian Trajectory Prediction
Ge Sun, Jun-Qi Ma
Autonomous DrivingDiffusion modelSequential
🎯 What it does: Proposes GDTS, a goal-guided diffusion model combined with tree sampling for multimodal pedestrian trajectory prediction.
GEAR: Gaze-Enabled Human-Robot Collaborative Assembly
Asad Ali Shahid, L. Roveda
Robotic IntelligenceImage
🎯 What it does: Developed a collaborative robot system called GEAR based on eye-tracking technology, which assists workers in grasping parts during assembly tasks and receives high-level instructions from workers; meanwhile, it was compared with traditional touchscreen interaction methods.
Generalizable and Actionable Part Detection and Manipulation with SAM-rectified Segmentation and Iterative Pose Refinement
Sucheng Qian, Cewu Lu
Object DetectionSegmentationPose EstimationRobotic IntelligenceTransformerSupervised Fine-TuningRectified FlowImage
🎯 What it does: Proposed the SAMIR framework for cross-category GAPart detection and manipulation.
Generalizable Category-Level Topological Structure Learning for Clothing Recognition in Robotic Grasping
Xin-Hai Zhu, Yixing Gao
RecognitionRobotic Intelligence
🎯 What it does: Proposes a topological structure representation and optimization strategy for category-level clothing structure feature learning, and constructs a multi-clothing classification framework based on multiple mask generation, capable of identifying clothing regions in scenes; achieves generalization to unseen clothing through learned structural features; simultaneously proposes fabric-specific grasping position estimation methods and develops a corresponding robotic grasping system that can select and grasp specified clothing according to user instructions.