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Grasping occluded objects in cluttered environments is an essential component in complex robotic manipulation tasks.
Planning Sensing Strategies in a Robot Work Cell with Multi-sensor Capabilities
S. A. Hutchinson, R. L. Cromwell, and A. C. Kak · 1988
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View Planning for Automated Three-dimensional Object Reconstruction and Inspection
W. R. Scott, G. Roth, and J.-F. Rivest · 2003
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Moveit![ros topics]
S. Chitta, I. Sucan, and S. Cousins · 2012
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Efficient Next-best-scan Planning for Autonomous 3D Surface Reconstruction of Unknown Objects
S. Kriegel, C. Rink, T. Bodenmüller, and M. Suppa · 2015
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TRAC-IK: An Open-source Library for Improved Solving of Generic Inverse Kinematics
P. Beeson and B. Ames · 2015
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Active Vision for Dexterous Grasping of Novel Objects
E. Arruda, J. Wyatt, and M. Kopicki · 2016
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High Precision Grasp Pose Detection in Dense Clutter
M. Gualtieri, A. Ten Pas, K. Saenko, and R. Platt · 2016
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Pairwise Decomposition of Image Sequences for Active Multi-View Recognition
E. Johns, S. Leutenegger, and A. J. Davison · 2016
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Pybullet, a Python Module for Physics Simulation for Games, Robotics and Machine Learning
E. Coumans and Y. Bai · 2016
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Dex-net 2.0: Deep Learning to Plan Robust Grasps with Synthetic Point Clouds and Analytic Grasp Metrics
J. Mahler, J. Liang, S. Niyaz, M. Laskey, R. Doan, X. Liu, J. A. Ojea, and K. Goldberg · 2017
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A Comparison of Volumetric Information Gain Metrics for Active 3D Object Reconstruction
J. Delmerico, S. Isler, R. Sabzevari, and D. Scaramuzza · 2018
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Open3D: A Modern Library for 3D Data Processing
Q.-Y. Zhou, J. Park, and V. Koltun · 2018
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6-DoF GraspNet: Variational Grasp Generation for Object Manipulation
A. Mousavian, C. Eppner, and D. Fox · 2019
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Learning Ambidextrous Robot Grasping Policies
J. Mahler, M. Matl, V. Satish, M. Danielczuk, B. DeRose, S. McKinley, and K. Goldberg · 2019
Cited alongside, same era.
Multi-View Picking: Next-best-view Reaching for Improved Grasping in Clutter
D. Morrison, P. Corke, and J. Leitner · 2019
Cited alongside, same era.
Learning Task-Oriented Grasping for Tool Manipulation from Simulated Self-Supervision
K. Fang, Y. Zhu, A. Garg, A. Kurenkov, V. Mehta, L. Fei-Fei, and S. Savarese · 2020
Cited alongside, same era.
Supervised Learning of the Next-Best-View for 3D Object Reconstruction
M. Mendoza, J. I. Vasquez-Gomez, H. Taud, L. E. Sucar, and C. Reta · 2020
Cited alongside, same era.
Grasping in the Wild:Learning 6DoF Closed-Loop Grasping from Low-Cost Demonstrations
S. Song, A. Zeng, J. Lee, and T. Funkhouser · 2020
Cited alongside, same era.
GraspNet-1Billion: A Large-Scale Benchmark for General Object Grasping
Closed-Loop Next-Best-View Planning for Target-Driven Grasping
M. Breyer, L. Ott, R. Siegwart, and J. J. Chung · 2022
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Deep Learning Approaches to Grasp Synthesis: A Review
R. Newbury, M. Gu, L. Chumbley, A. Mousavian, C. Eppner, J. Leitner, J. Bohg, A. Morales, T. Asfour, D. Kragic, and others · 2022
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Uncertainty Guided Policy for Active Robotic 3D Reconstruction using Neural Radiance Fields
S. Lee, L. Chen, J. Wang, A. Liniger, S. Kumar, and F. Yu · 2022
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Uncertainty-Driven Active Vision for Implicit Scene Reconstruction
E. J. Smith, M. Drozdzal, D. Nowrouzezahrai, D. Meger, and A. Romero-Soriano · 2022
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Active View Planning for Radiance Fields
K. Lin and B. Yi · 2022
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H.-S. Fang, C. Wang, M. Gou, and C. Lu · 2020
Cited alongside, same era.
Convolutional Occupancy Networks
S. Peng, M. Niemeyer, L. Mescheder, M. Pollefeys, and A. Geiger · 2020
Cited alongside, same era.
Volumetric Grasping Network: Real-time 6 DOF Grasp Detection in Clutter
M. Breyer, J. J. Chung, L. Ott, R. Siegwart, and J. Nieto · 2021
Cited alongside, same era.
Synergies Between Affordance and Geometry: 6-DoF Grasp Detection via Implicit Representations
Z. Jiang, Y. Zhu, M. Svetlik, K. Fang, and Y. Zhu · 2021
Cited alongside, same era.
NeRF: Representing Scenes as Neural Radiance Fields for View Synthesis
B. Mildenhall, P. P. Srinivasan, M. Tancik, J. T. Barron, R. Ramamoorthi, and R. Ng · 2021
Cited alongside, same era.
Vision-based Robotic Grasping from Object Localization, Object Pose Estimation to Grasp Estimation for Parallel Grippers: A Review
G. Du, K. Wang, S. Lian, and K. Zhao · 2021
Cited alongside, same era.
Contact-GraspNet: Efficient 6-DoF Grasp Generation in Cluttered Scenes
M. Sundermeyer, A. Mousavian, R. Triebel, and D. Fox · 2021
Cited alongside, same era.
X. Pan, Z. Lai, S. Song, and G. Huang · 2022
Later among the works it cites.
GraspNeRF: Multiview-based 6-DoF Grasp Detection for Transparent and Specular Objects Using Generalizable NeRF
Q. Dai, Y. Zhu, Y. Geng, C. Ruan, J. Zhang, and H. Wang · 2023
Closest in time.
Learning Any-View 6DoF Robotic Grasping in Cluttered Scenes via Neural Surface Rendering
S. Jauhri, I. Lunawat, and G. Chalvatzaki · 2023
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Edge Grasp Network: A Graph-Based SE(3)-invariant Approach to Grasp Detection
H. Huang, D. Wang, X. Zhu, R. Walters, and R. Platt · 2023
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NeU-NBV: Next Best View Planning Using Uncertainty Estimation in Image-Based Neural Rendering
L. Jin, X. Chen, J. Rückin, and M. Popović · 2023
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MIRA: Mental Imagery for Robotic Affordances
Y.-C. Lin, P. Florence, A. Zeng, J. T. Barron, Y. Du, W.-C. Ma, A. Simeonov, A. R. Garcia, and P. Isola · 2023
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View Planning in Robot Active Vision: A Survey of Systems, Algorithms, and Applications
R. Zeng, Y. Wen, W. Zhao, and Y.-J. Liu · 2096
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