{"about":{"non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","site":"https://codewithpapers.app","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page","syntology":{"site":"https://syntology.ai","developers":"https://syntology.ai/developers","mcp":{"server":"https://syntology.ai/mcp","transport":"streamable-http","server_card":"https://syntology.ai/.well-known/mcp/server-card.json","auth":{"type":"trial token, no account","trial_token":"https://syntology.ai/api/oauth/trial/token","method":"POST","docs":"https://syntology.ai/developers"}},"have":"https://syntology.ai/api/graph/have?x=<method, arXiv id or title> (free, answers coverage only)","paper_base":"https://syntology.ai/paper/","atlas_base":"https://app.syntology.ai/?focus="},"machine_readable":[{"url":"https://codewithpapers.app/llms.txt","what":"the machine catalog: every machine-readable file, counted"},{"url":"https://codewithpapers.app/index/manifest.json","what":"paper-to-code index by arXiv id, with Syntology's counts"},{"url":"https://codewithpapers.app/search/manifest.json","what":"site search index (titles, authors) and its files"},{"url":"https://codewithpapers.app/download","what":"bulk files: Syntology's layer, described there"},{"url":"https://codewithpapers.app/build_manifest.json","what":"the build record: inputs, counts, exclusions, probes"}]},"url":"/task/robotic-grasping/papers/2","list_of":"/task/robotic-grasping","task":"Robotic Grasping","archive":{"snapshot":"2025-07-28"},"key_notes":{"n_ran_checked":"legacy name, kept unchanged so existing readers do not break: it counts the samples that ran with no instrument failure (honoured, violated, and ran with no contract checked); it does not mean a contract was checked, and the pages print it as 'K with no instrument failure', not 'K checked'","n_constructed":"a sub-count of the samples that ran, never subtracted from them and never a failure: an executed sample whose run returned an instance of its own class (fixture_out_type equals the entry name): the run built an object and did not compute a result (Syntology's RAN record, counts.constructed)"},"syntology_read_at":"2026-09-28T10:30:06+00:00","order":"archive","order_definition":"repositories listed in the archive (most first), then date (newest first), then slug","page":2,"pages_in_order":3,"rows_per_page":100,"rows":[101,200],"of":246,"counts":{"archive_papers_tagged":246,"with_a_code_link":94,"where_syntology_ran_a_sample":11,"not_listed_spam_title":0,"listed":246,"listed_where_code_ran":11,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":10,"every_run_a_failure_of_syntologys_instrument":1,"listed_with_a_run_with_no_instrument_failure":10,"listed_every_run_a_failure_of_syntologys_instrument":1,"filter":{"states":["a run with no instrument failure","any run, instrument failures included"],"default":"a run with no instrument failure","note":"on the 'only where code ran' pages the default hides, in the browser, the rows where every run was a failure of Syntology's instrument; the second state shows them again. Rows are hidden, never re-ordered; these twins list every row"}},"definition":"distinct papers the archive tags; 'where Syntology ran a sample' counts papers with at least one harvested sample that ran, which is not a correctness claim"},"first_page":"/task/robotic-grasping","prev":"/task/robotic-grasping","next":"/task/robotic-grasping/papers/3","papers":[{"url":null,"slug":"vitapes-visuotactile-position-encodings-for","title":"ViTaPEs: Visuotactile Position Encodings for Cross-Modal Alignment in Multimodal Transformers","date":"2025-05-26","arxiv_id":"2505.20032","repositories_listed":0,"syntology":null},{"url":"/paper/grasp-the-graph-gtg-2-0-ensemble-of-gnns-for","slug":"grasp-the-graph-gtg-2-0-ensemble-of-gnns-for","title":"Grasp the Graph (GtG) 2.0: Ensemble of GNNs for High-Precision Grasp Pose Detection in Clutter","date":"2025-05-05","arxiv_id":"2505.02664","repositories_listed":0,"syntology":null},{"url":null,"slug":"category-level-and-open-set-object-pose","title":"Category-Level and Open-Set Object Pose Estimation for Robotics","date":"2025-04-28","arxiv_id":"2504.19572","repositories_listed":0,"syntology":null},{"url":null,"slug":"zerograsp-zero-shot-shape-reconstruction","title":"ZeroGrasp: Zero-Shot Shape Reconstruction Enabled Robotic Grasping","date":"2025-04-15","arxiv_id":"2504.10857","repositories_listed":0,"syntology":null},{"url":null,"slug":"corner-grasp-multi-action-grasp-detection-and","title":"Corner-Grasp: Multi-Action Grasp Detection and Active Gripper Adaptation for Grasping in Cluttered Environments","date":"2025-04-02","arxiv_id":"2504.01861","repositories_listed":0,"syntology":null},{"url":null,"slug":"gaa-tso-geometry-aware-assisted-depth","title":"GAA-TSO: Geometry-Aware Assisted Depth Completion for Transparent and Specular Objects","date":"2025-03-21","arxiv_id":"2503.17106","repositories_listed":0,"syntology":null},{"url":null,"slug":"grasping-partially-occluded-objects-using","title":"Grasping Partially Occluded Objects Using Autoencoder-Based Point Cloud Inpainting","date":"2025-03-16","arxiv_id":"2503.12549","repositories_listed":0,"syntology":null},{"url":null,"slug":"neugrasp-generalizable-neural-surface","title":"NeuGrasp: Generalizable Neural Surface Reconstruction with Background Priors for Material-Agnostic Object Grasp Detection","date":"2025-03-05","arxiv_id":"2503.03511","repositories_listed":0,"syntology":null},{"url":null,"slug":"robograsp-a-universal-grasping-policy-for","title":"RoboGrasp: A Universal Grasping Policy for Robust Robotic Control","date":"2025-02-05","arxiv_id":"2502.03072","repositories_listed":0,"syntology":null},{"url":null,"slug":"attribute-based-robotic-grasping-with-data","title":"Attribute-Based Robotic Grasping with Data-Efficient Adaptation","date":"2025-01-04","arxiv_id":"2501.02149","repositories_listed":0,"syntology":null},{"url":null,"slug":"gaussianproperty-integrating-physical","title":"GaussianProperty: Integrating Physical Properties to 3D Gaussians with LMMs","date":"2024-12-15","arxiv_id":"2412.11258","repositories_listed":0,"syntology":null},{"url":null,"slug":"an-adaptive-grasping-force-tracking-strategy","title":"An Adaptive Grasping Force Tracking Strategy for Nonlinear and Time-Varying Object Behaviors","date":"2024-12-03","arxiv_id":"2412.02335","repositories_listed":0,"syntology":null},{"url":null,"slug":"sparsegrasp-robotic-grasping-via-3d-semantic","title":"SparseGrasp: Robotic Grasping via 3D Semantic Gaussian Splatting from Sparse Multi-View RGB Images","date":"2024-12-03","arxiv_id":"2412.02140","repositories_listed":0,"syntology":null},{"url":null,"slug":"towards-cross-device-and-training-free","title":"Towards Cross-device and Training-free Robotic Grasping in 3D Open World","date":"2024-11-27","arxiv_id":"2411.18133","repositories_listed":0,"syntology":null},{"url":null,"slug":"vmgnet-a-low-computational-complexity-robotic","title":"VMGNet: A Low Computational Complexity Robotic Grasping Network Based on VMamba with Multi-Scale Feature Fusion","date":"2024-11-19","arxiv_id":"2411.12520","repositories_listed":0,"syntology":null},{"url":null,"slug":"grammarization-based-grasping-with-deep-multi","title":"Grammarization-Based Grasping with Deep Multi-Autoencoder Latent Space Exploration by Reinforcement Learning Agent","date":"2024-11-13","arxiv_id":"2411.08566","repositories_listed":0,"syntology":null},{"url":null,"slug":"manibox-enhancing-spatial-grasping","title":"ManiBox: Enhancing Spatial Grasping Generalization via Scalable Simulation Data Generation","date":"2024-11-04","arxiv_id":"2411.01850","repositories_listed":0,"syntology":null},{"url":null,"slug":"bayesian-optimization-for-robust-robotic","title":"Bayesian optimization for robust robotic grasping using a sensorized compliant hand","date":"2024-10-23","arxiv_id":"2410.18237","repositories_listed":0,"syntology":null},{"url":null,"slug":"from-words-to-poses-enhancing-novel-object","title":"From Words to Poses: Enhancing Novel Object Pose Estimation with Vision Language Models","date":"2024-09-09","arxiv_id":"2409.05413","repositories_listed":0,"syntology":null},{"url":null,"slug":"target-oriented-object-grasping-via","title":"Target-Oriented Object Grasping via Multimodal Human Guidance","date":"2024-08-20","arxiv_id":"2408.11138","repositories_listed":0,"syntology":null},{"url":null,"slug":"2408-03238","title":"LAC-Net: Linear-Fusion Attention-Guided Convolutional Network for Accurate Robotic Grasping Under the Occlusion","date":"2024-08-06","arxiv_id":"2408.03238","repositories_listed":0,"syntology":null},{"url":null,"slug":"2408-00337","title":"DistillGrasp: Integrating Features Correlation with Knowledge Distillation for Depth Completion of Transparent Objects","date":"2024-08-01","arxiv_id":"2408.00337","repositories_listed":0,"syntology":null},{"url":null,"slug":"local-occupancy-enhanced-object-grasping-with","title":"Local Occupancy-Enhanced Object Grasping with Multiple Triplanar Projection","date":"2024-07-22","arxiv_id":"2407.15771","repositories_listed":0,"syntology":null},{"url":null,"slug":"close-the-sim2real-gap-via-physically-based","title":"Close the Sim2real Gap via Physically-based Structured Light Synthetic Data Simulation","date":"2024-07-17","arxiv_id":"2407.12449","repositories_listed":0,"syntology":null},{"url":null,"slug":"targo-benchmarking-target-driven-object","title":"TARGO: Benchmarking Target-driven Object Grasping under Occlusions","date":"2024-07-08","arxiv_id":"2407.06168","repositories_listed":0,"syntology":null},{"url":null,"slug":"3d-feature-distillation-with-object-centric","title":"3D Feature Distillation with Object-Centric Priors","date":"2024-06-26","arxiv_id":"2406.18742","repositories_listed":0,"syntology":null},{"url":null,"slug":"towards-open-world-grasping-with-large-vision","title":"Towards Open-World Grasping with Large Vision-Language Models","date":"2024-06-26","arxiv_id":"2406.18722","repositories_listed":0,"syntology":null},{"url":null,"slug":"nerf-feat-6d-object-pose-estimation-using","title":"NeRF-Feat: 6D Object Pose Estimation using Feature Rendering","date":"2024-06-19","arxiv_id":"2406.13796","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-brief-survey-on-leveraging-large-scale","title":"A Brief Survey on Leveraging Large Scale Vision Models for Enhanced Robot Grasping","date":"2024-06-17","arxiv_id":"2406.11786","repositories_listed":0,"syntology":null},{"url":null,"slug":"language-driven-grasp-detection-1","title":"Language-driven Grasp Detection","date":"2024-06-13","arxiv_id":"2406.09489","repositories_listed":0,"syntology":null},{"url":null,"slug":"you-only-scan-once-a-dynamic-scene","title":"You Only Scan Once: A Dynamic Scene Reconstruction Pipeline for 6-DoF Robotic Grasping of Novel Objects","date":"2024-04-04","arxiv_id":"2404.03462","repositories_listed":0,"syntology":null},{"url":null,"slug":"robotics-and-computer-integrated","title":"Robotics and Computer-Integrated Manufacturing","date":"2024-04-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"said-nerf-segmentation-aided-nerf-for-depth","title":"SAID-NeRF: Segmentation-AIDed NeRF for Depth Completion of Transparent Objects","date":"2024-03-28","arxiv_id":"2403.19607","repositories_listed":0,"syntology":null},{"url":null,"slug":"speeding-up-6-dof-grasp-sampling-with-quality","title":"Speeding up 6-DoF Grasp Sampling with Quality-Diversity","date":"2024-03-10","arxiv_id":"2403.06173","repositories_listed":0,"syntology":null},{"url":null,"slug":"grasping-trajectory-optimization-with-point","title":"Grasping Trajectory Optimization with Point Clouds","date":"2024-03-08","arxiv_id":"2403.05466","repositories_listed":0,"syntology":null},{"url":null,"slug":"phygrasp-generalizing-robotic-grasping-with","title":"PhyGrasp: Generalizing Robotic Grasping with Physics-informed Large Multimodal Models","date":"2024-02-26","arxiv_id":"2402.16836","repositories_listed":0,"syntology":null},{"url":null,"slug":"jacquard-v2-refining-datasets-using-the-human","title":"Jacquard V2: Refining Datasets using the Human In the Loop Data Correction Method","date":"2024-02-08","arxiv_id":"2402.05747","repositories_listed":0,"syntology":null},{"url":null,"slug":"physics-encoded-graph-neural-networks-for","title":"Physics-Encoded Graph Neural Networks for Deformation Prediction under Contact","date":"2024-02-05","arxiv_id":"2402.03466","repositories_listed":0,"syntology":null},{"url":null,"slug":"robust-analysis-of-multi-task-learning-on-a","title":"Robust Analysis of Multi-Task Learning Efficiency: New Benchmarks on Light-Weighed Backbones and Effective Measurement of Multi-Task Learning Challenges by Feature Disentanglement","date":"2024-02-05","arxiv_id":"2402.03557","repositories_listed":0,"syntology":null},{"url":null,"slug":"agile-approach-based-grasp-inference-learned","title":"AGILE: Approach-based Grasp Inference Learned from Element Decomposition","date":"2024-02-02","arxiv_id":"2402.01303","repositories_listed":0,"syntology":null},{"url":null,"slug":"synthetic-data-enables-faster-annotation-and","title":"Synthetic data enables faster annotation and robust segmentation for multi-object grasping in clutter","date":"2024-01-24","arxiv_id":"2401.13405","repositories_listed":0,"syntology":null},{"url":null,"slug":"reinforcement-learning-based-bionic-reflex","title":"Reinforcement Learning-Based Bionic Reflex Control for Anthropomorphic Robotic Grasping exploiting Domain Randomization","date":"2023-12-08","arxiv_id":"2312.05023","repositories_listed":0,"syntology":null},{"url":null,"slug":"fvit-grasp-grasping-objects-with-using-fast","title":"FViT-Grasp: Grasping Objects With Using Fast Vision Transformers","date":"2023-11-23","arxiv_id":"2311.13986","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-vision-guided-robotic-system-for-grasping","title":"Robotic Grasping of Harvested Tomato Trusses Using Vision and Online Learning","date":"2023-09-29","arxiv_id":"2309.17170","repositories_listed":0,"syntology":null},{"url":null,"slug":"robotic-handling-of-compliant-food-objects-by","title":"Robotic Handling of Compliant Food Objects by Robust Learning from Demonstration","date":"2023-09-22","arxiv_id":"2309.12856","repositories_listed":0,"syntology":null},{"url":null,"slug":"wall-e-embodied-robotic-waiter-load-lifting","title":"WALL-E: Embodied Robotic WAiter Load Lifting with Large Language Model","date":"2023-08-30","arxiv_id":"2308.15962","repositories_listed":0,"syntology":null},{"url":null,"slug":"instance-segmentation-based-6d-pose","title":"Instance segmentation based 6D pose estimation of industrial objects using point clouds for robotic bin-picking","date":"2023-08-10","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"dmfc-graspnet-differentiable-multi-fingered","title":"DMFC-GraspNet: Differentiable Multi-Fingered Robotic Grasp Generation in Cluttered Scenes","date":"2023-08-01","arxiv_id":"2308.00456","repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-any-view-6dof-robotic-grasping-in","title":"Learning Any-View 6DoF Robotic Grasping in Cluttered Scenes via Neural Surface Rendering","date":"2023-06-12","arxiv_id":"2306.07392","repositories_listed":0,"syntology":null},{"url":null,"slug":"self-supervised-instance-segmentation-by","title":"Self-Supervised Instance Segmentation by Grasping","date":"2023-05-10","arxiv_id":"2305.06305","repositories_listed":0,"syntology":null},{"url":null,"slug":"fast-graspnext-a-fast-self-attention-neural","title":"Fast GraspNeXt: A Fast Self-Attention Neural Network Architecture for Multi-task Learning in Computer Vision Tasks for Robotic Grasping on the Edge","date":"2023-04-21","arxiv_id":"2304.11196","repositories_listed":0,"syntology":null},{"url":null,"slug":"implicit-representation-priors-meet","title":"Implicit representation priors meet Riemannian geometry for Bayesian robotic grasping","date":"2023-04-18","arxiv_id":"2304.08805","repositories_listed":0,"syntology":null},{"url":null,"slug":"shapeshift-superquadric-based-object-pose","title":"ShapeShift: Superquadric-based Object Pose Estimation for Robotic Grasping","date":"2023-04-10","arxiv_id":"2304.04861","repositories_listed":0,"syntology":null},{"url":null,"slug":"natural-language-robot-programming-nlp","title":"Natural Language Robot Programming: NLP integrated with autonomous robotic grasping","date":"2023-04-06","arxiv_id":"2304.02993","repositories_listed":0,"syntology":null},{"url":null,"slug":"simulation-based-bayesian-inference-for","title":"Simulation-based Bayesian inference for robotic grasping","date":"2023-03-10","arxiv_id":"2303.05873","repositories_listed":0,"syntology":null},{"url":null,"slug":"perceiving-unseen-3d-objects-by-poking-the","title":"Perceiving Unseen 3D Objects by Poking the Objects","date":"2023-02-26","arxiv_id":"2302.13375","repositories_listed":0,"syntology":null},{"url":null,"slug":"deep-reinforcement-learning-for-robotic-2","title":"Deep Reinforcement Learning for Robotic Pushing and Picking in Cluttered Environment","date":"2023-02-21","arxiv_id":"2302.10717","repositories_listed":0,"syntology":null},{"url":null,"slug":"towards-precise-model-free-robotic-grasping","title":"Towards Precise Model-free Robotic Grasping with Sim-to-Real Transfer Learning","date":"2023-01-28","arxiv_id":"2301.12249","repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-6-dof-fine-grained-grasp-detection","title":"Learning 6-DoF Fine-grained Grasp Detection Based on Part Affordance Grounding","date":"2023-01-27","arxiv_id":"2301.11564","repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-to-generate-all-feasible-actions","title":"Learning to Generate All Feasible Actions","date":"2023-01-26","arxiv_id":"2301.11461","repositories_listed":0,"syntology":null},{"url":null,"slug":"nerf-in-the-palm-of-your-hand-corrective","title":"NeRF in the Palm of Your Hand: Corrective Augmentation for Robotics via Novel-View Synthesis","date":"2023-01-18","arxiv_id":"2301.08556","repositories_listed":0,"syntology":null},{"url":null,"slug":"3dsgrasp-3d-shape-completion-for-robotic","title":"3DSGrasp: 3D Shape-Completion for Robotic Grasp","date":"2023-01-02","arxiv_id":"2301.00866","repositories_listed":0,"syntology":null},{"url":null,"slug":"neural-fields-for-robotic-object-manipulation","title":"One-Shot Neural Fields for 3D Object Understanding","date":"2022-10-21","arxiv_id":"2210.12126","repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-object-affordance-with-contact-and","title":"Contact2Grasp: 3D Grasp Synthesis via Hand-Object Contact Constraint","date":"2022-10-17","arxiv_id":"2210.09245","repositories_listed":0,"syntology":null},{"url":null,"slug":"monograspnet-6-dof-grasping-with-a-single-rgb","title":"MonoGraspNet: 6-DoF Grasping with a Single RGB Image","date":"2022-09-26","arxiv_id":"2209.13036","repositories_listed":0,"syntology":null},{"url":null,"slug":"gp-net-grasp-proposal-for-mobile-manipulators","title":"GP-net: Flexible Viewpoint Grasp Proposal","date":"2022-09-21","arxiv_id":"2209.10404","repositories_listed":0,"syntology":null},{"url":null,"slug":"robots-enact-malignant-stereotypes","title":"Robots Enact Malignant Stereotypes","date":"2022-07-23","arxiv_id":"2207.11569","repositories_listed":0,"syntology":null},{"url":null,"slug":"efficient-and-robust-training-of-dense-object","title":"Efficient and Robust Training of Dense Object Nets for Multi-Object Robot Manipulation","date":"2022-06-24","arxiv_id":"2206.12145","repositories_listed":0,"syntology":null},{"url":null,"slug":"evaluating-gaussian-grasp-maps-for-generative","title":"Evaluating Gaussian Grasp Maps for Generative Grasping Models","date":"2022-06-01","arxiv_id":"2206.00432","repositories_listed":0,"syntology":null},{"url":null,"slug":"physics-guided-hierarchical-reward-mechanism","title":"Physics-Guided Hierarchical Reward Mechanism for Learning-Based Robotic Grasping","date":"2022-05-26","arxiv_id":"2205.13561","repositories_listed":0,"syntology":null},{"url":null,"slug":"open-arms-open-source-arms-hands-control","title":"Open Arms: Open-Source Arms, Hands & Control","date":"2022-05-20","arxiv_id":"2205.12992","repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-6-dof-object-poses-to-grasp-category","title":"Learning 6-DoF Object Poses to Grasp Category-level Objects by Language Instructions","date":"2022-05-09","arxiv_id":"2205.04028","repositories_listed":0,"syntology":null},{"url":null,"slug":"hrpose-real-time-high-resolution-6d-pose","title":"HRPose: Real-Time High-Resolution 6D Pose Estimation Network Using Knowledge Distillation","date":"2022-04-20","arxiv_id":"2204.09429","repositories_listed":0,"syntology":null},{"url":null,"slug":"glocal-glocalized-curriculum-aided-learning","title":"GloCAL: Glocalized Curriculum-Aided Learning of Multiple Tasks with Application to Robotic Grasping","date":"2022-04-14","arxiv_id":"2204.06835","repositories_listed":0,"syntology":null},{"url":null,"slug":"sim-to-real-6d-object-pose-estimation-via","title":"Sim-to-Real 6D Object Pose Estimation via Iterative Self-training for Robotic Bin Picking","date":"2022-04-14","arxiv_id":"2204.07049","repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-to-synthesize-volumetric-meshes-from","title":"Learning to Synthesize Volumetric Meshes from Vision-based Tactile Imprints","date":"2022-03-29","arxiv_id":"2203.15155","repositories_listed":0,"syntology":null},{"url":null,"slug":"3d-object-reconstruction-and-6d-pose","title":"3D object reconstruction and 6D-pose estimation from 2D shape for robotic grasping of objects","date":"2022-03-02","arxiv_id":"2203.01051","repositories_listed":0,"syntology":null},{"url":null,"slug":"safer-data-efficient-and-safe-reinforcement-1","title":"SAFER: Data-Efficient and Safe Reinforcement Learning via Skill Acquisition","date":"2022-02-10","arxiv_id":"2202.04849","repositories_listed":0,"syntology":null},{"url":null,"slug":"dexvip-learning-dexterous-grasping-with-human","title":"DexVIP: Learning Dexterous Grasping with Human Hand Pose Priors from Video","date":"2022-02-01","arxiv_id":"2202.00164","repositories_listed":0,"syntology":null},{"url":null,"slug":"automatic-generation-of-realistic-training","title":"Automatic generation of realistic training data for learning parallel-jaw grasping from synthetic stereo images","date":"2021-12-07","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"demograsp-few-shot-learning-for-robotic","title":"DemoGrasp: Few-Shot Learning for Robotic Grasping with Human Demonstration","date":"2021-12-06","arxiv_id":"2112.02849","repositories_listed":0,"syntology":null},{"url":null,"slug":"mpf6d-masked-pyramid-fusion-6d-pose","title":"MPF6D: Masked Pyramid Fusion 6D Pose Estimation","date":"2021-11-17","arxiv_id":"2111.09378","repositories_listed":0,"syntology":null},{"url":null,"slug":"6d-pose-estimation-with-combined-deep","title":"6D Pose Estimation with Combined Deep Learning and 3D Vision Techniques for a Fast and Accurate Object Grasping","date":"2021-11-11","arxiv_id":"2111.06276","repositories_listed":0,"syntology":null},{"url":null,"slug":"when-neural-networks-using-different-sensors","title":"When Neural Networks Using Different Sensors Create Similar Features","date":"2021-11-04","arxiv_id":"2111.02732","repositories_listed":0,"syntology":null},{"url":null,"slug":"validate-on-sim-detect-on-real-model","title":"Validate on Sim, Detect on Real -- Model Selection for Domain Randomization","date":"2021-11-01","arxiv_id":"2111.00765","repositories_listed":0,"syntology":null},{"url":null,"slug":"safer-data-efficient-and-safe-reinforcement","title":"SAFER: Data-Efficient and Safe Reinforcement Learning Through Skill Acquisition","date":"2021-09-29","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"simulation-based-bayesian-inference-for-multi","title":"Simulation-based Bayesian inference for multi-fingered robotic grasping","date":"2021-09-29","arxiv_id":"2109.14275","repositories_listed":0,"syntology":null},{"url":null,"slug":"sample-efficient-safety-assurances-using","title":"Sample-Efficient Safety Assurances using Conformal Prediction","date":"2021-09-28","arxiv_id":"2109.14082","repositories_listed":0,"syntology":null},{"url":null,"slug":"robust-estimation-of-reflection-symmetry-in","title":"Robust Extrinsic Symmetry Estimation in 3D Point Clouds","date":"2021-09-21","arxiv_id":"2109.09927","repositories_listed":0,"syntology":null},{"url":"/paper/objectfolder-a-dataset-of-objects-with","slug":"objectfolder-a-dataset-of-objects-with","title":"ObjectFolder: A Dataset of Objects with Implicit Visual, Auditory, and Tactile Representations","date":"2021-09-16","arxiv_id":"2109.07991","repositories_listed":0,"syntology":null},{"url":null,"slug":"research-challenges-and-progress-in-robotic","title":"Research Challenges and Progress in Robotic Grasping and Manipulation Competitions","date":"2021-08-03","arxiv_id":"2108.01483","repositories_listed":0,"syntology":null},{"url":null,"slug":"domestic-waste-detection-and-grasping-points","title":"Domestic waste detection and grasping points for robotic picking up","date":"2021-05-14","arxiv_id":"2105.06825","repositories_listed":0,"syntology":null},{"url":null,"slug":"investigations-on-output-parameterizations-of","title":"Investigations on Output Parameterizations of Neural Networks for Single Shot 6D Object Pose Estimation","date":"2021-04-15","arxiv_id":"2104.07528","repositories_listed":0,"syntology":null},{"url":null,"slug":"attribute-based-robotic-grasping-with-one","title":"Attribute-Based Robotic Grasping with One-Grasp Adaptation","date":"2021-04-06","arxiv_id":"2104.02271","repositories_listed":0,"syntology":null},{"url":null,"slug":"collision-aware-target-driven-object-grasping","title":"Collision-Aware Target-Driven Object Grasping in Constrained Environments","date":"2021-04-01","arxiv_id":"2104.00776","repositories_listed":0,"syntology":null},{"url":null,"slug":"suctionnet-1billion-a-large-scale-benchmark","title":"SuctionNet-1Billion: A Large-Scale Benchmark for Suction Grasping","date":"2021-03-23","arxiv_id":"2103.12311","repositories_listed":0,"syntology":null},{"url":null,"slug":"ddgc-generative-deep-dexterous-grasping-in","title":"DDGC: Generative Deep Dexterous Grasping in Clutter","date":"2021-03-08","arxiv_id":"2103.04783","repositories_listed":0,"syntology":null},{"url":null,"slug":"pointguard-provably-robust-3d-point-cloud","title":"PointGuard: Provably Robust 3D Point Cloud Classification","date":"2021-03-04","arxiv_id":"2103.03046","repositories_listed":0,"syntology":null},{"url":null,"slug":"cooking-object-s-state-identification-without","title":"Cooking Object's State Identification Without Using Pretrained Model","date":"2021-03-03","arxiv_id":"2103.02305","repositories_listed":0,"syntology":null},{"url":"/paper/lightweight-convolutional-neural-network-with","slug":"lightweight-convolutional-neural-network-with","title":"Lightweight Convolutional Neural Network with Gaussian-based Grasping Representation for Robotic Grasping Detection","date":"2021-01-25","arxiv_id":"2101.10226","repositories_listed":0,"syntology":null}],"record_sha256":"a2375dc3d3c816e90c4b4e942fe8da69554da21e800a899726431ca84f332715","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}