Data to 7 Oct 2026

Goal-Auxiliary Actor-Critic for 6D Robotic Grasping with Point Clouds

arXiv 2010.00824 ↗First posted 2 Oct 2020cs.RO cs.CVcited by 24

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Abstract (arXiv)

6D robotic grasping beyond top-down bin-picking scenarios is a challenging task. Previous solutions based on 6D grasp synthesis with robot motion planning usually operate in an open-loop setting, which are sensitive to grasp synthesis errors. In this work, we propose a new method for learning closed-loop control policies for 6D grasping. Our policy takes a segmented point cloud of an object from an egocentric camera as input, and outputs continuous 6D control actions of the robot gripper for grasping the object. We combine imitation learning and reinforcement learning and introduce a goal-auxiliary actor-critic algorithm for policy learning. We demonstrate that our learned policy can be integrated into a tabletop 6D grasping system and a human-robot handover system to improve the grasping performance of unseen objects. Our videos and code can be found at https://sites.google.com/view/gaddpg .

Key facts. Cited by 24 papers in the map (data through 7 Oct 2026). First posted on arXiv 2 Oct 2020.

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Citing papers per year: 2022: 7; 2023: 7; 2024: 5; 2025: 5.

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2024Scaling Proprioceptive-Visual Learning with Heterogeneous Pre-trained Transformerscited by 145
2022DexPoint: Generalizable Point Cloud Reinforcement Learning for Sim-to-Real Dexterous Manipulationcited by 78
2023DexArt: Benchmarking Generalizable Dexterous Manipulation with Articulated Objectscited by 64
2023NeRF in the Palm of Your Hand: Corrective Augmentation for Robotics via Novel-View Synthesiscited by 56
2024GenSim2: Scaling Robot Data Generation with Multi-modal and Reasoning LLMscited by 48
2024PoCo: Policy Composition from and for Heterogeneous Robot Learningcited by 42
2023Learning Human-to-Robot Handovers from Point Cloudscited by 34
2023HACMan: Learning Hybrid Actor-Critic Maps for 6D Non-Prehensile Manipulationcited by 27
2022Learning to Grasp the Ungraspable with Emergent Extrinsic Dexteritycited by 25
2022Mean Shift Mask Transformer for Unseen Object Instance Segmentationcited by 19
2023XVO: Generalized Visual Odometry via Cross-Modal Self-Trainingcited by 17
2022HandoverSim: A Simulation Framework and Benchmark for Human-to-Robot Object Handoverscited by 15

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2024GenH2R: Learning Generalizable Human-to-Robot Handover via Scalable Simulation, Demonstration, and Imitationcited by 14
2023SynH2R: Synthesizing Hand-Object Motions for Learning Human-to-Robot Handoverscited by 13
2022NeuralGrasps: Learning Implicit Representations for Grasps of Multiple Robotic Handscited by 12
2023Robot Fleet Learning via Policy Mergingcited by 11
2022DA2 Dataset: Toward Dexterity-Aware Dual-Arm Graspingcited by 10
2022Neural Motion Fields: Encoding Grasp Trajectories as Implicit Value Functionscited by 3
2024Stereo Hand-Object Reconstruction for Human-to-Robot Handovercited by 2
2025GraspCoT: Integrating Physical Property Reasoning for 6-DoF Grasping under Flexible Language Instructionscited by 2
2025Visuomotor Grasping with World Models for Surgical Robotscited by 1
2025Grasp-MPC: Closed-Loop Visual Grasping via Value-Guided Model Predictive Controlcited by 1
2025PointNet4D: A Lightweight 4D Point Cloud Video Backbone for Online and Offline Perception in Robotic Applicationscited by 1
2025COMBO-Grasp: Learning Constraint-Based Manipulation for Bimanual Occluded Graspingcited by 0

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