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

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Showing 26–50 of 246 papers

TitleStatusHype
Causal Counterfactuals for Improving the Robustness of Reinforcement LearningCode1
A Robotic Visual Grasping Design: Rethinking Convolution Neural Network with High-ResolutionsCode1
6IMPOSE: Bridging the Reality Gap in 6D Pose Estimation for Robotic GraspingCode1
Action Conditioned Tactile Prediction: case study on slip predictionCode1
6-DoF Pose Estimation of Household Objects for Robotic Manipulation: An Accessible Dataset and BenchmarkCode1
When Transformer Meets Robotic Grasping: Exploits Context for Efficient Grasp DetectionCode1
MetaGraspNet_v0: A Large-Scale Benchmark Dataset for Vision-driven Robotic Grasping via Physics-based Metaverse SynthesisCode1
CALVIN: A Benchmark for Language-Conditioned Policy Learning for Long-Horizon Robot Manipulation TasksCode1
Depth-aware Object Segmentation and Grasp Detection for Robotic Picking TasksCode1
"Good Robot! Now Watch This!": Repurposing Reinforcement Learning for Task-to-Task TransferCode1
CLIPort: What and Where Pathways for Robotic ManipulationCode1
The Role of Tactile Sensing in Learning and Deploying Grasp Refinement AlgorithmsCode1
CaTGrasp: Learning Category-Level Task-Relevant Grasping in Clutter from SimulationCode1
End-to-end Trainable Deep Neural Network for Robotic Grasp Detection and Semantic Segmentation from RGBCode1
REGRAD: A Large-Scale Relational Grasp Dataset for Safe and Object-Specific Robotic Grasping in ClutterCode1
Contact-GraspNet: Efficient 6-DoF Grasp Generation in Cluttered ScenesCode1
Object Detection and Pose Estimation from RGB and Depth Data for Real-time, Adaptive Robotic GraspingCode1
Object SLAM-Based Active Mapping and Robotic GraspingCode1
Same Object, Different Grasps: Data and Semantic Knowledge for Task-Oriented GraspingCode1
Goal-Auxiliary Actor-Critic for 6D Robotic Grasping with Point CloudsCode1
Learning Dexterous Grasping with Object-Centric Visual AffordancesCode1
Grasping Field: Learning Implicit Representations for Human GraspsCode1
Orientation Attentive Robotic Grasp Synthesis with Augmented Grasp Map RepresentationCode1
GraspNet-1Billion: A Large-Scale Benchmark for General Object GraspingCode1
Event-based Robotic Grasping Detection with Neuromorphic Vision Sensor and Event-Stream DatasetCode1
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All datasetsGraspNet-1BillionCornell Grasp DatasetJacquard dataset

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1FlexLoG-CDmAP56.02—Unverified
2GtG2.0mAP53.42—Unverified
3Scale-Balanced-Grasp-CDmAP48.97—Unverified
4graspness-CDmAP48.75—Unverified
5HGGD-CDmAP47.54—Unverified
6HGGDmAP44.24—Unverified
7graspnet-baseline-CDmAP35.45—Unverified
8graspnet-baselinemAP21.41—Unverified
#ModelMetricClaimedVerifiedStatus
1grasp_det_seg_cnn (rgb only, IW split)5 fold cross validation98.2—Unverified
2GR-ConvNet5 fold cross validation97.7—Unverified
3ResNet50 multi-grasp predictor5 fold cross validation96—Unverified
4Multi-Modal Grasp Predictor5 fold cross validation89.21—Unverified
5AlexNet, MultiGrasp5 fold cross validation88—Unverified
6GGCNN5 fold cross validation73—Unverified
7Fast Search5 fold cross validation60.5—Unverified
#ModelMetricClaimedVerifiedStatus
1Efficient-GraspingAccuracy (%)95.6—Unverified
2GR-ConvNetAccuracy (%)94.6—Unverified
3grasp_det_seg_cnn (rgb only)Accuracy (%)92.95—Unverified