3 accepted papers
Estimating 7-DoF grasping poses (6-DoF with gripper width) in cluttered scenes is a critical challenge for robotic manipulation. In such environments, object edges often contain many promising grasp candidates, but relying solely on incomplete single-view point cloud to infer them is difficult. Whil…
Stereo-based category-level shape and 6D pose estimation methods have the potential to generalize to a wider range of materials than RGBD methods, which often suffer from depth measurement errors. However, without explicit depth from two views, parameters to be estimated can become inherently entan…
In this work, we tackle the problem of 7-DoF grasping pose estimation(6-DoF with the opening width of parallel-jaw gripper) from point cloud data, which is a fundamental task in robotic manipulation. Most existing methods adopt 3D voxel CNNs as the backbone for their efficiency in handling unordered…