The YCB object and Model set: Towards common benchmarks for manipulation research

ROS: an open-source Robot Operating System

Quigley, M. (2009) · Proceedings - IEEE International Conference on Robotics and Automation/Proceedings · Cited by 8,729

Surface simplification using quadric error metrics

Garland, M., & Heckbert, P. S. (1997) · ACM SIGGRAPH Annual Conference on Computer Graphics and Interactive Techniques (SIGGRAPH) · doi:10.1145/258734.258849 · Cited by 3,445

Adult Norms for the Box and Block Test of Manual Dexterity

Mathiowetz, V. G., Volland, G., Kashman, N., & Weber, K. (1985) · American Journal of Occupational Therapy · doi:10.5014/ajot.39.6.386 · Cited by 2,105

The Open Motion Planning Library

Sucan, I. A., Moll, M., & Kavraki, L. E. (2012) · IEEE Robotics & Automation Magazine · doi:10.1109/mra.2012.2205651 · Cited by 1,616

The princeton shape benchmark

Shilane, P., Min, P., Kazhdan, M., & Funkhouser, T. A. (2004) · IEEE International Conference on Shape Modeling and Applications · doi:10.1109/smi.2004.1314504 · Cited by 1,461

CHOMP: Gradient optimization techniques for efficient motion planning

Ratliff, N., Zucker, M., Bagnell, J. A., & Srinivasa, S. S. (2009) · Proceedings - IEEE International Conference on Robotics and Automation/Proceedings · doi:10.1109/robot.2009.5152817 · Cited by 1,052

Adult Norms for the Nine Hole Peg Test of Finger Dexterity

Mathiowetz, V. G., Weber, K., Kashman, N., & Volland, G. (1985) · The Occupational Therapy Journal of Research · doi:10.1177/153944928500500102 · Cited by 973

Robotic Grasping of Novel Objects using Vision

Saxena, A., Driemeyer, J., & Ng, A. Y. (2008) · The International Journal of Robotics Research · doi:10.1177/0278364907087172 · Cited by 950

MoveIt! [ROS Topics]

Chitta, S., Sucan, I. A., & Cousins, S. (2012) · IEEE Robotics & Automation Magazine · doi:10.1109/mra.2011.2181749 · Cited by 475

OpenRAVE: A Planning Architecture for Autonomous Robotics

Diankov, R., & Kuffner, J. (2008) · Cited by 381

Enhancing Antipodal Grasping Modalities in Complex Environments Through Learning and Analytical Fusion

Bui, T. H., Son, Y. G., Hong, J., Kim, Y. H., & Choi, H. R. (2024) · IEEE Transactions on Automation Science and Engineering · doi:10.1109/tase.2024.3512005 · Cited by 2

Evaluating a Movable Palm in Caging Inspired Grasping using a Reinforcement Learning-based Approach

Beddow, L., Wurdemann, H. A., & Kanoulas, D. (2024) · IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) · doi:10.1109/iros58592.2024.10801702 · Cited by 2

Development and Functional Evaluation of The PrHand V3 Soft-Robotics Prosthetic Hand

Ramos, O., Arco, L. D., Múnera, M., Robledo, J., Moazen, M., Wurdemann, H. A., & Cifuentes, C. A. (2024) · IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) · doi:10.1109/iros58592.2024.10801454 · Cited by 2

Gravity-aware Grasp Generation with Implicit Grasp Mode Selection for Underactuated Hands

Ko, T., Ikeda, T., Stewart, T., Lee, R., & Nishiwaki, K. (2024) · IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) · doi:10.1109/iros58592.2024.10801600 · Cited by 2

A workpiece grasp detection method based on 3D object detection

Li, H., Duan, L., Wang, Q., Zhang, Y., & Ye, B. (2025) · Industrial Robot the international journal of robotics research and application · doi:10.1108/ir-07-2024-0333 · Cited by 2

UDI-3DVT: A Novel Network for 3-D Reconstruction via Uncertainty-Driven Sampling and Incremental Visual-Tactile Fusion

Zhang, C., Zhang, S., Li, Y., Chen, W., Gao, G., & Wu, P. (2025) · IEEE Sensors Journal · doi:10.1109/jsen.2025.3531929 · Cited by 2

Multiview Object Pose Estimation Using Viewpoint Weight Based on Shared Object Representation

Yabashi, K., & Tasaki, T. (2025) · Journal of Robotics and Mechatronics · doi:10.20965/jrm.2025.p0310 · Cited by 2

MultiTalk: Introspective and Extrospective Dialogue for Human-Environment-LLM Alignment

Devarakonda, V. N., Kaypak, A. U., Yuan, S., Krishnamurthy, P., Fang, Y., & Khorrami, F. (2024) · IEEE International Conference on Robotics and Automation · doi:10.1109/icra55743.2025.11128486 · Cited by 4

SynthRetailProduct3D (SyRePro3D): A Pipeline for Synthesis of 3D Retail Product Models with Domain Specific Details Based on Package Class Templates

Lindermayr, J., Odabaşı, Ç., Völk, M., Chen, Y., Bormann, R., & Huber, M. F. (2023) · Lecture notes in computer science · doi:10.1007/978-3-031-44137-0_20 · Cited by 2

Model based Reinforcement Learning for Robot Grasping Trajectory Generation

Xue, H., Wen, S., Yang, C., & Liu, H. (2019) · International Conference on Advanced Robotics and Mechatronics (ICARM) · doi:10.1109/icarm.2019.8834254 · Cited by 2

Robotic grasping in agile production

Sefat, A. M., Ahmad, S. B. S., Angleraud, A., Rahtu, E., & Pieters, R. (2022) · Elsevier eBooks · doi:10.1016/b978-0-32-385787-1.00021-x · Cited by 2

Learning Grasp Ability Enhancement Through Deep Shape Generation

Jiang, J., Xiao, X., Chen, F., & Li, M. (2022) · Lecture notes in computer science · doi:10.1007/978-3-031-13841-6_66 · Cited by 2

GRASPA-fying the Panda: Easily Deployable, Fully Reproducible Benchmarking of Grasp Planning Algorithms

Bottarel, F., Altobelli, A., Pattacini, U., & Natale, L. (2023) · IEEE Robotics & Automation Magazine · doi:10.1109/mra.2023.3256272 · Cited by 2

Ensemble of 6 DoF Pose estimation from state-of-the-art deep methods.

Merino, I., Azpiazu, J., Remazeilles, A., & Sierra, B. (2023) · Neurocomputing · doi:10.1016/j.neucom.2023.126270 · Cited by 2

An Effective Method for Minimizing Domain Gap in Sim2Real Object Recognition Using Domain Randomization

Ono, T., Suzuki, A., & Tamukoh, H. (2023) · Proceedings of International Conference on Artificial Life and Robotics · doi:10.5954/icarob.2023.os17-6 · Cited by 2

Local object crop collision network for efficient simulation of non-convex objects in GPU-based simulators

Son, D., & Kim, B. (2023) · Robotics: Science and Systems · doi:10.15607/rss.2023.xix.033 · Cited by 2

Canonical Plane Segmentation Without Annotating Pixel-Level Object Regions for Image Registration

Yoneda, S., Irie, G., & Nishiyama, M. (2024) · IEEE Access · doi:10.1109/access.2024.3373463 · Cited by 2

SlotGNN: Unsupervised Discovery of Multi-Object Representations and Visual Dynamics

Rezazadeh, A., Badithela, A., Desingh, K., & Choi, C. (2024) · Proceedings - IEEE International Conference on Robotics and Automation/Proceedings · doi:10.1109/icra57147.2024.10611588 · Cited by 2

YCB Benchmarking Project : Object Set, Data Set and Their Applications (特集 ロボットマニピュレーション革命)

Çallı, B., Singh, A., Bruce, J., Walsman, A., Konolige, K., Srinivasa, S. S., Abbeel, P., & Dollar, A. M. (2017) · Jidō seigyo/Jido seigyo · doi:10.11499/sicejl.56.792 · Cited by 2

Benchmarking Unsupervised Representation Learning for Continuous Control

Antonova, R., Devlin, S., Hofmann, K., & Kragić, D. (2020) · Cited by 2

3DOPE-DL: Accuracy Evaluation of a Deep Learning Framework for 3D Object Pose Estimation

Fabris, D. M., Sala, R., & Marco, T. (2020) · IEEE International Workshop on Metrology for Industry 4.0 & IoT (MetroInd4.0&IoT) · doi:10.1109/metroind4.0iot48571.2020.9138271 · Cited by 2

Comparative Evaluation of Approaches for Determination of Grasp Points on Objects, Manipulated by Robotic Systems

Iakovlev, R., Rubtsova, J., & Erashov, A. (2021) · Mekhatronika Avtomatizatsiya Upravlenie · doi:10.17587/mau.22.83-93 · Cited by 2

CATCH-919 Hand: Design of a 9-actuator 19-DOF Anthropomorphic Robotic HandPreprint

Zhang, Z., Han, T., Pan, J., & Wang, Z. (2018) · arXiv (Cornell University) · doi:10.48550/arxiv.1809.04290 · Cited by 2

Building 3D Object Models during Manipulation by Reconstruction-Aware Trajectory OptimizationPreprint

Huang, K., & Hermans, T. (2019) · arXiv (Cornell University) · doi:10.48550/arxiv.1905.03907 · Cited by 2

Recurrent Connectivity Aids Recognition of Partly Occluded ObjectsPreprint

Ernst, M., Triesch, J., & Burwick, T. (2019) · arXiv (Cornell University) · doi:10.48550/arxiv.1909.06175 · Cited by 2

OCID-Ref: A 3D Robotic Dataset with Embodied Language for Clutter Scene GroundingPreprint

Wang, K.-J., Liu, Y.-H., Su, H.-T., Wang, J.-W., Wang, Y.-S., Hsu, W. H., & Chen, W. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2103.07679 · Cited by 2

Robotic grasping in unstructured and dynamic environments

Morrison, D. (2021) · Queensland University of Technology · doi:10.5204/thesis.eprints.207886 · Cited by 2

Mpf6d: Masked Pyramid Fusion 6d Pose EstimationPreprint

Pereira, N. J. M., & Alexandre, L. A. (2022) · SSRN Electronic Journal · doi:10.2139/ssrn.4002123 · Cited by 2

Simulation to reality and back: A robot's guide to crossing the reality gap

Collins, J. T. (2022) · Queensland University of Technology · doi:10.5204/thesis.eprints.230537 · Cited by 2

Indoor Synthetic Data Generation: A Systematic ReviewPreprint

Schieber, H., Demir, K. C., Kleinbeck, C., Yang, S. H., & Roth, D. (2023) · SSRN Electronic Journal · doi:10.2139/ssrn.4528507 · Cited by 2

Transpose: 6d Object Pose Estimation with Geometry-Aware TransformerPreprint

Lin, X., Wang, D., Zhou, G., Liu, C., & Chen, Q. (2023) · SSRN Electronic Journal · doi:10.2139/ssrn.4670638 · Cited by 2

Zero-shot Pose Estimation Using Image Translation to Maintain Object Pose

Fujita, K., & Tasaki, T. (2023) · IEEJ Transactions on Electronics Information and Systems · doi:10.1541/ieejeiss.143.1113 · Cited by 1

Cross-domain fusion and embedded refinement-based 6D object pose tracking on textureless objects

Wang, J., Duan, G., Wang, Y., Yi, G., Dong, L., Wang, Z., Zhang, X., & Zhang, S. (2024) · Journal of Intelligent Manufacturing · doi:10.1007/s10845-023-02316-9 · Cited by 1

Embodied Runtime Monitoring of Learning-enabled Robot Perception Components

Nair, D., Panchangam, S., Olivares-Méndez, M. A., & Hochgeschwender, N. (2024) · IEEE International Conference on Automation Science and Engineering (CASE) · doi:10.1109/case59546.2024.10711844 · Cited by 1

BiCap: A novel bi-modal dataset of daily living dual-arm manipulation actions

Carmona, D., & Yu, H. (2024) · The International Journal of Robotics Research · doi:10.1177/02783649241290836 · Cited by 1

Incremental Object 6D Pose Estimation

Tian, L., Sorrenti, A., Pang, Y. L., Bellitto, G., Palazzo, S., Spampinato, C., & Oh, C. (2024) · Lecture notes in computer science · doi:10.1007/978-3-031-78395-1_22 · Cited by 1

Homologous multimodal fusion network with geometric constraint keypoints selection for 6D pose estimation

Guo, Y., Wang, F., & Ding, Q. (2024) · Expert Systems with Applications · doi:10.1016/j.eswa.2024.126022 · Cited by 1

Rotograb: Combining Biomimetic Hands with Industrial Grippers using a Rotating Thumb

Bersier, A., Leonforte, M., Vanetta, A., Wotke, S. L. A., Nappi, A., Zhou, Y., Oliani, S., Kübler, A. M., & Katzschmann, R. K. (2024) · IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) · doi:10.1109/iros58592.2024.10802788 · Cited by 1

dGrasp: NeRF-Informed implicit grasp policies with supervised optimization slopes

Sóti, G., Huang, X., Wurll, C., & Hein, B. (2025) · Robotics and Autonomous Systems · doi:10.1016/j.robot.2025.104921 · Cited by 1

InvSlotGNN: Unsupervised Discovery of Viewpoint Invariant Multiobject Representations and Visual Dynamics

Rezazadeh, A., Yu, H., Desingh, K., & Choi, C. (2025) · IEEE Transactions on Robotics · doi:10.1109/tro.2025.3543274 · Cited by 1

Discovering Conceptual Knowledge with Analytic Ontology Templates for Articulated Objects

Sun, J., Li, Y., Xu, L., Wei, J., Chai, L., & Lu, C. (2025) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v39i14.33609 · Cited by 1

Robotic Grasping of Common Objects: Focusing on Edge Detection for Improved Handling

Shiba, T., & Tamukoh, H. (2025) · Proceedings of International Conference on Artificial Life and Robotics · doi:10.5954/icarob.2025.os17-5 · Cited by 1

HILO: A Large-Scale Heterogeneous Object Dataset for Benchmarking Robotic Grasping Approaches

Song, X., Banerjee, S. K., & Banerjee, N. K. (2025) · International Conference on Automation, Robotics and Applications · doi:10.1109/icara64554.2025.10977572 · Cited by 1

HandBooster+: Boosting 3D Hand-Mesh Reconstruction From Data Synthesis to Progressive Multi-Hypothesis Aggregation

Xu, H., Li, H., Wang, Y., Liu, S., & Fu, C. (2025) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2025.3596986 · Cited by 3

Multi-Scale Balanced Grasp Pose Detection for Robotic Sorting of Diverse Consumer Goods

Gui, H., Pang, S., He, X., Zhai, X. M., Wang, N., Qiao, S., Yin, W., Ayouni, S., & Maddeh, M. (2025) · IEEE Transactions on Consumer Electronics · doi:10.1109/tce.2025.3596898 · Cited by 1

MuST: Multi-Head Skill Transformer for Long-Horizon Dexterous Manipulation with Skill Progress

Gao, K., Wang, F., Aduh, E., Randle, D., & Shi, J. (2025) · Proceedings - IEEE International Conference on Robotics and Automation/Proceedings · doi:10.1109/icra55743.2025.11127280 · Cited by 3

Prompt-Responsive Object Retrieval with Memory-Augmented Student-Teacher Learning

Mosbach, M., & Behnke, S. (2025) · Proceedings - IEEE International Conference on Robotics and Automation/Proceedings · doi:10.1109/icra55743.2025.11128512 · Cited by 1

WL-cobot: Collaborative Handover of Objects Using Preference-Based Grasp Postures with Human Hand Pose

Chen, Y.-Y., Lin, H., Lin, T.-R., & Lin, C. (2025) · International Conference on Advanced Robotics and Intelligent Systems (ARIS) · doi:10.1109/aris66143.2025.11163508 · Cited by 1

Learning from SAM: Harnessing a Foundation Model for Sim2Real Adaptation by Regularization

Bonani, M. E., Schwarz, M., & Behnke, S. (2025) · IEEE International Conference on Automation Science and Engineering (CASE) · doi:10.1109/case58245.2025.11163800 · Cited by 1

Leveraging CVAE for Joint Configuration Estimation of Multifingered Grippers from Point Cloud Data

Mérand, J., Meden, B., & Grossard, M. (2025) · IEEE International Conference on Automation Science and Engineering (CASE) · doi:10.1109/case58245.2025.11164060 · Cited by 1

GraspR: A Computational Model of Spatial User Preferences for Adaptive Grasp UI Design

Caetano, A., Luo, Y., Sharma, A., & Sra, M. (2025) · ACM Symposium on User Interface Software and Technology · doi:10.1145/3746059.3747744 · Cited by 3

Design Optimization and Evaluation of a Robotic Thumb with Anatomical Geometry and Passive Soft-Tissue Integration

Lenggenhager, D., Weirich, S., Wand, P., & Katzschmann, R. K. (2025) · IEEE-RAS International Conference on Humanoid Robots (Humanoids) · doi:10.1109/humanoids65713.2025.11203036 · Cited by 1

PCHands: PCA-Based Hand Pose Synergy Representation on Manipulators with $N$-DoF

Puang, E. Y., Ceola, F., Pasquale, G., & Natale, L. (2025) · IEEE-RAS International Conference on Humanoid Robots (Humanoids) · doi:10.1109/humanoids65713.2025.11203193 · Cited by 1

CCPose: high-precision six-dimensional pose estimation for industrial objects

Roovere, P. D., Daems, R., Croenen, J., & wyffels, F. (2025) · Machine Vision and Applications · doi:10.1007/s00138-025-01763-z · Cited by 1

Automating synthetic dataset generation for image-based 3D detection: a literature review

Schulz, P., Hempel, T., Jung, M., & Al-Hamadi, A. (2025) · Artificial Intelligence Review · doi:10.1007/s10462-025-11431-3 · Cited by 1

DG16M: A Large-Scale Dataset for Dual-Arm Grasping with Force-Optimized Grasps

Karim, M. F., Hashmi, M. S. J., Bollimuntha, S., Tapeti, M. R., Singh, G., Govindan, N., & Krishna, K. M. (2025) · IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) · doi:10.1109/iros60139.2025.11246970 · Cited by 1

LensDFF: Language-enhanced Sparse Feature Distillation for Efficient Few-Shot Dexterous Manipulation

Feng, Q., Knoll, A., Lema, D. S. M., Chen, Z., & Feng, J. (2025) · IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) · doi:10.1109/iros60139.2025.11247703 · Cited by 1

GRASPLAT: Enabling dexterous grasping through novel view synthesis

Bortolon, M., Duarte, N. F., Moreno, P., Poiesi, F., Santos-Victor, J., & Bue, A. D. (2025) · IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) · doi:10.1109/iros60139.2025.11246749 · Cited by 1

Neural Collision Detection for Constrained Grasp Pose Optimization in Cluttered Environments

Lin, L., Zhu, W., Zhuang, Y., Zheng, Q., & Yu, Y. (2025) · IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) · doi:10.1109/iros60139.2025.11246779 · Cited by 1

6-DoF Object Tracking with Event-based Optical Flow and Frames

Li, Z., Glover, A., Bartolozzi, C., & Natale, L. (2025) · IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) · doi:10.1109/iros60139.2025.11245865 · Cited by 1

Steel-reinforced Pneu-net based bioinspired soft claw: design, fabrication, and application

Chen, K., Hao, T., Ma, Y., Liu, S., & Wang, J. (2025) · International Journal of Intelligent Robotics and Applications · doi:10.1007/s41315-025-00510-x · Cited by 1

Slip detection for compliant robotic hands using inertial signals and deep learning

Cravetz, M., Vyas, P., Grimm, C. M., & Davidson, J. R. (2025) · Frontiers in Robotics and AI · doi:10.3389/frobt.2025.1698591 · Cited by 2

SimTac: A Physics-Based Simulator for Vision-Based Tactile Sensing with Biomorphic Structures

Zhang, X., Jiang, J., Chen, Z., Zhao, Y., Yang, T., Gomes, D. F., Wang, J., & Luo, S. (2026) · Cyborg and Bionic Systems · doi:10.34133/cbsystems.0510 · Cited by 1

TARGO and TARGO-Net: Benchmarking Target-Driven Object Grasping Under Occlusions

Xia, Y., Ding, R., Qin, Z., Zhan, G., Zhou, K., Yang, L., Dong, H., & Cremers, D. (2026) · International Journal of Computer Vision · doi:10.1007/s11263-025-02716-9 · Cited by 1

Geometry-Aware 6-DoF Grasp Learning From Stacked Point Clouds in Unstructured Scenes

Li, X., Zhang, Z., Zeng, Y., Shengjun, X. U., & Chen, I. M. (2026) · IEEE Robotics and Automation Letters · doi:10.1109/lra.2026.3678127 · Cited by 1

Single-Motor-Driven Robotic Hand With Multiple Grippers Using Gravity-Driven Torque-Path Switching Mechanism

Nishimura, T., Okatsu, H., & Watanabe, T. (2026) · IEEE Robotics and Automation Letters · doi:10.1109/lra.2026.3685935 · Cited by 1

SDT-6D: Fully Sparse Depth-Transformer for Staged End-to-End 6D Pose Estimation in Industrial Multi-View Bin Picking

Leuze, N., Hoh, M., Doğan, S., Peña, N. R., & Schoettl, A. (2026) · IEEE Winter Conference on Applications of Computer Vision · doi:10.1109/wacv61042.2026.00811 · Cited by 1

Learning‐Based Soft Robotic Grasping: Recent Progress and Remaining Challenges

Majumder, A., Konstantinova, J., Deacon, G., & Althoefer, K. A. (2026) · Advanced Robotics Research · doi:10.1002/adrr.70139 · Cited by 1

Semantic-Aware Active Perception for Next-Best-View Grasp Planning

Kweon, T. H., & Jeon, S. J. (2026) · International Journal of Precision Engineering and Manufacturing · doi:10.1007/s12541-026-01554-0 · Cited by 1

AutoSynPose: Automatic Generation of Synthetic Datasets for 6D Object Pose Estimation

Engemann, H., Du, S., Kallweit, S., Ning, C., & Anwar, S. (2020) · Frontiers in artificial intelligence and applications · doi:10.3233/faia200770 · Cited by 1

Shortened Color-Shape Descriptors for Point Cloud Classification from RGB-D Cameras

Seib, V., & Paulus, D. W. R. (2021) · IEEE International Conference on Autonomous Robot Systems and Competitions · doi:10.1109/icarsc52212.2021.9429775 · Cited by 1

A Novel Data Glove for Hand-object Pressure Capture

Zhao, X., & Wang, Y. (2021) · Youth Academic Annual Conference of Chinese Association of Automation (YAC) · doi:10.1109/yac53711.2021.9486590 · Cited by 1

Deep Segmentation Network Without Mask Image Supervision for 2D Image Registration

Yoneda, S., Irie, G., Shibata, T., Nishiyama, M., & Iwai, Y. (2022) · Communications in computer and information science · doi:10.1007/978-3-031-06381-7_16 · Cited by 1

Ω2: Optimal Hierarchical Planner for Object Search in Large Environments via Mobile Manipulation

Cho, Y., Shin, D., & Kim, B. (2022) · IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) · doi:10.1109/iros47612.2022.9981194 · Cited by 1

Learning of 6D Object Poses with Multi-task Point-wise Regression Deep Networks

Bai, K., Zhang, L., Chen, Z., & Zhang, J. (2022) · IEEE International Conference on Robotics and Biomimetics (ROBIO) · doi:10.1109/robio55434.2022.10011669 · Cited by 1

Exploiting Point-Wise Attention in 6D Object Pose Estimation Based on Bidirectional Prediction

Yang, Y., Wu, J., Wang, Y., Zhang, G., & Xiong, R. (2023) · IEEE Robotics and Automation Letters · doi:10.1109/lra.2023.3320015 · Cited by 1

LWOSNet: A Lightweight One-Shot Network Framework for Object Pose Estimation

Wang, C., Zang, X., Zhang, X., Cao, B., Zhou, L., Zhao, J., & Ang, M. H. (2023) · IEEE Sensors Journal · doi:10.1109/jsen.2023.3320697 · Cited by 1

Hybrid6D: A Dual-Stream Transformer-CNN Approach for 6D Object Pose Estimation from RGB-D Images *

Fu, S., Zhang, Q., Sun, X., Liu, M., & Fan, Z. (2023) · IEEE International Conference on Robotics and Biomimetics (ROBIO) · doi:10.1109/robio58561.2023.10354630 · Cited by 1

6D Grasp Pose Detection in Cluttered Environment from a Single-view

Li, E., Fu, Y., & Feng, H. (2023) · IEEE International Conference on Robotics and Biomimetics (ROBIO) · doi:10.1109/robio58561.2023.10354876 · Cited by 1

Digital Images – The Bread and Butter of Computer Vision

Nassif, J., Tekli, J., & Kamradt, M. (2024) · Springer eBooks · doi:10.1007/978-3-031-47560-3_5 · Cited by 2

Silhouette-Based 6D Object Pose Estimation

Cui, X., Li, N., Zhang, C., Zhang, Q., Feng, W., & Wan, L. (2024) · Lecture notes in computer science · doi:10.1007/978-981-97-2092-7_8 · Cited by 1

Generating Synthetic LiDAR Point Cloud Data for Object Detection Using the Unreal Game Engine

Eggert, M., Schade, M., Bröhl, F., & Moriz, A. (2024) · Lecture notes in computer science · doi:10.1007/978-3-031-61175-9_20 · Cited by 1

6-DoF Grasp Pose Evaluation and Optimization via Transfer Learning from NeRFs

Sóti, G., Huang, X., Wurll, C., & Hein, B. (2024) · Proceedings - IEEE International Conference on Robotics and Automation/Proceedings · doi:10.1109/icra57147.2024.10610402 · Cited by 1

Toward Standarization of Food Samples for Robotic Food Picking

Wada, K. (2024) · Journal of the Robotics Society of Japan · doi:10.7210/jrsj.42.646 · Cited by 1

DenseFusion-DA2: End-to-End Pose-Estimation Network Based on RGB-D Sensors and Multi-Channel Attention Mechanisms

Li, H., Wan, G., Li, X., Wang, C., Zhang, H., & Liu, B. (2024) · Sensors · doi:10.3390/s24206643 · Cited by 1

The TIP Benchmark: A Tactile Image-Based Psychophysics-Inspired Benchmark for Artificial Tactile Sensors

Liu, T., & Ward-Cherrier, B. (2024) · Lecture notes in computer science · doi:10.1007/978-3-031-70058-3_8 · Cited by 1

A Video Dataset of Everyday Life Grasps for the Training of Shared Control Operation Models for Myoelectric Prosthetic Hands

de Godoy, R. V., Guan, B., Dwivedi, A., Owen, M., & Liarokapis, M. V. (2024) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/embc53108.2024.10782638 · Cited by 1

A Deep Signed Directional Distance Function for Shape Representation

Zobeidi, E., & Atanasov, N. (2024) · IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) · doi:10.1109/iros58592.2024.10801713 · Cited by 1

RoboWrangler: Toward Rope-based Grasping for Mobile Manipulation

Friedrich, C., Gomez-Andreu, M., Métois, G., Shi, F., Hutter, M., & Baines, R. L. (2025) · IEEE International Conference on Soft Robotics (RoboSoft) · doi:10.1109/robosoft63089.2025.11020811 · Cited by 1

Robust contact-rich manipulation through implicit motor adaptation

Xue, T., Razmjoo, A., Shetty, S., & Calinon, S. (2025) · The International Journal of Robotics Research · doi:10.1177/02783649251344638 · Cited by 1

Computer Vision for Objects Used in Group Work: Challenges and Opportunities

Jung, C., Mannan, S., Fitzgerald, J., & Blanchard, N. (2025) · Communications in computer and information science · doi:10.1007/978-3-031-99264-3_23 · Cited by 1

Hand-held Object Reconstruction from RGB Video with Dynamic Interaction

Jiang, S., Ye, Q., Xie, R., Huo, Y., & Chen, J. (2025) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr52734.2025.01141 · Cited by 1

Propagative Distance Optimization for Motion Planning

Chen, Y. L., Xu, J., Cai, Y., Wong, T.-W., Ren, Z., Choset, H., & Shi, G. (2025) · Proceedings - IEEE International Conference on Robotics and Automation/Proceedings · doi:10.1109/icra55743.2025.11128392 · Cited by 1

Proactive Tactile Exploration for Object-Agnostic Shape Reconstruction from Minimal Visual Priors

Oikonomou, P., Retsinas, G., Maragos, P. A., & Tzafestas, C. S. (2025) · Proceedings - IEEE International Conference on Robotics and Automation/Proceedings · doi:10.1109/icra55743.2025.11127653 · Cited by 1

Learning From Imperfect Demonstrations With Self-Supervision for Robotic Manipulation

Wu, K., Liu, N., Zhao, Z., Qiu, D., Li, J., Che, Z., Xu, Z., & Tang, J. (2025) · Proceedings - IEEE International Conference on Robotics and Automation/Proceedings · doi:10.1109/icra55743.2025.11127918 · Cited by 5

Multi-Heuristic Robotic Bin Packing of Regular and Irregular Objects

Nickel, T., Bormann, R., & Arras, K. O. (2025) · Proceedings - IEEE International Conference on Robotics and Automation/Proceedings · doi:10.1109/icra55743.2025.11128421 · Cited by 1

Robust Manipulation via Contact Sensing

Koval, M. C. (2016) · KiltHub Repository · doi:10.1184/r1/6721358 · Cited by 1

An automated pick-and-place benchmarking system in robotics

Neumann, N., zu Borgsen, S. M., Lücking, P., & Wachsmuth, S. (2018) · IEEE International Conference on Autonomous Robot Systems and Competitions · doi:10.1109/icarsc.2018.8374190 · Cited by 1

Assembly Planning in Cluttered Environments Through Heterogeneous Reasoning

Beßler, D., Pomarlan, M., Akbari, A., Muhayyuddin, Diab, M., Rosell, J., Bateman, J. A., & Beetz, M. (2018) · Lecture notes in computer science · doi:10.1007/978-3-030-00111-7_18 · Cited by 1

3D Hand Joints Position Estimation with Graph Convolutional Networks: A GraphHands Baseline

Castro-Vargas, J.-A., García-García, A., Oprea, S., Martínez-González, P., & García‐Rodríguez, J. (2019) · Advances in intelligent systems and computing · doi:10.1007/978-3-030-36150-1_45 · Cited by 1

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

Çallı, B., Walsman, A., Singh, A., Srinivasa, S. S., Abbeel, P., & Dollar, A. M. (2015) · IEEE Robotics & Automation Magazine · doi:10.1109/mra.2015.2448951 · Cited by 602

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

Çallı, B., Walsman, A., Singh, A., Srinivasa, S. S., Abbeel, P., & Dollar, A. M. (2015) · arXiv (Cornell University) · doi:10.48550/arxiv.1502.03143 · Cited by 208

Yale-CMU-Berkeley dataset for robotic manipulation research

Çallı, B., Singh, A., Bruce, J., Walsman, A., Konolige, K., Srinivasa, S. S., Abbeel, P., & Dollar, A. M. (2017) · The International Journal of Robotics Research · doi:10.1177/0278364917700714 · Cited by 375

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

Khargonkar, N., Allu, S. H., Lu, Y., Jishnu Jaykumar, P., Prabhakaran, B., & Yu, X. (2024) · Proceedings - IEEE International Conference on Robotics and Automation/Proceedings · doi:10.1109/icra57147.2024.10610180 · Cited by 8

DexYCB: A Benchmark for Capturing Hand Grasping of Objects

Chao, Y.-W., Yang, W., Yu, X., Molchanov, P. A., Handa, A., Tremblay, J., Narang, Y., Wyk, K. V., Iqbal, U., Birchfield, S. T., et al. (2021) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr46437.2021.00893 · Cited by 296