SOTAVerified

Robotic Grasping

This task is composed of using Deep Learning to identify how best to grasp objects using robotic arms in different scenarios. This is a very complex task as it might involve dynamic environments and objects unknown to the network.

Papers

Showing 76100 of 246 papers

TitleStatusHype
A Benchmarking Study of Vision-based Robotic Grasping AlgorithmsCode0
Consensus-Driven Uncertainty for Robotic Grasping based on RGB PerceptionCode0
Composing Pick-and-Place Tasks By Grounding LanguageCode0
PGA: Personalizing Grasping Agents with Single Human-Robot InteractionCode0
Self-supervised 3D Shape and Viewpoint Estimation from Single Images for RoboticsCode0
A Fast Method For Computing Principal Curvatures From Range ImagesCode0
MonoSIM: Simulating Learning Behaviors of Heterogeneous Point Cloud Object Detectors for Monocular 3D Object DetectionCode0
Learning to Grasp on the Moon from 3D Octree Observations with Deep Reinforcement LearningCode0
Learning Object Placements For Relational Instructions by Hallucinating Scene RepresentationsCode0
Effective Deployment of CNNs for 3DoF Pose Estimation and Grasping in Industrial SettingsCode0
Solving the Real Robot Challenge using Deep Reinforcement LearningCode0
Adversarial samples for deep monocular 6D object pose estimationCode0
Jacquard: A Large Scale Dataset for Robotic Grasp DetectionCode0
DynGraspVS: Servoing Aided Grasping for Dynamic EnvironmentsCode0
Bimodal SegNet: Instance Segmentation Fusing Events and RGB Frames for Robotic GraspingCode0
Improving Robot Dual-System Motor Learning with Intrinsically Motivated Meta-Control and Latent-Space Experience ImaginationCode0
HiFi-CS: Towards Open Vocabulary Visual Grounding For Robotic Grasping Using Vision-Language ModelsCode0
Action Priors for Large Action Spaces in RoboticsCode0
IKEA Furniture Assembly Environment for Long-Horizon Complex Manipulation TasksCode0
Distributed Reinforcement Learning of Targeted Grasping with Active Vision for Mobile Manipulators0
Robotic Grasping of Harvested Tomato Trusses Using Vision and Online Learning0
DexVIP: Learning Dexterous Grasping with Human Hand Pose Priors from Video0
Automatic generation of realistic training data for learning parallel-jaw grasping from synthetic stereo images0
Attribute-Based Robotic Grasping with One-Grasp Adaptation0
Densely Supervised Grasp Detector (DSGD)0
Show:102550
← PrevPage 4 of 10Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1FlexLoG-CDmAP56.02Unverified
2GtG2.0mAP53.42Unverified
3Scale-Balanced-Grasp-CDmAP48.97Unverified
4graspness-CDmAP48.75Unverified
5HGGD-CDmAP47.54Unverified
6HGGDmAP44.24Unverified
7graspnet-baseline-CDmAP35.45Unverified
8graspnet-baselinemAP21.41Unverified
#ModelMetricClaimedVerifiedStatus
1grasp_det_seg_cnn (rgb only, IW split)5 fold cross validation98.2Unverified
2GR-ConvNet5 fold cross validation97.7Unverified
3ResNet50 multi-grasp predictor5 fold cross validation96Unverified
4Multi-Modal Grasp Predictor5 fold cross validation89.21Unverified
5AlexNet, MultiGrasp5 fold cross validation88Unverified
6GGCNN5 fold cross validation73Unverified
7Fast Search5 fold cross validation60.5Unverified
#ModelMetricClaimedVerifiedStatus
1Efficient-GraspingAccuracy (%)95.6Unverified
2GR-ConvNetAccuracy (%)94.6Unverified
3grasp_det_seg_cnn (rgb only)Accuracy (%)92.95Unverified