2D and 3D Grasp Planners for the GET Asymmetrical Gripper
For robotic grasping with asymmetrical grippers, the paper provides a fast and effective planner that significantly outperforms a simple baseline, though the method is incremental.
The paper presents two grasp planners for the GET asymmetrical gripper: GET-2D-1.0 (fast, single-view RGB-D) and GET-3D-1.0 (mesh-based, slower). Physical experiments show GET-2D-1.0 improves over a bounding box baseline by over 40% in lift success, shake survival, and force resistance, while GET-3D-1.0 offers slight improvements but is much slower (17s vs 683ms).
In this paper, we introduce GET-2D-1.0, a fast grasp planner for the GET asymmetrical gripper that operates from a single-view RGB-D image, using the Ferrari-Canny metric and a novel sampling strategy, and GET-3D-1.0, a mesh-based method using a 3D gripper model and ray-tracing. We evaluate both grasp planners against baselines with physical experiments, which suggest that GET-2D-1.0 can improve over a bounding box baseline by over 40% in lift success, shake survival, and force resistance. Experiments with GET-3D-1.0 suggest slight improvement compared to GET-2D-1.0 on lift success and shake survival, but are more computationally expensive, averaging 17 seconds of planning compared to 683 ms for GET-2D-1.0.