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Generalization in Dexterous Manipulation via Geometry-Aware Multi-Task LearningPreprint

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MetaGraspNet: A Large-Scale Benchmark Dataset for Scene-Aware Ambidextrous Bin Picking via Physics-based Metaverse Synthesis

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FingerSLAM: Closed-loop Unknown Object Localization and Reconstruction from Visuo-tactile Feedback

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Integrating Context into Artificial Intelligence: Research from the Robotics Collaborative Technology Alliance

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Domain adversarial transfer for cross-domain and task-constrained grasp pose detection

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Multimodal Anomaly Detection based on Deep Auto-Encoder for Object Slip Perception of Mobile Manipulation Robots

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Exploiting Three-Dimensional Gaze Tracking for Action Recognition During Bimanual Manipulation to Enhance Human–Robot Collaboration

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Rigid-Soft Interactive Learning for Robust Grasping

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A Software Architecture for Service Robots Manipulating Objects in Human Environments

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Predicting Stable Configurations for Semantic Placement of Novel ObjectsPreprint

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WFH-VR: Teleoperating a Robot Arm to set a Dining Table across the Globe via Virtual Reality

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UPG: 3D vision-based prediction framework for robotic grasping in multi-object scenes

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DexTouch: Learning to Seek and Manipulate Objects With Tactile Dexterity

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Model Predictive Control for Fluid Human-to-Robot Handovers

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GP2C: Geometric Projection Parameter Consensus for Joint 3D Pose and Focal Length Estimation in the Wild

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Skill Learning by Autonomous Robotic Playing Using Active Learning and Exploratory Behavior Composition

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A Multi-Hypothesis Approach to Pose Ambiguity in Object-Based SLAM

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Learning Object Relations with Graph Neural Networks for Target-Driven Grasping in Dense Clutter

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Performance measures to benchmark the grasping, manipulation, and assembly of deformable objects typical to manufacturing applications

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Train Offline, Test Online: A Real Robot Learning Benchmark

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DGECN++: A Depth-Guided Edge Convolutional Network for End-to-End 6D Pose Estimation via Attention Mechanism

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From Single 2D Depth Image to Gripper 6D Pose Estimation: A Fast and Robust Algorithm for Grabbing Objects in Cluttered Scenes

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Data-Driven Object Pose Estimation in a Practical Bin-Picking Application

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Synthesizing Dexterous Nonprehensile Pregrasp for Ungraspable Objects

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Collision-aware In-hand 6D Object Pose Estimation using Multiple Vision-based Tactile Sensors

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EARL: Eye-on-Hand Reinforcement Learner for Dynamic Grasping with Active Pose Estimation

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Early or Late Fusion Matters: Efficient RGB-D Fusion in Vision Transformers for 3D Object Recognition

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Rubik's Cube Handling Using a High-Speed Multi-Fingered Hand and a High-Speed Vision System

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Predicting Pushing Action Effects on Spatial Object Relations by Learning Internal Prediction Models

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Hierarchical Tactile-Based Control Decomposition of Dexterous In-Hand Manipulation Tasks

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A Miniaturised Neuromorphic Tactile Sensor integrated with an Anthropomorphic Robot Hand

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Freehand Grasping: An Analysis of Grasping for Docking Tasks in Virtual Reality

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Stability-driven Contact Reconstruction From Monocular Color Images

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Toward Sim-to-Real Directional Semantic Grasping

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6-D Object Pose Estimation Using Multiscale Point Cloud Transformer

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ViHOPE: Visuotactile In-Hand Object 6D Pose Estimation With Shape Completion

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Dexterous manipulation of construction tools using anthropomorphic robotic hand

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Fast and Comfortable Robot-to-Human Handover for Mobile Cooperation Robot System

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ReorientDiff: Diffusion Model based Reorientation for Object Manipulation

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Put Myself in Your Shoes: Lifting the Egocentric Perspective from Exocentric Videos

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MultiGripperGrasp: A Dataset for Robotic Grasping from Parallel Jaw Grippers to Dexterous Hands

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Tactile-Based In-Hand Object Pose Estimation

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SHOP-VRB: A Visual Reasoning Benchmark for Object Perception

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Attribute-Based Robotic Grasping with One-Grasp Adaptation

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Generalization Guarantees for Imitation Learning

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Active Learning of Probabilistic Movement Primitives

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BiLuNetICP: A Deep Neural Network for Object Semantic Segmentation and 6D Pose Recognition

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DA$^{2}$ Dataset: Toward Dexterity-Aware Dual-Arm Grasping

Zhai, G., Zheng, Y., Xu, Z., Kong, X., Liu, Y., Busam, B., Ren, Y., Navab, N., & Zhang, Z. (2022) · IEEE Robotics and Automation Letters · doi:10.1109/lra.2022.3189959 · Cited by 16

Fast and Comfortable Interactive Robot-to-Human Object Handover

Meng, C., Zhang, T., & Lam, T. L. (2022) · IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) · doi:10.1109/iros47612.2022.9981484 · Cited by 16

DCL-Net: Deep Correspondence Learning Network for 6D Pose Estimation

Li, H., Lin, J., & Jia, K. (2022) · Lecture notes in computer science · doi:10.1007/978-3-031-20077-9_22 · Cited by 16

Planning for Multi-Object Manipulation with Graph Neural Network Relational Classifiers

Huang, Y., Conkey, A., & Hermans, T. (2023) · Proceedings - IEEE International Conference on Robotics and Automation/Proceedings · doi:10.1109/icra48891.2023.10161204 · Cited by 16

Inferring Occluded Geometry Improves Performance When Retrieving an Object from Dense Clutter

Price, A., Jin, L., & Berenson, D. (2022) · Springer proceedings in advanced robotics · doi:10.1007/978-3-030-95459-8_23 · Cited by 16

Fusion++: Volumetric Object-Level SLAMPreprint

McCormac, J., Clark, R., Bloesch, M., Davison, A. J., & Leutenegger, S. (2018) · arXiv (Cornell University) · doi:10.48550/arxiv.1808.08378 · Cited by 16

KVNet: An iterative 3D keypoints voting network for real-time 6-DoF object pose estimation

Wang, F., Zhang, X., Chen, T., Shen, Z., Liu, S., & He, Z. (2023) · Neurocomputing · doi:10.1016/j.neucom.2023.01.036 · Cited by 15

Fed-HANet: Federated Visual Grasping Learning for Human Robot Handovers

Huang, C.-I., Huang, Y.-Y., Liu, J.-X., Ko, Y.-T., Wang, H., Chiang, K., & Yu, L.-F. (2023) · IEEE Robotics and Automation Letters · doi:10.1109/lra.2023.3270745 · Cited by 15

A Comprehensive User Study on Augmented Reality-Based Data Collection Interfaces for Robot Learning

Jiang, X., Mattes, P., Jia, X., Schreiber, N., Neumann, G. M., & Lioutikov, R. (2024) · ACM/IEEE International Conference on Human-Robot Interaction (HRI) · doi:10.1145/3610977.3634995 · Cited by 15

Telemanipulation via Virtual Reality Interfaces with Enhanced Environment Models

Wonsick, M., Keleştemur, T., Alt, S., & Padır, T. (2021) · IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) · doi:10.1109/iros51168.2021.9636005 · Cited by 15

PANet: A Pixel-Level Attention Network for 6D Pose Estimation With Embedding Vector Features

Xie, T., Wang, K., Li, R., Tang, X., & Zhao, L. (2021) · IEEE Robotics and Automation Letters · doi:10.1109/lra.2021.3136873 · Cited by 15

MM-Spatial: Exploring 3D Spatial Understanding in Multimodal LLMs

Daxberger, E., Wenzel, N., Griffiths, D., Gang, H., Lazarow, J., Kohavi, G., Kang, K., Eichner, M. L., Yang, Y., Dehghan, A., et al. (2025) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv51701.2025.00694 · Cited by 47

Automatic “Ground Truth” Annotation and Industrial Workpiece Dataset Generation for Deep Learning

Liu, F., & Wang, Z.-Y. (2020) · Machine Intelligence Research · doi:10.1007/s11633-020-1221-8 · Cited by 14

Optimal Order Pick-and-Place of Objects in Cluttered Scene by a Mobile Manipulator

Wang, F., Guadarrama-Olvera, J. R., & Cheng, G. (2021) · IEEE Robotics and Automation Letters · doi:10.1109/lra.2021.3093021 · Cited by 14

Robotic picking in dense clutter via domain invariant learning from synthetic dense cluttered rendering

Liu, W., Wang, W., You, Y., Xue, T., Pan, Z., Qi, J., & Hu, J. (2021) · Robotics and Autonomous Systems · doi:10.1016/j.robot.2021.103901 · Cited by 14

Measuring Object Rotation via Visuo-Tactile Segmentation of Grasping Region

Castaño-Amorós, J., & Gil, P. (2023) · IEEE Robotics and Automation Letters · doi:10.1109/lra.2023.3285471 · Cited by 14

NEWTON: Are Large Language Models Capable of Physical Reasoning?

Wang, Y., Duan, J., Fox, D., & Srinivasa, S. S. (2023) · Findings of the Association for Computational Linguistics: EMNLP (Findings of EMNLP) · doi:10.18653/v1/2023.findings-emnlp.652 · Cited by 52

FRoGGeR: Fast Robust Grasp Generation via the Min-Weight Metric

Li, A. H., Culbertson, P., Burdick, J. W., & Ames, A. D. (2023) · IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) · doi:10.1109/iros55552.2023.10341806 · Cited by 14

In-Hand Manipulation With a Simple Belted Parallel-Jaw Gripper

Xie, G., Holladay, R., Chin, L., & Rus, D. L. (2023) · IEEE Robotics and Automation Letters · doi:10.1109/lra.2023.3346750 · Cited by 14

Cook2LTL: Translating Cooking Recipes to LTL Formulae using Large Language Models

Mavrogiannis, A., Mavrogiannis, C., & Aloimonos, Y. (2024) · Proceedings - IEEE International Conference on Robotics and Automation/Proceedings · doi:10.1109/icra57147.2024.10611086 · Cited by 19

Spatially distributed biomimetic compliance enables robust anthropomorphic robotic manipulation

Junge, K., & Hughes, J. (2025) · Communications Engineering · doi:10.1038/s44172-025-00407-4 · Cited by 19

Scalable Tactile Sensing for an Omni-adaptive Soft Robot Finger

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Grasping as Inference: Reactive Grasping in Heavily Cluttered Environment

Son, D. (2022) · IEEE Robotics and Automation Letters · doi:10.1109/lra.2022.3181735 · Cited by 14

Triangulate geometric constraint combined with visual-flow fusion network for accurate 6DoF pose estimation

Jiang, Z., Wang, X., Huang, X., & Li, H. (2021) · Image and Vision Computing · doi:10.1016/j.imavis.2021.104127 · Cited by 14

Skill Learning by Autonomous Robotic Playing using Active Learning and CreativityPreprint

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In-Hand Object Stabilization by Independent Finger ControlPreprint

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VLATest: Testing and Evaluating Vision-Language-Action Models for Robotic Manipulation

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Visual-tactile pretraining and online multitask learning for humanlike manipulation dexterity

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A Hybrid, Encompassing, Three-Fingered Robotic Gripper Combining Pneumatic Telescopic Mechanisms and Rigid Claws

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HandBooster: Boosting 3D Hand-Mesh Reconstruction by Conditional Synthesis and Sampling of Hand-Object Interactions

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Computational design of passive grippers

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ProgressLabeller: Visual Data Stream Annotation for Training Object-Centric 3D Perception

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Certifiable Object Pose Estimation: Foundations, Learning Models, and Self-Training

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Digital Twin Tracking Dataset (DTTD): A New RGB+Depth 3D Dataset for Longer-Range Object Tracking Applications

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Benchmarking in Manipulation Research: Using the Yale-CMU-Berkeley Object and Model Set

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Benchmarking in Manipulation Research: The YCB Object and Model Set and Benchmarking ProtocolsPreprint

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SceneReplica: Benchmarking Real-World Robot Manipulation by Creating Replicable Scenes

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DexYCB: A Benchmark for Capturing Hand Grasping of Objects

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